sumar fiŞa de verificare în cadrul comisiei de i candidat ... · sumar fiŞa de verificare a...

SUMAR FIŞA DE VERIFICARE

a îndeplinirii standardelor minimale naţionale de acordare a titlului de abilitarei

în cadrul comisiei de Informatică

CANDIDAT: Ruxandra Stoean

Domeniul de activitate

(Indicator, Criteriu) Punctaj minim (puncte) Punctaj realizatii (puncte)

Informatică, Indicator B,

Producția științifică

56 (24 de tip A si 16 de tip

minim B)

70,67

(49 de tip A, 54,33 de tip minim B)

Informatică, Indicator C,

Impactul rezultatelor 120 (40 de tip minim B) 436,5 (338 de tip minim B)

Informatică, Indicator D,

Performanța academică 60 72,33

Total 236 579,5

Data

03.10.2016

i Conform Ordinului nr. 5648/13.12.2013 pentru modificarea art. 3 din anexa nr. 1 la Ordinul ministrul educației,

cercetării, tineretului și sportului nr. 5691/2011 privind aprobarea Regulamentului de funcţionare a Consiliului

Naţional de Atestare a Titlurilor, Diplomelor şi Certificatelor Universitare în vederea evaluării tezelor de abilitare şi

a modelului Cererii-tip pentru susţinerea tezei de abilitare, publicat in Monitorul Oficial al României, Partea I, nr.

811/20.12.2013 ii Punctaj calculat după cele două seturi de liste (ianuarie 2013 și ianuarie 2014) privind clasificarea forumurilor din

domeniul informatică și serviciul web de determinare a clasificării jurnalelor din alte domenii decât informatica,

conform site-ului web http://informatica-universitaria.ro/ppages/16/

Nr Referinta bibliografica Tip* Puncte Workshop Autori Ponderat

1

Ruxandra Stoean, Catalin Stoean, Modeling Medical Decision

Making by Support Vector Machines, Explaining by Rules of

Evolutionary Algorithms with Feature Selection, Expert Systems

with Applications, Vol. 40 Issue 7, June, 2013

pp. 2677-2686, 2013,

http://www.sciencedirect.com/science/article/pii/S0957417412012

171.

J85 8 - 2 8

2

Ruxandra Stoean, Catalin Stoean, Monica Lupsor, Horia Stefanescu,

Radu Badea, Evolutionary-Driven Support Vector Machines for

Determining the Degree of Liver Fibrosis in Chronic Hepatitis C,

Artificial Intelligence in Medicine, Elsevier, Vol. 51, Issue 1, pp. 53-

65, ISSN 0933-3657, 2011,

http://www.ncbi.nlm.nih.gov/pubmed/20675106.

J293 4 - 5 1,33

3

Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D.

Dumitrescu, Support Vector Machine Learning with an Evolutionary

Engine, Journal of the Operational Research Society, Palgrave

Macmillan, Vol. 60, Issue 8 (August 2009), Special Issue: Data

Mining and Operational Research: Techniques and Applications,

Kweku-Muata Osei-Bryson and Vic J Rayward-Smith (Guest Editors),

pp. 1116-1122, ISSN 0160-5682, 2009,

https://www.jstor.org/stable/40206837.

Servici

ul

WEB

4 - 5 1,33

4

Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu,

Evolutionary Multi-class Support Vector Machines for Classification,

International Journal of Computers, Communications & Control,

Supplementary Issue, pp. 423 – 428, ISSN 1841-9836, 2006,

http://apps.webofknowledge.com/full_record.do?product=WOS&s

earch_mode=GeneralSearch&qid=2&SID=V1qF3TxY5Gb25YcGa5J&

page=3&doc=21.

J736 2 - 4 1

5

Ruxandra Stoean, Catalin Stoean, Monica Lupsor, Horia Stefanescu,

Radu Badea, Evolutionary Conditional Rules versus Support Vector

Machines Weighted Formulas for Liver Fibrosis Degree Prediction,

Annals of the University of Craiova, Mathematics and Computer

Science Series, Vol. 37, No. 1, pp. 43-54, 2010,

http://inf.ucv.ro/~ami/index.php/ami/article/view/307.

Lista

20142 - 5 0,67

6

Ruxandra Stoean, Catalin Stoean, Adrian Sandita, Daniela Ciobanu

and Cristian Mesina, Ensemble of Classifiers for Length of Stay

Prediction in Colorectal Cancer, International Work-Conference on

Artificial Neural Networks (IWANN 2015), Advances in

Computational Intelligence, Lecture Notes in Computer Science,

Springer, Volume 9094, Palma de Mallorca, Spain, 10-12 June, pp.

444-457, 2015, http://link.springer.com/chapter/10.1007/978-3-

319-19258-1_37.

C1142 4 nu 5 1,33

7

Ruxandra Stoean, Florin Gorunescu, A Survey on Feature Ranking

by Means of Evolutionary Computation, Annals of the University of

Craiova, Mathematics and Computer Science Series, Vol. 40, No.

1, pp. 100-105, 2013,

http://inf.ucv.ro/~ami/index.php/ami/article/view/518.

Lista

20142 - 2 2

Perspectiva B. Producția științifică

Ruxandra Stoean

1/4


8

Ruxandra Stoean, Mike Preuss, Catalin Stoean, D. Dumitrescu,

Concerning the Potential of Evolutionary Support Vector Machines,

The IEEE Congress on Evolutionary Computation - CEC 2007 (ISI

proceedings), Singapore, pp. 1436 - 1443, 2007,

http://ieeexplore.ieee.org/document/4424640/.

C125 8 nu 4 4

9

Ruxandra Stoean, Mike Preuss, D. Dumitrescu, Catalin Stoean,

Evolutionary support vector regression machines, Proceedings of

the 8th International Symposium on Symbolic and Numeric

Algorithms for Scientific Computing (SYNASC 2006), art. no.

4090338 , pp. 330-335, 2006,


C634 2 nu 4 1

10

Ruxandra Stoean, Catalin Stoean, D. Dumitrescu, Investigating

landscape topology for subpopulation differentiation in genetic

chromodynamics, Proceedings of the 2008 10th International

Symposium on Symbolic and Numeric Algorithms for Scientific

Computing, (SYNASC 2008) , art. no. 5204869 , pp. 551-554, 2008,

http://ieeexplore.ieee.org/document/5204869/?reload=true&arnu

mber=5204869.

C634 2 nu 3 2

11

Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu,

Multimodal Optimization by means of a Topological Species

Conservation Algorithm, IEEE Transactions on Evolutionary

Computation, IEEE Intelligence Computational Society, Vol. 14,

Issue 6, pp. 842-864, ISSN 1089-778X, 2010,


J121 8 - 4 4

12

Catalin Stoean, Mike Preuss, Ruxandra Stoean, EA-based Parameter

Tuning of Multimodal Optimization Performance by Means of

Different Surrogate Models, The ACM Genetic and Evolutionary

Computation Conference, Workshop on Problem Understanding

and Real-World Optimisation, series GECCO '13 Companion -

volum distinct, pp. 1063-1070, 2013,

http://dl.acm.org/citation.cfm?id=2482684.

C111 8 da 3 4

13

Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu,

Disburdening the Species Conservation Evolutionary Algorithm of

Arguing with Radii, The ACM Genetic and Evolutionary

Computation Conference - GECCO 2007, London, UK, pp. 1420 -

1427, 2007, http://dl.acm.org/citation.cfm?id=1277220.

C111 8 nu 4 4

14

Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, EA-

Powered Basin Number Estimation by Means of Preservation and

Exploration, 10th International Conference on Parallel Problem

Solving from Nature – PPSN X, Springer Berlin / Heidelberg, vol.

5199, pp. 569-578, 2008, ISBN 978-3-540-87699-1,

http://link.springer.com/chapter/10.1007%2F978-3-540-87700-

4_57.

C292 8 nu 4 4

15

Mike Preuss, Catalin Stoean, Ruxandra Stoean, Niching

Foundations: Basin Identification on Fixed-Property Generated

Landscapes, The ACM Genetic and Evolutionary Computation

Conference (GECCO-2011), Dublin, Ireland, pp. 837-844, 2011,

http://dl.acm.org/citation.cfm?id=2001691&dl=ACM&coll=DL&CFID

=832353512&CFTOKEN=76666515.

C111 8 nu 3 8

2/4


16

Catalin Stoean, Ruxandra Stoean, Post-evolution of variable-length

class prototypes to unlock decision making within support vector

machines, Applied Soft Computing, Vol. 25, pp. 159–173, 2014,


J26 8 - 2 8,00

17

Catalin Stoean, Ruxandra Stoean, Monica Lupsor, Horia Stefanescu,

Radu Badea, Feature Selection for a Cooperative Coevolutionary

Classifier in Liver Fibrosis Diagnosis, Computers in Biology and

Medicine, Elsevier, Vol. 41, Issue 4, pp. 238-246, ISSN 0010-4825,

2011,

http://www.computersinbiologyandmedicine.com/article/S0010-

4825(11)00030-8/abstract.

J326 4 - 5 1,33

18

Catalin Stoean, Mike Preuss, Ruxandra Gorunescu, D. Dumitrescu,

Elitist Generational Genetic Chromodynamics - a New Radii-Based

Evolutionary Algorithm for Multimodal Optimization, The 2005 IEEE

Congress on Evolutionary Computation - CEC 2005, Edinburgh, UK,

September 2-5, 2005, pp. 1839 - 1846, ISBN 0-7803-9363-5,


C125 8 nu 4 4

19

Catalin Stoean, Ruxandra Stoean, Mike Preuss, D. Dumitrescu, A

Cooperative Evolutionary Algorithm for Classification, International

Journal of Computers, Communications & Control, Supplementary

Issue, pp. 417-422, ISSN 1841-9836, 2006,

http://apps.webofknowledge.com/full_record.do?product=WOS&s

earch_mode=GeneralSearch&qid=2&SID=V1qF3TxY5Gb25YcGa5J&

page=2&doc=20&cacheurlFromRightClick=no.

J736 2 - 4 1

20

Ruxandra Gorunescu, P.H. Millard, D. Dumitrescu, Evolutionary

Placement Decisions of a Multidisciplinary Panel using Genetic

Chromodynamics, Journal of Enterprise Information Management

(INSPEC indexed), Vol. 21, No. 1, pp. 93-104, ISSN 1741-0398,

2008,

http://www.emeraldinsight.com/doi/abs/10.1108/1741039081084

2282.

J891 2 - 3 2

21

Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Daniela Ciobanu,

Cristian Mesina, Corina Lavinia Gruia, SVM-Based Cancer Grading

from Histopathological Images using Morphological and Topological

Features of Glands and Nuclei, 9th International KES Conference on

Intelligent Interactive Multimedia: Systems and Services (KES

IIMSS), 55, Smart Innovation, Systems and Technologies, Puerto de

la Cruz, Tenerife, Spain, pp. 145-155, 15-17 June 2016,

http://link.springer.com/chapter/10.1007%2F978-3-319-39345-

2_13.

C1109 2 nu 6 0,5

22

Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Cristian Mesina,

Daniela Ciobanu, Corina Lavinia Gruia, Investigation on Parameter

Effect for Semi-Automatic Contour Detection in Histopathological

Image Processing, IEEE Post-Proceedings of the 17th International


Computing (SYNASC 2015), IEEE Computer Society, September 21

– 24, pp. 445-452, 2015, Timisoara, Romania,


C634 2 nu 6 0,5

3/4


23

Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Investigation of

Alternative Evolutionary Prototype Generation in Medical

Classification, IEEE Post-Proceedings of the 16th International


Computing (SYNASC 2014), September 22 – 25, 2014, Timisoara,

Romania, pp. 537-543, 2014,

http://ieeexplore.ieee.org/document/7034727/?reload=true&arnu

mber=7034727.

C634 2 nu 3 2

24

Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Cristian Mesina,

Corina Lavinia Gruia, Daniela Ciobanu, Evolutionary Search for An

Accurate Contour Segmentation in Histopathological Images, The

ACM Genetic and Evolutionary Computation Conference (GECCO

2015), GECCO Companion - volum distinct, Madrid, Spain, 11-15

July, pp. 1491-1492, 2015,


C111 8 da 6 1

25

Catalin Stoean, D. Dumitrescu, Mike Preuss, Ruxandra Stoean,

Cooperative evolution of rules for classification, Proceedings of the

8th International Symposium on Symbolic and Numeric Algorithms

for Scientific Computing (SYNASC 2006), art. no. 4090336, pp. 317-

322, 2007, http://ieeexplore.ieee.org/document/4090336/.

C634 2 nu 4 1

26

Ruxandra Stoean, Catalin Stoean, Mike Preuss, Elia El-Darzi, D.

Dumitrescu, Evolutionary support vector machines for diabetes

mellitus diagnosis, IEEE Intelligent Systems (IS) , art. no. 4155421,

pp. 182-187, 2006,


C282 2 nu 5 0,67

27

Catalin Stoean, Mike Preuss, Ruxandra Stoean, Evolutionary Species

Separation by a Clustering Mean for Multimodal Optimization,

Annals of the University of Craiova, Mathematics and Computer

Science Series, Vol. XXXVI, No. 2, pp. 53-62, ISSN 1223-6934, 2009,

inf.ucv.ro/~ami/index.php/ami/article/download/285/276.

Lista

20142 - 3 2

Total puncte categoria A

49

Total puncte categoria B

5,33

Total puncte minim B

54,33

Ruxandra Stoean

* Pozitia din listele de jurnale (J) sau conferinte (C) propuse de Comisia de Informatica CNATDCU din 2013

TOTAL

70,67

Minim necesar abilitare

56 (24 de tip minim A si 16 de tip minim B)

4/4

Numarul

publicatiei

care citeaza

Referinta bibliografica a publicatiei k care citeaza Tip * sk n ni

67 5 3 22,33

1

Javad Salimi Sartakhti, Mohammad Hossein Zangooei, Kourosh

Mozafari, Hepatitis disease diagnosis using a novel hybrid

method based on support vector machine and simulated

annealing (SVM-SA), Computer Methods and Programs in

Biomedicine, Vol. 108, Issue 2, ISSN 0169-2607, 2012.

J315 4

2

Bharti P, Mittal D, Ananthasivan R, Computer-Aided

Characterization and Diagnosis of Diffuse Liver Diseases Based

on Ultrasound Imaging: A Review, Ultrason Imaging, DOI:

10.1177/0161734616639875, 2016.

Serviciul

WEB2

3

H Luchian, ME Breaban, A Bautu, On Meta-heuristics in

Optimization and Data Analysis. Application to Geosciences,

Artificial Intelligent Approaches in Petroleum Geosciences,

Artificial Intelligent Approaches in Petroleum Geosciences, pp.

53-100, 2015.

BDI 1

4

M.R. Ibraheem, M. Elmogy, Automated Segmentation and

Classification of Hepatocellular Carcinoma Using Fuzzy C-

Means and SVM, Medical Imaging in Clinical Applications,

Volume 651, Studies in Computational Intelligence pp 193-

210, 2016.

Book/PhD 1

5Belciug, Gorunescu, Improving hospital bed occupancy and

resource utilization through queuing modelling and

evolutionary computation, Journal of Biomedical Informatics,

vol 53, pp. 261-269, ISSN 1532-0464, 2015.

J175 8

6

Jung-Kyu Choi, Keun-Hwan Jeon, Yonggwan Won, and Jung-Ja

Kim. 2015. Application of big data analysis with decision tree

for the foot disorder. Cluster Computing 18, 4 (December

2015), 1399-1404. DOI=http://dx.doi.org/10.1007/s10586-015-

0480-6

J305 4

7

Ahmet Kadir Arslan, Cemil Colak, Mehmet Ediz Sarihan,

Different medical data mining approaches based prediction of

ischemic stroke, Computer Methods and Programs in

Biomedicine, Volume 130, July 2016, Pages 87-92, ISSN 0169-

2607, http://dx.doi.org/10.1016/j.cmpb.2016.03.022.

J315 4

8MH Horng, CF Chao, HZ Chai, The construction of a support

vector machine using the shuffled frog-leaping algorithm,

Computer Science and Systems Engineering, 2014.

Book/PhD 1

Perspectiva C. Impactul rezultatelor (citări)

Ruxandra Stoean

Ruxandra Stoean, Catalin Stoean, Monica Lupsor, Horia Stefanescu, Radu Badea,

Evolutionary-Driven Support Vector Machines for Determining the Degree of Liver Fibrosis in

Chronic Hepatitis C, Artificial Intelligence in Medicine, Elsevier, Vol. 51, Issue 1, pp. 53-65,

ISSN 0933-3657, 2011, http://www.ncbi.nlm.nih.gov/pubmed/20675106.


8

Total puncte minim categoria B

18,67

k

ks k

k

i

sn

1

1/23

Numarul

publicatiei

care citeaza


k

ks k

k

i

sn

1

9CF Chao, MH Horng, The Construction of Support Vector

Machine Classifier Using the Firefly Algorithm,

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,

Volume 2015, http://dx.doi.org/10.1155/2015/212719, 2015.

Lista 2014 4

10

Daniel Gartner, Optimizing Hospital-wide Patient Scheduling,

Lecture Notes in Economics and Mathematical Systems,

Volume 674, 2014.

BDI 1

11

Cheng-Min Chao, Ya-Wen Yu, Bor-Wen Cheng, Yao-Lung Kuo,

Construction the Model on the Breast Cancer Survival Analysis

Use Support Vector Machine, Logistic Regression and Decision

Tree, 38(10):106. doi: 10.1007/s10916-014-0106-1, 2014.

J450 4

12

F. Gorunescu, S. Belciug, Evolutionary Strategy to Develop

Learning-based Decision Systems. Application to Breast Cancer

and Liver Fibrosis Stadialization, Journal of Biomedical

Informatics, http://dx.doi.org/10.1016/j.jbi.2014.02.001, 2014.

J175 8

13

Faezeh Hosseinzadeh, Amir Hossein KayvanJoo, Mansuor

Ebrahimi, Prediction of lung tumor types based on protein

attributes by machine learning algorithms, Springerplus, 2:

238, DOI: 10.1186/2193-1801-2-238, 2013.

BDI 1

14

Ahmed M. Hashem, M. Emad M. Rasmy, Khaled M. Wahba,

Olfat G. Shaker, Single stage and multistage classification

models for the prediction of liver fibrosis degree in patients

with chronic hepatitis C infection, Computer Methods and

Programs in Biomedicine, Volume 105, Issue 3, March 2012,

Pages 194-209, ISSN 0169-2607, 10.1016/j.cmpb.2011.10.005.

J315 4

15

Mandal, Indrajit; Sairam, N., Accurate Prediction of Coronary

Artery Disease Using Reliable Diagnosis System, JOURNAL OF

MEDICAL SYSTEMS, 36 (5):3353-3373; 10.1007/s10916-012-

9828-0 OCT 2012.

J450 4

16

Muthanantha Murugavel, A.S., Ramakrishnan, S., Balasamy, K.,

Gopalakrishnan, T., Lyapunov features based EEG signal

classification by multi-class SVM, Proceedings of the 2011

World Congress on Information and Communication

Technologies, WICT 2011 , art. no. 6141243 , pp. 197-201,

2011.

BDI 1

17Florin Gorunescu, Data Mining: Concepts, Models and

Techniques, Springer Verlag, 2011.Book/PhD 1

18

JS Sartakhti, MH Zangooei, K Mozafari, Hepatitis disease

diagnosis using a novel hybrid method based on support

vector machine and simulated annealing (SVM-SA), Computer

Methods and Programs in Biomedicine

Vol. 108, Issue 2, pp. 570–579, 2012.

J315 4

19

A Mozaffari, S Behzadipour, M Kohani, Identifying the tool-

tissue force in robotic laparoscopic surgery using neuro-

evolutionary fuzzy systems and a synchronous self-learning

hyper level supervisor, Applied Soft Computing, Vol. 14, Issue

PART A, pp. 12 - 30, 2014.

J26 8

20

S Belciug, F Gorunescu, A hybrid neural network/genetic

algorithm applied to breast cancer detection and recurrence,

Expert Systems, 2012.

J644 2

2/23

Numarul

publicatiei

care citeaza


k

ks k

k

i

sn

1

77 2 1 77

1N Cuong, W Yong, N Ha Nam, Random forest classifier

combined with feature selection for breast cancer diagnosis

and prognostic, Journal of Biomedical Science and

Engineering, Vol.6 No.5, pp. 551-560, May 2013.

BDI 1

2A. F. Seddik and D. M. Shawky, "Logistic regression model for

breast cancer automatic diagnosis," SAI Intelligent Systems

Conference (IntelliSys), IEEE, 2015, London, 2015, pp. 150-154.

doi: 10.1109/IntelliSys.2015.7361138

BDI 1

3

A. O. Ibrahim, S. M. Shamsuddin, A. y. Saleh, A. Abdelmaboud

and A. Ali, "Intelligent multi-objective classifier for breast

cancer diagnosis based on multilayer perceptron neural

network and Differential Evolution," Computing, Control,

Networking, Electronics and Embedded Systems Engineering

(ICCNEEE), 2015 International Conference on, Khartoum,

2015, pp. 422-427.

BDI 1

4

R. Sali, H. Shavandi, and M. Sadeghi, “A clinical decision

support system based on support vector machine and binary

particle swarm optimisation for cardiovascular disease

diagnosis,” International Journal of Data Mining and

Bioinformatics, vol. 15, no. 4,

http://dx.doi.org/10.1504/IJDMB.2016.078150, 2016.

Serviciul

WEB2

5F. Gorunescu, Intelligent decision systems in Medicine ??? A

short survey on medical diagnosis and patient management, E-

Health and Bioengineering Conference (EHB), pp. 1-9, 2015.

BDI 1

6

Fadzil Ahmad, Nor Ashidi Mat Isa, Zakaria Hussain,

Muhammad Khusairi Osman, and Siti Noraini Sulaiman. 2015.

A GA-based feature selection and parameter optimization of

an ANN in diagnosing breast cancer. Pattern Anal. Appl. 18, 4

(November 2015), 861-870.

J502 4

7

Akin Ozcift and Arif Gulten. 2012. A Robust Multi-Class

Feature Selection Strategy Based on Rotation Forest Ensemble

Algorithm for Diagnosis of Erythemato-Squamous Diseases. J.

Med. Syst. 36, 2 (April 2012), 941-949.

J976 2

8X Wanga, W Tanb, H Wuc, An Innovative SVM for Wheat Seed

Quality Estimation, Journal of Information & Computational

Science 12:1, pp. 223–233, January 2015.

J898 2

9

S Ali, A Majid, Can-Evo-Ens: Classifier stacking based

evolutionary ensemble system for prediction of human breast

cancer using amino acid sequences, Journal of Biomedical

Informatics, Volume 54, pp. 256–269, April 2015.

J175 8

R. Stoean, C. Stoean, Modeling medical decision making by support vector machines,

explaining by rules of evolutionary algorithms with feature selection, Expert Systems with

Applications, Volume 40, Issue 7, Pages 2677–2686, June 2013,

http://www.sciencedirect.com/science/article/pii/S0957417412012171.


40


52

3/23

Numarul

publicatiei

care citeaza


k

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k

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1

10

Archana Purwar, Sandeep Kumar Singh, Hybrid prediction

model with missing value imputation for medical data, Expert

Systems with Applications, Volume 42, Issue 13, 1 August

2015, pp 5621–5631.

J85 8

11Daniel Gartner, Optimizing Hospital-wide Patient Scheduling,

Lecture Notes in Economics and Mathematical Systems,

Volume 674, 2014.

Book/PhD 1

12

SI Omurca, E Ekinci, An alternative evaluation of post

traumatic stress disorder with machine learning methods,

2015 International Symposium on Innovations in Intelligent

SysTems and Applications (INISTA), pp. 1-7, 2-4 Sept. 2015.

C1108 2

13

Mohammad M. Ghiasia, Alireza Bahadorib, Sohrab

Zendehboudic, Ioannis Chatzisd, Rigorous models to optimise

stripping gas rate in natural gas dehydration units, Fuel,

Elsevier, 140, pp. 421–428, 2015.

Serviciul

WEB4

14

Lenka Skanderova, Ivan Zelinka, Petr Šaloun, Chaos Powered

Selected Evolutionary Algorithms, Nostradamus 2013:

Prediction, Modeling and Analysis of Complex Systems

Advances in Intelligent Systems and Computing Springer, Vol.

210, pp 111-124, 2013.

BDI 1

15

Majid A., Ali S., HBC-Evo: predicting human breast cancer by

exploiting amino acid sequence-based feature spaces and

evolutionary ensemble system, Amino Acids, pp 217-221,

2014.

BDI 2

16

Eneko Osaba, Roberto Carballedo, Fernando Diaz, Enrique

Onieva, Asier Perallos, A Proposal of Good Practice in the

Formulation and Comparison of Meta-heuristics for Solving

Routing Problems, International Joint Conference SOCO’14-

CISIS’14-ICEUTE’14

Advances in Intelligent Systems and Computing, Springer, Vol

299, pp 31-40, 2014.

BDI 1

17

Mohammad M. Ghiasi, Amir H. Mohammadi, Rigorous

modeling of CO2 equilibrium absorption in MEA, DEA, and TEA

aqueous solutions, Journal of Natural Gas Science and

Engineering, 18, pp. 39–46, 2014.

Serviciul

WEB2

18

Manjeevan Seera, Chee Peng Lim, Shing Chiang Tan, and Chu

Kiong Loo. 2015. A hybrid FAM---CART model and its

application to medical data classification. Neural Comput.

Appl. 26, 8 (November 2015), 1799-1811.

DOI=http://dx.doi.org/10.1007/s00521-015-1852-9

J976 2

19

Lenka Skanderova, Ivan Zelinka, Petr Saloun, Complex

Network Construction Based on SOMA: Vertices In-Degree

Reliance on Fitness Value Evolution, ISCS 2013:

Interdisciplinary Symposium on Complex Systems Emergence,

Complexity and Computation, 8, 2014, Springer Berlin

Heidelberg, pp. 291-297.

BDI 1

20





J175 8

21

Shuai Hou, Fuan Hua, Wu Lv, Zhaodong Wang, Yujia Liu,

Guodong Wang, Hybrid Modeling of Flotation Height in Air

Flotation Oven Based on Selective Bagging Ensemble Method,

Mathematical Problems in Engineering, Vol. 2013, DOI:

http://dx.doi.org/10.1155/2013/281523, ISSN 1024-123X,

2013.

BDI 4

4/23

Numarul

publicatiei

care citeaza


k

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1

22

S. Ali, A. Majid, A. Khan, IDM-PhyChm-Ens: Intelligent decision-

making ensemble methodology for classification of human

breast cancer using physicochemical properties of amino

acids, Amino Acids, pp. 1-17, ISSN 0939-4451, 2014.

BDI 2

23

M Seera, CP Lim, A hybrid intelligent system for medical data

classification, Expert Systems with Applications, Vol. 41, Issue

5, pp. 2239 - 2249, 2014.

J85 8

24

Nguyen, D. , Bernstein, L. and Goel, M. (2012) Asian-American

elders’ health and physician use: An examination of social

determinants and lifespan influences. Health, 4, 1106-1115.

doi: 10.4236/health.2012.411168.

BDI 1

25

T Landesberger, S Bremm, M Kirschner, Stefan Wesarg, Arjan

Kuijper, Visual Analytics for model-based medical image

segmentation: Opportunities and challenges, Expert Systems

with Applications, vol. 40, issue 12, pp. 4934–4943, 2013.

J85 8

216 4 2 108

1

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WEB2

5

Florin Gorunescu, Smaranda Belciug, Boosting

backpropagation algorithm by stimulus-sampling: Application

in computer-aided medical diagnosis, Journal of Biomedical

Informatics, Volume 63, October 2016, Pages 74-81, ISSN

1532-0464, http://dx.doi.org/10.1016/j.jbi.2016.08.004

J175 8

6 Soliman, Omar S; Elhamd, Eman Abo, A Chaotic Levy Flights

Bat Algorithm for Diagnosing Diabetes Mellitus, International

Journal of Computer Applications, 111.1 pp.36-42, 2015.

Serviciul

WEB2

7

S Belciug, MS Serbanescu, Regression-Based Approach For

Feature Selection In Classification Issues. Application To

Breast Cancer Detection And Recurrence, Volume 67, Issue

1,pp. 13-18, 2015.

BDI 1


Catalin Stoean, Ruxandra Stoean, Monica Lupsor, Horia Stefanescu, Radu Badea, Feature

Selection for a Cooperative Coevolutionary Classifier in Liver Fibrosis Diagnosis, Computers in

Biology and Medicine, Elsevier, Vol. 41, Issue 4, pp. 238-246, ISSN 0010-4825, 2011,

http://www.sciencedirect.com/science/article/pii/S0010482511000308.


8,00

8,00

14/23

Numarul

publicatiei

care citeaza


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k

i

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1

8





J175 8

9

Huang, Min; Chen, Jie; Sun, Bo, A new collaborator selection

method of cooperative co-evolutionary genetic algorithm and

its application, International Conference on Multisensor

Fusion and Information Integration for Intelligent Systems

(MFI), IEEE, Beijing, 2014.

BDI 1

10S Belciug, F Gorunescu, A hybrid neural network/genetic


Expert Systems, Vol. 30, Issue 3, pp. 243–254, 2013.

J644 2

11E Parras-Gutierrez, VM Rivas, M Garcia-Arenas, Short, medium

and long term forecasting of time series using the L-Co-R

algorithm, Neurocomputing, Elsevier 2013.

J234 8

12

Dr. S.Appavu Alias Balamurugan,S.Sasikala, Dr.S.Geetha, A

Survey on Predictive Data mining Approaches for Medical

Informatics, International Journal of Scientific & Engineering

Research Volume 3, Issue 9, September-2012.

BDI 1

1 2 1 1,00

1

Florin Gorunescu, Intelligent decision systems in Medicine ???

A short survey on medical diagnosis and patient management,

E-Health and Bioengineering Conference (EHB), pp. 1 - 9, Iasi,

Romania, 2015.

BDI 1

5 5 3 1,67

1

Gürbüz, E., Kiliç, E., Uyarlanabilir DVM yöntemi kullanilarak

şeker hastaliginin teşhis edilmesi | [Diagnosis of diabetes by

using adaptive SVM], 2011 IEEE 19th Signal Processing and

Communications Applications Conference, SIU 2011 , art. no.

5929584 , pp. 46-49, 2011.

BDI 1



Book/PhD 1

3

E Gürbüz, E Kiliç, A new adaptive support vector machine for

diagnosis of diseases, Expert Systems, Wiley, DOI:

10.1111/exsy.12051, 2013.

J644 2


Stoean, R., Stoean, C., Preuss, M., El-Darzi, E., Dumitrescu, D., Evolutionary support vector

machines for diabetes mellitus diagnosis, IEEE Intelligent Systems - IS , art. no. 4155421, pp.

182-187, 2006, http://ieeexplore.ieee.org/document/4155421/.

Catalin Stoean, Ruxandra Stoean, Post-evolution of variable-length class prototypes to unlock

decision making within support vector machines, Applied Soft Computing, Vol. 25, pp.

159–173, 2014, http://www.sciencedirect.com/science/article/pii/S1568494614004694.


0


0

0


0

15/23

Numarul

publicatiei

care citeaza


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k

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1

4

Vanessa Terezinha Ales, Algoritmo Sequential Minimal

Optimisation para Resolucao do problema de support vector

machine: uma tecnica para reconhecimento de padroes (in

spaniola), PhD Dissertation, Universidade Federal do Paraná,

2009.

Book/PhD 1

15 2 1 15,00

1

Meryem Berghida, Abdelmadjid Boukra, Resolution of a

Vehicle Routing Problem with Simultaneous Pickup and

Delivery: A Cooperative Approach, International Journal of

Applied Metaheuristic Computing (IJAMC) 6(3),

10.4018/ijamc.2015070103.

BDI 1

2

Gloria Cerasela Crişan, Camelia-M. Pintea , Petrică Pop, Oliviu

Matei, An Analysis of the Hardness of Novel TSP Iberian

Instances, 11th International Conference, HAIS 2016, Seville,

Spain, April 18-20, 2016, Hybrid Artificial Intelligent Systems

Volume 9648 of the series Lecture Notes in Computer Science

pp 353-364, 2016.

C472 2

3

Gloria Cerasela Crişan, Camelia-M. Pintea, Vasile Palade,

Emergency management using geographic information

systems: application to the first Romanian traveling salesman

problem instance, Knowledge and Information Systems, pp 1-

21, 2016, 10.1007/s10115-016-0938-8.

J213 8

4

Smaranda Belciuge, Florin Gorunescu, A hybrid genetic

algorithm-queuing multi-compartment model for optimizing

inpatient bed occupancy and associated costs, Artificial

Intelligence in Medicine , Volume 68 , 59 - 69, 2016.

J293 4

19 4 2 9,5

1

Yin, X., Yin, G., Hu, X., Zhao, X., Positioning accuracy of robot

vision system based on support vector machine regression,

Jixie Gongcheng Xuebao/Journal of Mechanical Engineering 47

(1) , pp. 48-54, 2011.

J845 2

2




Volume 98, Number 1/2010, pp. 87-106, 2010.

J359 4

Stoean, R., Preuss, M., Dumitrescu, D., Stoean, C., Evolutionary support vector regression

machines, Proceedings of the 8th International Symposium on Symbolic and Numeric

Algorithms for Scientific Computing, SYNASC 2006 , art. no. 4090338 , pp. 330-335, 2006,



4


6

Catalin Stoean, Ruxandra Stoean, Support Vector Machines and Evolutionary Algorithms for

Classification - Single or Together?, Intelligent Systems Reference Library, Springer, Vol. 69,

122 p., ISBN 978-3-319-06941-8, 2014, http://www.springer.com/br/book/9783319069401.


8


12

16/23

Numarul

publicatiei

care citeaza


k

ks k

k

i

sn

1

3

LIU Jian-hua, MA Wen-bin, SVM and wavelet analysis method

for hydraulic pump fault of rock drilling, International

Conference on Automation, Mechanical Control and

Computational Engineering (AMCCE 2015), pp. 1855-1859,

2015.

BDI 1

4

Jianzhou Wang, Qingping Zhou, Haiyan Jiang, Ru Hou, Short-

Term Wind Speed Forecasting Using Support Vector

Regression Optimized by Cuckoo Optimization Algorithm,

Mathematical Problems in Engineering, Volume 2015 (2015),

Article ID 619178, http://dx.doi.org/10.1155/2015/619178

BDI 1

3



2012, pp. 9246 - 9254.

J85 8

4

Kramer, O., Hein, T., Stochastic feature selection in support

vector machine based instrument recognition, German

Conference on Artificial Intelligence KI, Lecture Notes in

Computer Science (including subseries Lecture Notes in


5803 LNAI, pp. 727-734, 2009.

C235 2

5

Giovanni Montana, Francesco Parrella, Data Mining for

Algorithmic Asset Management, Book chapter in Data Mining

for Business Applications, Part II, Springer US, pp. 283-295,

2009.

Book/PhD 1

20 3 1 20,00

1

M. W. Pereira, G. S. Neto and M. Roisenberg, "A topological

niching covariance matrix adaptation for multimodal

optimization," 2014 IEEE Congress on Evolutionary

Computation (CEC), Beijing, 2014, pp. 2562-2569.

C125 8

2

Evgenii Sopov, A Self-configuring Multi-strategy Multimodal

Genetic Algorithm, Advances in Nature and Biologically

Inspired Computing

Volume 419 of the series Advances in Intelligent Systems and

Computing pp 15-26, 2016.

BDI 1

3

MA Muñoz, Y Sun, M Kirley, SK Halgamuge, Algorithm

selection for black-box continuous optimization problems: A

survey on methods and challenges, Information Sciences,

Volume 317, pp. 224–245, 2015.

J157 8

4

EA Sopov, Multiple optima identification using multi-strategy

multimodal genetic algorithm, Journal of Siberian Federal

University. Mathematics & Physics 2016, 9(2), pp. 246–257,

2016.

BDI 1

5Oliver Kramer, Machine Learning for Evolution Strategies, 20,

ISBN 978-3-319-33381-6, 2016.Book/PhD 1

Mike Preuss, Catalin Stoean, Ruxandra Stoean, Niching Foundations: Basin Identification on

Fixed-Property Generated Landscapes, The ACM Genetic and Evolutionary Computation

Conference (GECCO-2011), Dublin, Ireland, pp. 837-844, 2011,

http://dl.acm.org/citation.cfm?id=2001691&dl=ACM&coll=DL&CFID=661851677&CFTOKEN=2

2485374.


16


16

17/23

Numarul

publicatiei

care citeaza


k

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k

i

sn

1

6

V. Stanovov, E. Sopov and E. Semenkin, "Multi-Strategy

Multimodal Genetic Algorithm for Designing Fuzzy Rule Based

Classifiers," Computational Intelligence, 2015 IEEE Symposium

Series on, Cape Town, 2015, pp. 167-173.

BDI 1

4 4 2 2

1D. Morariu, R. Cretulescu, L. Vintan, Improving a SVM Meta-

classifier for Text Documents by using Naive Bayes,

International Journal Of Computers Communications &

Control, Vol. 5, No. 3, pp. 351-361, 2010.

J736 2

2

L. State, I. Paraschiv-Muntean, A New Linear Classifier Based

on Combining Supervised and Unsupervised Techniques, Int. J.

of Computers, Communications & Control, Vol. 6, No. 1, pp.

175-186, 2011

J736 2

2 4 2 1





Book/PhD 1

1 4 2 0,5



Book/PhD 1


0

Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Evolutionary Multi-class

Support Vector Machines for Classification, International Journal of Computers,

Communications & Control, Supplementary Issue, pp. 423 – 428, ISSN 1841-9836, 2006,

http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSear

ch&qid=2&SID=V1qF3TxY5Gb25YcGa5J&page=3&doc=21.


0


0


0


0


Stoean, C., Dumitrescu, D., Preuss, M., Stoean, R., Cooperative evolution of rules for

classification, Proceedings of the 8th International Symposium on Symbolic and Numeric

Algorithms for Scientific Computing, SYNASC 2006 , art. no. 4090336, pp. 317-322, 2007,


Catalin Stoean, Ruxandra Stoean, Mike Preuss, D. Dumitrescu, A Cooperative Evolutionary

Algorithm for Classification, International Journal of Computers, Communications & Control,

Supplementary Issue,2006, pp. 417-422, ISSN 1841-9836,

http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSear

ch&qid=2&SID=V1qF3TxY5Gb25YcGa5J&page=2&doc=20&cacheurlFromRightClick=no.

0

18/23

Numarul

publicatiei

care citeaza


k

ks k

k

i

sn

1

12 4 2 6

1

E Gajda-Zagórska, Multiobjective evolutionary strategy for

finding neighbourhoods of pareto-optimal solutions,

Applications of Evolutionary Computation, Lecture Notes in

Computer Science, Springer, Volume 7835, pp 112-121, 2013.

LNCS 2

3

B Lacroix, D Molina, F Herrera, Region-based Memetic

Algorithm with Archive for multimodal optimisation,

Information Sciences, Information Sciences, Volumes

367–368, Elsevier, pp. 719–746, 2016.

J157 8

4Ewa Gajda-Zagórska, Recognizing Sets in Evolutionary

Multiobjective Optimization, Journal of Telecommunications &

Information Technology, Vol. 2012 Issue 1, p74-82, 2012.

BDI 1

2 Ewa Gajda-Zagórska, Recognizing Sets in Evolutionary



BDI 1

17 5 3 5,67



2




Volume 98, Number 1/2010, pp. 87-106, 2010.

J359 4

3


Expert Systems with Applications, Vol. 39, Issue 10, pp. 9246 -

9254, 2012.

J85 8

4

AM Hashem, MEM Rasmy, KM Wahba, Olfat G. Shaker, Single

stage and multistage classification models for the prediction

of liver fibrosis degree in patients with chronic hepatitis C

infection, Computer Methods and Programs in Biomedicine,

Vol. 105, Issue 3, pp. 194–209, 2012.

J315 4

10 4 2 5

5,33


4


4


2,67


Catalin Stoean, Mike Preuss, Ruxandra Stoean, D. Dumitrescu, EA-Powered Basin Number

Estimation by Means of Preservation and Exploration, 10th International Conference on

Parallel Problem Solving from Nature – PPSN X, Lecture Notes in Computer Science, Springer

Berlin / Heidelberg, vol. 5199, pp. 569-578, 2008, ISBN 978-3-540-87699-1,

http://link.springer.com/chapter/10.1007%2F978-3-540-87700-4_57.

Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D Dumitrescu, An evolutionary

approximation for the coefficients of decision functions within a support vector machine

learning strategy, Foundations of Computational, Intelligence Volume 1, pp. 83-114, 2009,


C Stoean, D Dumitrescu, M Preuss, R Stoean, Cooperative Coevolution for Classification, Bio-

Inspired Computing: Theory and Applications, pp. 289-298, 2006.

19/23

Numarul

publicatiei

care citeaza


k

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k

i

sn

1

1

Z Wang, M Li, A Coevolution Approach for Learning

Multimodal Concepts, Third International Conference on

Natural Computation, 2007. ICNC 2007, Vol. 3, pp. 389 - 393,

2007.

C519 2

2

BY Hiew, SC Tan, WS Lim, Intra-specific competitive co-

evolutionary artificial neural network for data classification,

Neurocomputing, Elsevier, Volume 185, 12 April 2016, pp.

220–230, 2016

J234 8

20 2 1 20

1

X Guo, Z Zhu, J Shi, Integration of semi-fuzzy SVDD and CC-

Rule method for supplier selection, Expert Systems with

Applications, Vol. 41, Issue 4, Part 2, pp. 2083–2097, March

2014.

J85 8

2





J175 8

3

Camelia-M. Pintea, Petrica C. Pop, Sensitive Ants for Denial

Jamming Attack on Wireless Sensor Network, CISIS 13,

Advances in Intelligent Systems and Computing Vol. 239, pp

409-418, 2014.

C79 4

3 3 1 3

1Ewa Gajda-Zagórska, Recognizing Sets in Evolutionary



BDI 1

2

E Gajda-Zagórska, Multiobjective evolutionary strategy for

finding neighbourhoods of pareto-optimal solutions,

Applications of Evolutionary Computation, Lecture Notes in

Computer Science, Springer, Volume 7835, pp 112-121, 2013.

LNCS 2

4 4 2 2

20


0


0


0

C Stoean, R Stoean, M Preuss, Approximating the number of attraction basins of a function

by means of clustering and evolutionary algorithms, 8th Int. Conf. on AIDC. Res. No. in AIDC,

pp. 171-180, 2008.


4


4


16


C Stoean, R Stoean, Evolution of cooperating classification rules with an archiving strategy to

underpin collaboration, Intelligent Systems and Technologies, Springer chapter, pp. 47-65,

2009, http://link.springer.com/chapter/10.1007%2F978-3-642-01885-5_3#page-1.

Catalin Stoean, Ruxandra Stoean, Mike Preuss, D. Dumitrescu, Coevolution for Classification,

Technical Report Nr. CI-239/08, Collaborative Research Center on Computational

Intelligence, University of Dortmund, 2008.

20/23

Numarul

publicatiei

care citeaza


k

ks k

k

i

sn

1

1S Wang, Z Zheng, Z Wu, Q Sun, H Zou, F Yang, Context-aware

mobile service adaptation via a Co-evolution eXtended

Classifier System in mobile network environments, Mobile

Information Systems, DOI 10.3233/MIS-130178, 2013.

J482 4

8 2 1 8

1

MS Habib, Improving Scalability of Support Vector Machines

for Biomedical Named Entity Recognition, PhD thesis,

University of Colorado, 2008.

Book/PhD 1

2 Enhong Chen, Feng Wang, Dynamic Clustering Using Multi-

objective Evolutionary Algorithm, Computational Intelligence

and Security, pp. 73-80, LNCS, 2005.

LNCS 2

3

H. Ye and Z. Ni, "An Evolutionary Multi-centers Based

Dynamical Clustering Algorithm," Third International

Conference on Natural Computation (ICNC 2007), Haikou,

2007, pp. 586-590.

doi: 10.1109/ICNC.2007.199

C948 2

4

Habiboulaye Amadou Boubacar, Classification Dynamique de

données non-stationnaires :

Apprentissage et Suivi de Classes évolutives, PhD thesis,

Automatique / Robotique. Université des Sciences et

Technologie de Lille - Lille I, 2006.

Book/PhD 1

5

Ji Dan, Qiu Jianlin, Chen Jianping, Chen Li, He Peng, An

improved decision tree algorithm and its application in maize

seed breeding, 2010 Sixth International Conference on Natural

Computation (ICNC), vol.1, pp.117-121, 2010.

C 2

1 3 1 1




BDI 1

8 3 1 8


2

Stoean C, Stoean R, El-Darzi E. Breast cancer diagnosis by means of cooperative coevolution.

In: Proc. 3rd ACM international conference on intelligent computing and information systems

– ICICIS 2007. Cairo: Police Press; 2007. p. 493–7.


Ruxandra Gorunescu, D. Dumitrescu, Evolutionary clustering using an incremental technique,

Studia Univ. Babes - Bolyai, Informatica, Volume XL VIII, Number 2, pp. 25 - 33, 2003,

http://www.cs.ubbcluj.ro/~studia-i/2003-2/4-Dumitrescu.pdf.

Catalin Stoean, Ruxandra Stoean, Adrian Sandita, Investigation of Alternative Evolutionary

PrototypeGeneration in Medical Classification, IEEE Post-Proceedings of the 16th

International Symposium on Symbolic and Numeric Algorithms for Scientific Computing

(SYNASC 2014), September 22 – 25, 2014, Timisoara, Romania, pp. 537-543, 2014,

http://ieeexplore.ieee.org/document/7034727/?reload=true&arnumber=7034727.



0


0

0


0

21/23

Numarul

publicatiei

care citeaza


k

ks k

k

i

sn

1

1





J175 8

1 4 2 0,5

1

S. A. Davidsen and M. Padmavathamma, "Multi-modal

evolutionary ensemble classification in medical diagnosis

problems," Advances in Computing, Communications and

Informatics (ICACCI), 2015 International Conference on, Kochi,

2015, pp. 1366-1370.

BDI 1

2

Shankaracharya1, Odedra D, Samanta S, Vidyarthi AS.,

Computational intelligence in early diabetes diagnosis: a

review, Rev Diabet Stud. 2010 Winter;7(4), pp. 252-62, 2011.

doi: 10.1900/RDS.2010.7.252

BDI 1

2 4 2 1

1J Silc, K Taskova, P Korosec, Data Mining-Assisted Parameter

Tuning of a Search Algorithm, Informatica, 39, pp.169-176,

2015

J681 2

1 5 3 0,333333333

Catalin Stoean, Ruxandra Stoean, Mike Preuss, D. Dumitrescu, Diabetes Diagnosis through

the Means of a Multimodal Evolutionary Algorithm, Proceedings of the First East European

Conference on Health Care Modelling and Computation - HCMC 2005, Craiova, Romania,

August 31st - September 2nd 2005, Vol. 2, pp. 277-289, ISBN 973-7757-67-X, https://ls11-

www.cs.tu-dortmund.de/_media/staff/preuss/sspd05.pdf.


0


0

8


8

Ruxandra Stoean, Thomas Bartz-Beielstein, Mike Preuss, Catalin Stoean, A Support Vector

Machine-Inspired Evolutionary Approach for Parameter Setting in Metaheuristics, CIOP

Reports. Technical reports from the Computational Intelligence, Optimization, and Data

mining research group, Thomas Bartz-Beielstein and Wolfgang Konen (Eds.), Cologne

University of Applied Sciences, TR01/09, 2009,

http://www.academia.edu/11824166/A_Support_Vector_Machine-

Inspired_Evolutionary_Approach_for_Parameter_Setting_in_Metaheuristics.


0


0

Ruxandra Stoean, Catalin Stoean, Adrian Sandita, Daniela Ciobanu and Cristian Mesina,

Ensemble of Classifiers for Length of Stay Prediction in Colorectal Cancer, International Work-

Conference on Artificial Neural Networks (IWANN 2015), Advances in Computational

Intelligence, Lecture Notes in Computer Science, Springer, Volume 9094, Palma de Mallorca,

Spain, 10-12 June, pp. 444-457, 2015, http://link.springer.com/chapter/10.1007/978-3-319-

19258-1_37.


0


0

22/23

Numarul

publicatiei

care citeaza


k

ks k

k

i

sn

1




BDI 1

2 5 3 0,666666667

1Bharti P, Mittal D, Ananthasivan R, Computer-Aided



10.1177/0161734616639875, 2016.

Serviciul

WEB2

3 2 1 3

1

E. Pashaei, M. Ozen and N. Aydin, "A novel gene selection

algorithm for cancer identification based on random forest

and particle swarm optimization," Computational Intelligence

in Bioinformatics and Computational Biology (CIBCB), 2015

IEEE Conference on, Niagara Falls, ON, 2015, pp. 1-6.

C650 2

2

B. Amarnath, S. Appavu alias Balamurugan, Metaheuristic

Approach for Efficient Feature Selection: A Data Classification

Perspective, Indian Journal of Science & Technology, 9(4),

10.17485/ijst/2016/v9i4/87039, 2016.

BDI 1

A

274,67

Ruxandra Stoean


0


0

Ruxandra Stoean, Catalin Stoean, Monica Lupsor, Horia Stefanescu, Radu Badea,

Evolutionary Conditional Rules versus Support Vector Machines Weighted Formulas for Liver

Fibrosis Degree Prediction, Annals of the University of Craiova, Mathematics and Computer

Science Series, Vol. 37, No. 1, pp. 43-54, 2010,

http://inf.ucv.ro/~ami/index.php/ami/article/viewFile/307/294.


0


Minim necesar abilitare

120 (40 de tip minim B)

* Pozitia din listele de jurnale (J) sau conferinte (C) propuse de Comisia de Informatica CNATDCU din 2013. Cand este de tip C sau D,

am completat LNCS, respectiv BDI/Book/PhD. Cand revista nu este luata din lista din 2013, am completat Lista 2014.

B

63,33

Citări în lucrări de tipTotal

436,50

Total citări în lucrări de

tip minim B

338

Ruxandra Stoean, Florin Gorunescu, A Survey on Feature Ranking by Means of Evolutionary

Computation, Annals of the University of Craiova, Mathematics and Computer Science Series,

Vol. 40, No. 1, pp. 100-105, 2013, http://inf.ucv.ro/~ami/index.php/ami/article/view/518.

0

23/23

Numarul publicatiei Referinta bibliograficaNumar

autoriPuncte

Puncte

ponderat

1

Catalin Stoean, Ruxandra Stoean, Support Vector Machines and Evolutionary

Algorithms for Classification - Single or Together?, Intelligent Systems Reference

Library, Springer, Vol. 69, 122 p., ISBN 978-3-319-06941-8, 2014,

http://www.springer.com/br/book/9783319069401. Recenzii in Memoirs of the

Scientific Sections of the Romanian Academy, Tome XXXVIII, 2015, pp. 132-133,

Acad. Prof. H.N. Teodorescu, http://mss.academiaromana-

is.ro/mem_sc_st_2015/7_Book%20Reviews.pdf si Epaminondas Kapetanios,

Computing Reviews, November, 2014,

http://www.springer.com/br/book/9783319069401#reviews

2 8 8

2

Ruxandra Stoean, Catalin Stoean, Evolutie si inteligenta artificiala. Paradigme

moderne si aplicatii, Editura Albastra - Grupul MicroInformatica, 166 p., ISBN: 978-

973-650-277-4, 2010,

http://www.gmi.ro/librarie/catalog/product_info.php?products_id=225&PHPSESSID

=7e4460cc6728f6297c1efc81fc915490.

2 2 2

3

Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu, An

Evolutionary Approximation for the Coefficients of Decision Functions within a

Support Vector Machine Learning Strategy, Foundations on Computational

Intelligence, Aboul Ella Hassanien and Ajith Abraham (Eds.), Springer, Vol. 1, pp. 83-

114, ISSN 1860-949X, 2009, http://link.springer.com/chapter/10.1007%2F978-3-642-

01082-8_4.

5 4 1,33

4

Catalin Stoean, Ruxandra Stoean, Evolution of Cooperating Classification Rules with

an Archiving Strategy to Underpin Collaboration, Intelligent Systems and

Technologies - Methods and Applications, Springer, H. N. Teodorescu, Junzo Watada

and L. Jain (Eds.), pp. 47-65, ISSN 1860-949X, 2009,


2 4 4

5

Ruxandra Stoean, Support Vector Machines. An Evolutionary Resembling Approach,

Research Center for Artificial Intelligence, Computer Science Series, Universitaria

Publishing House, Craiova, 132 pages, ISBN: 978-606-510-161-6, 2008,

http://editurauniversitaria.ucv.ro/support-vector-machines-an-evolutionary-

resembling-approach.

1 2 2

Total partial 17,33

Numar curent Grant Puncte

1

Grant PNCDI de tip Parteneriate, Contract Nr. 26/2014, cod PN-II-PT-PCCA-2013-4-

1153, Sistem informatic medical inteligent pentru diagnosticul si monitorizarea

tratamentului la pacientii cu neoplasm colorectal,

https://sites.google.com/site/imediatreat/, iulie 2014 - iunie 2016, valoare

Universitatea din Craiova 498.487 lei, Membru.

4

2

Grant PNCDI de tip Parteneriate, CNMP PC - 2076, Contract Nr. 41071, Algoritm

pentru diagnoza si predictia evolutiei fibrozei hepatice prin mijloace ultrasonografice

neinvazive optimizate prin analiza stochastica a imaginilor, 2007 - 2010, Membru.

1

3

Grant PNCDI de tip Parteneriate, CNMP PC - 2120, Contract Nr. 11028, Noi modele

de calcul natural in studiul complexitatii si in rezolvarea problemelor complexe, 2007

- 2010, Membru.

1

4Grant CNCSIS de tip A, CNCSIS A-322, Calcul evolutiv: noi paradigme, tehnici si clase.

Aplicatii in optimizare, 2007 - 2009, Membru. 1

5Grant IDEI, CNCSIS IDEI - 508, Noi paradigme computationale in abordarea

problemelor complexe, 2007 - 2009, Membru. 1

6Grant CNCSIS de tip A, CNCSIS A - 1477, Modele computationale inspirate din natura.

Noi paradigme si metaeuristici. Aplicatii reale, 2004 - 2006, Membru.1

Total partial 9

Perspectiva D. Performanța academică

Ruxandra StoeanCarti si capitole publicate

Membru al unui grant/proiect/contract/program de cercetare

1/4

Numar curent Conferinta Puncte Tip

1Nature Inspired Cooperative Strategies for Optimization 2011,

http://www.econ.ubbcluj.ro/~rodica.lung/nicso2011/?page_id=232 C420

2

Conference on Parallel Problem Solving From Nature 2010 , Workshop on

Experimental Methods for the Assessment of Computational Systems,

http://www.imada.sdu.dk/~marco/WEMACS2010/

4 C292

3 International KES Conference on Intelligent Decision Technologies, KES IDT 2016,

http://idt-16.kesinternational.org/cmsIPCdisplay.php1 C750

4International KES Conference on Intelligent Decision Technologies, http://idt-

15.kesinternational.org/cmsIPCdisplay.php1 C750

5

International Symposium on Symbolic and Numeric Algorithms for Scientific

Computing (SYNASC), Workshop on Natural Computing and Applications, 2012,

http://synasc12.info.uvt.ro/workshops/nca-2012

1 C634

6



http://synasc.ro/synasc2013/workshops/nca-2013/

1 C634

7



http://synasc.ro/2014/workshops/nca-2014/

1 C634

8




1 C634

9




1 C634

Total partial 13

Numar curent Conferinta Puncte

1 First East European Conference on Health Care Modelling and Computation - HCMC

2005, Craiova, Romania, 2005, membru (dovada atasata D1).1

Total partial 1

Numar curent Conferinta Puncte

1Ruxandra Stoean, TU Dortmund (World rank 622), Chair of Algorithm Engineering,

Conferinta despre "Evolutionary Clustering", iunie 2003 (dovada atasata D2).1

Total partial 1

Numar curent Universitatea Puncte

1Ruxandra Stoean, TU Dortmund (World rank 622), Facultatea de Informatica,

Catedra de Ingineria Algoritmilor, 01.06-31.07.2009, 2 luni, (dovada atasata D4)2

Total partial 2

Numar curent Echipa

Numar

persoa

ne

An

Puncte

(nr.

persoane

x nr. ani)

1 Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Elia El-Darzi 5 2006 5

Invited speaker la universitati

Visiting professor la o universitate din top 1000

Consolidarea de echipe de cercetare prin publicatii/participari in proiecte in calitate de lider

(autor principal/director)

Membru in comitetul stiintific al unor conferinte

Organizare evenimente stiintifice in calitate de director/membru

2/4

2 Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu 4 2007 4

3 Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, P.H. Millard 5 2008 5

4 Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Elia El-Darzi 5 2009 5

5Director proiect de cercetare nr 42C/2014, Universitatea din Craiova - 4 membri,

https://sites.google.com/site/grantintern2014/4 2014 4

Ruxandra Stoean este prim autor in 2009 pentru urmatoarele publicatii (in Informatica primul autor si cel

corespondent sunt considerati autori principali, conform UEFISCDI):

Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu, An Evolutionary Approximation for the

Coefficients of Decision Functions within a Support Vector Machine Learning Strategy, Foundations on

Computational Intelligence, Aboul Ella Hassanien and Ajith Abraham (Eds.), Vol. 1, pp. 83-114, ISSN 1860-949X,

2009.

Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu, Support Vector Machine Learning with

an Evolutionary Engine, Journal of the Operational Research Society (2009 Impact Factor: 1.009), Palgrave

Macmillan, Vol. 60, Issue 8 (August 2009), Special Issue: Data Mining and Operational Research: Techniques and

Applications, Kweku-Muata Osei-Bryson and Vic J Rayward-Smith (Guest Editors), pp. 1116-1122, ISSN 0160-5682,

2009.

Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Evolutionary Detection of Separating Hyperplanes

in E-mail Classification, Acta Cibiniensis, Vol. LV Technical series, University "Lucian Blaga" Sibiu Press, ISSN 1583-

7149, pp. 41-46, 2007.

Ruxandra Stoean este prim autor in 2008 pentru urmatoarea publicatie (in Informatica primul autor si cel


Ruxandra Stoean, Catalin Stoean, D. Dumitrescu, Investigating Landscape Topology for Subpopulation

Differentiation in Multimodal Evolutionary Algorithms. Study on Crowding Genetic Chromodynamics, IEEE

Postproceedings, 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing -

SYNASC 2008, IEEE Press, pp. 551-554, 2008.

Ruxandra Gorunescu, P.H. Millard, D. Dumitrescu, Evolutionary Placement Decisions of a Multidisciplinary Panel

using Genetic Chromodynamics, Journal of Enterprise Information Management (INSPEC indexed), Vol. 21, No. 1,

pp. 93-104, ISSN 1741-0398, 2008.

Ruxandra Stoean, Mike Preuss, Catalin Stoean, Approximating the Number of Attraction Basins of a Function by

Means of Clustering and Evolutionary Algorithms, Proceedings of the 8th International Conference on Artificial

Intelligence and Digital Communications - AIDC 2008, pp. 171-180, 2008.

Ruxandra Stoean, Catalin Stoean, D. Dumitrescu, Investigating Landscape Topology for Subpopulation

Differentiation in Multimodal Evolutionary Algorithms. Study on Crowding Genetic Chromodynamics, IEEE

Postproceedings, 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing -

SYNASC 2008, IEEE Press, pp. 551-554, 2008.

Ruxandra Stoean, D. Dumitrescu, Catalin Stoean, Nonlinear Evolutionary Support Vector Machines. Application to

Classification, Studia Babes-Bolyai, Seria Informatica, Vol. LI, No. 1, pp. 3-12, 2006.

Ruxandra Stoean, Catalin Stoean, Mike Preuss, Elia El-Darzi, D. Dumitrescu, Evolutionary Support Vector Machines

for Diabetes Mellitus Diagnosis, IEEE IS 2006, Westminster, London, pp. 182-187, ISBN 1-4244-0196-8, 2006.

Ruxandra Stoean, Mike Preuss, D. Dumitrescu, Catalin Stoean, Evolutionary Support Vector Regression Machines,

IEEE Post-proceedings SYNASC 2006, IEEE Press, Lisa O'Conner (Ed.), Los Alamitos, CA, USA, pp. 330-335, ISBN 0-

7695-2740-X, 2006.

Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Evolutionary Support Vector Machines for Spam

Filtering, RoEduNet IEEE International Conference, Sibiu, Romania, 2006, pp. 261-266.



Ruxandra Stoean, Mike Preuss, Catalin Stoean, D. Dumitrescu, Concerning the Potential of Evolutionary Support

Vector Machines, The IEEE Congress on Evolutionary Computation - CEC 2007 (ISI proceedings), Singapore, pp.

1436 - 1443, 2007.



Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Evolutionary Multi-class Support Vector Machines

for Classification, International Journal of Computers, Communications & Control, Supplementary Issue,

International Conference on Computers and Communications - ICCC 2006, Baile Felix Spa - Oradea, Romania,

2006, pp. 423 � 428, ISSN 1841-9836.

Ruxandra Stoean, Catalin Stoean, Mike Preuss, D. Dumitrescu, Forecasting Soybean Diseases from Symptoms by

Means of Evolutionary Support Vector Machines, Phytologia Balcanica (ISI indexed), Vol. 12, No. 3, pp. 345 - 350,

Sofia, Bulgaria, ISSN 1310-7771, 2006.

3/4

Total partial 23

Numar curent Universitatea Puncte

1Ruxandra Stoean, Premiul "Grigore Moisil" al Academiei Romane pentru anul 2006,

decernat in 2008 (dovada atasata D4).

2

Ruxandra Stoean, Diploma de onoare, locul I in cadrul Departamentului de

Informatica, Facultatea de Stiinte, Gala Excelentei in Cercetare, Universitatea din

Craiova, 2016 (dovada atasata D5).

Total partial 6

Total Minim necesar abilitare

72,33 60

Ruxandra Stoean

In 2014 am fost director de proiect pentru contractul 42C, castigat prin competitie la Universitatea din Craiova.

Titlul Proiectului este "Evoluţia prototipurilor în clasificarea cu maşini cu suport vectorial şi reţele neuronale".

Premii si alte merite

6

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