Vasile Palade : Publications
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[1] |
An Insight into Classification with Imbalanced Data: Empirical Results and Current Trends on Using Data Intrinsic Characteristics V. Lopez‚ A. Fernandez‚ S. Garcia‚ V. Palade and F. Herrera In Information Sciences. 2013. accepted March 2013 |
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[2] |
Solving the Power Economic Dispatch Problem with Generator Constraints by Random Drift Particle Swarm Optimization J. Sun‚ V. Palade‚ W. Fang‚ X. Wu and W. Xu In IEEE Trans. on Industrial Informatics. 2013. accepted |
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[3] |
Dense Structural Expectation Maximisation with Parallelisation for Efficient Large−Network Structural Inference C. Fogelberg and V. Palade In International Journal on Artificial Intelligence Tools. 2013. in press |
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[4] |
Advanced Techniques in Web Intelligence −2: Web User Browsing Behaviour and Preference Analysis J.D. Velasquez‚ V. Palade and L.C. Jain (Eds.) Springer. 2012. |
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[5] |
Class Imbalance Learning Methods for Support Vector Machines R. Batuwita and V. Palade In “Imbalanced Learning: Foundations‚ Algorithms‚ and Applications”‚ Haibo He and Yunqian Ma (Eds.)‚ Wiley‚ (book chapter in press). 2012. |
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[6] |
Tracking Multiple Optima in Dynamic Environments by Quantum−Behavior Particle Swarm using Speciation J. Zhao‚ J. Sun and V. Palade In International Journal of Swarm Intelligence Research. Vol. 3. No. 1. Pages 55−76. 2012. |
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[7] |
Convergence Analysis and Improvements of Quantum−Behaved Particle Swarm Optimization J. Sun‚ X. Wu‚ V. Palade‚ W. Fang‚ C.−H. Lai and W. Xu In Information Sciences. Vol. 193. Pages 81−103. 2012. accepted‚ in print |
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[8] |
Adjusted Geometric−mean: A Novel Performance Measure for Imbalanced Bioinformatics Datasets Learning R. Batuwita and V. Palade In Journal of Bioinformatics and Computational Biology. Vol. 10. No. 4. 2012. |
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[9] |
Selection of Significant On−Road Sensor Data for Short−Term Traffic Flow Forecasting Using the Taguchi Method. K.Y. Chan‚ S. Khadem‚ T. S. Dillon‚ V. Palade‚ J. Singh and E.Chang In IEEE Transactions on Industrial Informatics. Vol. 8. No. 2. Pages 255−266. 2012. |
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[10] |
Using Structural Information and Citation Evidence to Detect Significant Plagiarism Cases in Scientific Publications S. Alzahrani‚ V. Palade‚ N. Salim and A. Abraham In Journal of the American Society for Information Science and Technology. Vol. 63. No. 2. Pages 286−312. 2012. |
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[11] |
Quantum−Behaved Particle Swarm Optimization: Analysis of the Individual Particle’s Behavior and Parameter Selection J. Sun‚ W. Fang‚ X. Wu‚ V. Palade and X. Wenbo In Evolutionary Computation. Vol. 20. No. 3. 2012. |
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[12] |
Modeling and Optimization of Fermentation Processes with Genetic Programming and Quantum−Behaved Particle Swarm Optimization J. Sun‚ V. Palade and X. Wu In CIMA Workshop − European Conference on Artficial Intelligence 2012‚ Montepellier − France‚ Aug. 2012. 2012. |
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[13] |
Quantum−Behaved Particle Swarm Optimization with Gaussian Distributed Local Attractor Point J. Sun‚ W. Fang‚ V. Palade‚ X. Wu and W. Xu In Applied Mathematics and Computation (Elsevier). Vol. 218. No. 7. Pages 3763−3775. 2011. |
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[14] |
Building Interpretable Fuzzy Models for High Dimensional Data Analysis in Cancer Diagnosis Z. Wang and V. Palade In BMC Genomics. No. 12(S2):S5. 2011. |
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[15] |
A customizable fuzzy system for offline handwritten character recognition R. Batuwita‚ V. Palade and D. C. Bandara In International Journal on Artificial Intelligence Tools. Vol. 20. No. 3. Pages 425−455. 2011. |
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[16] |
Ensemble of Elman Neural Networks and Support Vector Machines for Reverse Engineering of Gene Regulatory Networks S.I. Ao and V. Palade In Applied Soft Computing. Vol. 11. No. 2. Pages 1718−1726. 2011. |
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[17] |
iPlag: Intelligent Plagiarism Reasoner in Scientific Publications S. Alzahrani‚ N. Salim‚ A. Abraham and Vasile Palade In Proc. of IEEE WICT 2011‚ Mumbai −India‚ Dec 11−14‚ 2011. 2011. |
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[18] |
Web Ad−Slot Offline Scheduling Using an Ant Colony Algorithm Vasile Palade and Soumya Banerjee In Proc. of ICMLA 2011 − The 10th IEEE Int. Conf. on Machine Learning and Applications‚ Honolulu‚ USA‚ 18−21 Dec. 2011. Vol. 2. Pages 263−268. 2011. |
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[19] |
FSVM−CI: Fuzzy Support Vector Machines for Class Imbalance Learning Rukshan Batuwita and Vasile Palade In IEEE Transactions on Fuzzy Systems. Vol. 18. No. 3. Pages 558−571. 2010. |
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[20] |
Using Classifier Fusion Techniques for Protein Secondary Structure Prediction M. Kazemian‚ B. Moshiri‚ V. Palade‚ H. Nikbakht and C. Lucas In International Journal of Computational Intelligence in Bioinformatics and Systems Biology. Vol. 1. No. 4. Pages 418−434. 2010. |
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[21] |
Efficient resampling methods for training support vector machines with imbalanced datasets R. Batuwita and V. Palade In Proc. of IJCNN 2010‚ 2010 IEEE World Congress on Comp. Intelligence − WCCI 2010‚ Barcelona − Spain‚ July 2010. 2010. |
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[22] |
GreenSim: A network simulator for comprehensively validating and evaluating new machine learning techniques for network structural inference Christopher Fogelberg and Vasile Palade 2010. in Proc. of 22nd IEEE Int. Conf. on Tools with Artificial Intelligence − ICTAI 2010‚ Arras − France‚ Oct. 2010 |
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[23] |
microPred: Effective classification of pre−miRNAs for human miRNA gene prediction Rukshan Batuwita and Vasile Palade In Bioinformatics. Vol. 25. No. 8. Pages 989−995. February, 2009. Details | BibTeX | DOI (doi:10.1093/bioinformatics/btp107) | Link |
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[24] |
Model−based fault detection and isolation of a steam generator using neuro−fuzzy networks Roozbeh Razavi−Far‚ Hadi Davilu‚ Vasile Palade and Caro Lucas In Neurocomputing. Vol. 72. No. 13−15. Pages 2939−2951. 2009. |
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[25] |
Signal denoising in engineering problems through the Minimum Gradient Method D.A.G. Vieira‚ L. Travassos‚ R.R. Saldanha and V. Palade In Neurocomputing. Vol. 72. No. 10−12. Pages 2270−2275. 2009. |
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[26] |
Evaluating Clustering Algorithms for Genetic Regulatory Network Structural Inference Christopher Fogelberg and Vasile Palade In Proc. of AI−2009 The 29th Int. Conf. on Artificial Intelligence‚ Cambridge−UK‚ 15−17 Dec.. 2009. |
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[27] |
AGm: A new performance measure for class imbalance learning. Application to Bioinformatics problems. R. Batuwita and V. Palade In Proc. of ICMLA09 − The 8th IEEE Int. Conf. on Machine Learning and Applications‚ Miami−USA‚ Dec. 2009. |
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[28] |
Machine Learning and Genetic Regulatory Networks: A Review and a Roadmap Christopher Fogelberg and Vasile Palade No. RR−08−04. Oxford University Computing Laboratory. April, 2008. technical report‚ reduced version published in A. Abraham‚ A.E Hassanien‚ A. Vasilakos‚ W.Pedrycz‚ F. Herrera‚ P. Siarry‚ A. de Carvalho and A. P. Engelbrecht (Eds.)‚ Foundations of Computational Intelligence‚ vol.1‚ chapter 1‚ Springer−Verlag‚ 2009. |
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[29] |
Noise Reduction in a Non−Homogenous Ground Penetrating Radar Problem by Multiobjective Neural Networks L. Travassos‚ D. A. G. Vieira‚ V. Palade and A. Nicolas In IEEE Transaction in Magnetics. Vol. 45. No. 3. Pages 1454−1457. March, 2008. 2009 |
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[30] |
Adaptive Web Sites: A Knowledge Extraction from Web Data Approach J. D. Velasquez and V. Palade 2008. |
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[31] |
The Q−norm Complexity Measure and the Minimum Gradient Method: A Novel Approach to the Machine Learning Structural Risk Minimization Problem D.A.G. Vieira‚ R.H.C. Takahashi‚ V. Palade‚ J.A. Vasconcelos and W.M. Caminhas In IEEE Trans. on Neural Networks. Vol. 19. No. 8. Pages 1415−1431. 2008. |
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[32] |
The Minimum Gradient Complexity Control Applied to Sensitivity Extraction of Electromagnetic Devices D.A.G. Vieira‚ J.A. Vasconcelos‚ V. Palade and W.M. Caminhas In IEEE Transaction in Magnetics. Vol. 44. Pages 1114−1117. 2008. |
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[33] |
An improved non−comparative classification method for human microRNA gene prediction R. Batuwita and V. Palade In Proc.of the 8th IEEE International Conference on BioInformatics and BioEngineering‚ Athens Greece‚ Oct.. 2008. |
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[34] |
Advances in Evolutionary Computing for System Design L. Jain‚ V. Palade and D. Srinivasan, editors Springer. May, 2007. |
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[35] |
A Comprehensive Fuzzy−Based Framework for Cancer Microarray Data Gene Expression Analysis Z. Wang and V. Palade In Proceedings of the IEEE 7th International Conference on BioInformatics and BioEngineering. October, 2007. |
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[36] |
Building a Knowledge Base for Implementing a Web−based Computerized Recommendation System J.D. Velasquez and V. Palade In International Journal of Artificial Intelligence Tools. Vol. 16. No. 5. Pages 793–828. 2007. |
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[37] |
A Knowledge Base for the Maintenance of Knowledge Extracted from Web Data J.D. Velasquez and V. Palade In Knowledge−Based Systems Journal. Vol. 20. No. 3. Pages 238–248. 2007. |
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[38] |
Computational Intelligence in Fault Diagnosis V. Palade‚ C.D. Bocaniala and L. Jain, editors Springer. August, 2006. |
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[39] |
Genetic Algorithm Convergence Analysis Using a Unified Representation of Genes and the Hamming Distance R. Belea‚ S. Caraman and V. Palade In Int. Journal of Knowledge−Based and Intelligent Engineering Systems. Vol. 10. No. 1. Pages 29–40. 2006. |
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[40] |
Multi−Classifier Systems: Review and a Roadmap for Developers R. Ranawana and V. Palade In Int. Journal of Hybrid Intelligent Systems. Vol. 3. No. 2. Pages 35–61. 2006. |
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[41] |
Testing online navigation recommendations in a web site J. Velasquez and V. Palade In Proc. of KES2006 − The 10th Int. Conf. on Knowledge Based Intelligent Information & Engineering Systems. LNAI − Springer. 2006. |
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[42] |
Neuro−Fuzzy Ensemble Approach for Microarray Cancer Gene Expression Data Analysis Z. Wang‚ V. Palade and Y. Xu In Proceedings of the 2006 International Symposium on Evolving Fuzzy Systems. IEEE. 2006. |
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[43] |
Optimized Precision − A New Measure for Classifier Performance Evaluation R. Ranawana and V. Palade In Proc. of the IEEE World Congress on Computational Intelligence. 2006. |
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[44] |
Experimental Validation of a Novel Fuzzy Classifier Performance C.D. Bocaniala‚ V. Palade and S. Bumbaru In Studies in Informatics and Control. Vol. 14. No. 3. September, 2005. |
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[45] |
Computational Intelligence: Engineering of Hybrid Systems M. Negoita‚ D. Neagu and V. Palade Springer−Verlag. 2005. |
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[46] |
Human−like fault diagnosis using a neural network implementation of plausibility and relevance V. Ariton and V. Palade In Neural Computing and Applications. Vol. 14. No. 2. Pages 149–165. 2005. |
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[47] |
A Neural Network Based Multi−Classifier System for Gene Identification in DNA Sequences R. Ranawana and V. Palade In Neural Computing and Applications. Vol. 14. No. 2. Pages 122–131. 2005. |
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[48] |
Fuzzy−Based Refinement of the Fault Diagnosis Task in Industrial Devices C. D. Bocaniala‚ J. Sa da Costa and V. Palade In Journal of Intelligent Manufacturing. Vol. 16. No. 6. Pages 599–614. 2005. |
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[49] |
Automatic Fuzzy Rule Base Generation for On−line Handwritten Alphanumeric Character Recognition R. Ranawana‚ V. Palade and G.E.M.D.C. Bandara In Int. Journal of Knowledge−Based and Intelligent Engineering Systems. Vol. 9. No. 3. Pages 327–340. 2005. |
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[50] |
Blind Separation of Mixed Kurtosis Signed Signals using Partial Observations and Low Complexity Activation Functions K. Chinnasarn‚ C. Lursinsap and V. Palade In Int. Journal of Computational Intelligence and Applications. Vol. 4. No. 2. Pages 207–223. June, 2004. |
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[51] |
A Novel Fuzzy Classification Solution for Fault Diagnosis C. D. Bocaniala‚ J. Sa da Costa and V. Palade In International Journal of Fuzzy and Intelligent Systems. Vol. 15. No. 3–4. Pages 195–206. 2004. |
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[52] |
Neural Network Based Optimal Control of a Biosynthesis Process G. Fetecau‚ V. Palade and V. Nicolau In Int. Journal of Knowledge−Based and Intelligent Engineering Systems. Vol. 8. No. 2. Pages 107–116. 2004. |
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[53] |
MultinNNProm: A multi−classifier system for finding genes R. Ranawana and V. Palade In Proc. of 9th Online World Conference on Soft Computing in Industrial Applications – WSC9. Springer−Verlag. 2004. |
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[54] |
Refinement of the diagnosis process performed with a fuzzy classifier C.D. Bocaniala‚ J. Sa da Costa and V. Palade In Proc. of 8th Int. Conf. on Knowledge−Based Intelligent Information & Engineering Systems. 2004. |
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[55] |
An efficient fuzzy method for handwritten character recognition R. Ranawana‚ V. Palade and G.E.M.D.C. Bandara In Proc. of 8th Int. Conf. on Knowledge−Based Intelligent Information & Engineering Systems. 2004. |
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[56] |
Diagnosing the population state in a genetic algorithm using Hamming distance R. Belea‚ S. Caraman and V. Palade In Proc. of 8th Int. Conf. on Knowledge−Based Intelligent Information & Engineering Systems. 2004. |
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[57] |
Proceedings of KES 2003− The 7th Int. Conf. on Knowledge−Based Intelligent Information and Engineering Systems V. Palade‚ R.J. Howlett and L. Jain, editors Springer−Verlag. September, 2003. |
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[58] |
A Neuro−Fuzzy Approach for Functional Genomics Data Interpretation and Analysis D. Neagu and V. Palade In Neural Computing and Applications. No. 12. Pages 153–159. 2003. |
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[59] |
Low complexity functions for stationary independent component mixtures K. Chinnasarn‚ C. Lursinsap and V. Palade In Proc. of the 7th Int. Conf. on Knowledge−Based Intelligent Engineering and Information Systems – KES2003. 2003. |
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[60] |
Sequential Source Separation of Mixed Kurtosis Sign Sources K. Chinnasarn‚ C. Lursinsap and V. Palade In Proc. of the 3rd Int. Symposium on Communications and Information Technologies – ISCIT2003. 2003. |
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[61] |
Neural and Neuro−Fuzzy Integration in a Knowledge−Based System for Air Quality Prediction D. Neagu‚ E. Kalapanidas‚ M. Avouris and V. Palade In Applied Intelligence. No. 17(2). Pages 141–169. 2002. |
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[62] |
Neuro−fuzzy based fault diagnosis applied to an electro−pneumatic valve F. J. Uppal‚ R. J. Patton and V. Palade In Proc. of the 15th IFAC World Congress. Pages 2483–2488. 2002. |
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[63] |
Modular neuro−fuzzy networks used in explicit and implicit knowledge integration D. Neagu and V. Palade In Proc. of 15th International Conference of Florida Artificial Intelligence Society – FLAIRS2002. Pages 277–281. 2002. |
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[64] |
Fault diagnosis of an industrial gas turbine using neuro−fuzzy methods V. Palade‚ Ron J. Patton‚ F.J. Uppal‚ J. Quevedo and S. Daley In Proc. of the 15th IFAC World Congress. Pages 2477−2482. 2002. |
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[65] |
Neuro−fuzzy based analysis of gene expression data V. Palade and D. Neagu In Proc. of the 6th International Conference on Knowledge−Based Intelligent Information & Engineering Systems – KES2002. Pages 1088–1092. 2002. |
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[66] |
Hybrid Intelligent Systems V. Palade and D. Neagu Matrix ROM Publishers , AddressBucharest. 2001. in 2 volumes: vol.1 – Hybrid Intelligent Systems: Transformation Systems‚ authors: V. Palade & D. Neagu‚ and vol.2 − Hybrid Intelligent Systems: Combination Systems‚ authors: D. Neagu & V. Palade. |
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[67] |
Analysis of a neuro−fuzzy aproach of air pollution: building a case study D.C. Neagu‚ D. Neagu‚ L. Georgescu and V. Palade In Proc. of the 11th International Symposium on Modelling‚ Simulation and Systems Identification − SIMSIS11. Pages 160–165. 2001. |
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[68] |
Interpretation of trained neural networks by rule extraction V. Palade‚ D. Neagu and R. J. Patton In Bernd Reusch, editor, Computional Intelligence: Theory and Applications. No. 2206. Pages 152–161. Springer Verlag. 2001. |
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[69] |
An interactive fuzzy operator used in rule extraction from neural networks D. Neagu and V. Palade In Neural Network World. No. 10/04/08. Pages 675–684. 2000. |
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[70] |
A neuro−fuzzy aproach to photochemical pollution prediction D. Neagu and V. Palade In Proc. of the 10th Int. Conference on Systems Theory‚ Automation‚ Robotics and Informatics – SINTES10. Pages A/128–A/131. 2000. |
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[71] |
A procedure of fault detection for driving systems using self−organizing neural networks G. Puscasu‚ V. Palade and A. Stancu In Proc. of the 10th IEEE Mediterranean Electrotechnical and Electronical International Conference – MELECON2000. Pages 98–101. 2000. |
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[72] |
An interactive fuzzy operator used in rule extraction from neural networks D. Neagu and V. Palade In Proceedings of the Int. Conference of Neural Network World – NNW2000. Pages 50–51. 2000. an abstract‚ the complete paper was published in the Neural Network World Journal |
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[73] |
Using fuzzy neural networks for process modelling V. Palade‚ D. Neagu and G. Puscasu In Proc. of the 10th Int. Conference on Systems Theory‚ Automation‚ Robotics and Informatics − SINTES10. Pages 264–268. 2000. |
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[74] |
An aproach of DC driving system neural control by inverting forward model V. Palade‚ G. Puscasu and D. Neagu In Proc. of the 10th IEEE Mediterranean Electrotechnical and Electronical International Conference − MELECON2000. Pages 45–48. 2000. |
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[75] |
Rule extraction from neural networks by interval propagation V. Palade‚ D. Neagu and G. Puscasu In Proc. of the 4th IEEE International Conference on Knowledge−Based Intelligent Engineering Systems − KES2000. Pages 217–220. 2000. |
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[76] |
Fuzzy Computing in a Multi−purpose Neural Network Implementation V. Palade In Berndt Reusch, editor, Computional Intelligence: Theory and Applications. No. 1625. Pages 697–700. Springer Verlag. May, 1999. |
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[77] |
Bond Graphs and the Semi−Qualitative Encoding of the Faulty Behaviour in Conductive Flow Systems V. Ariton‚ S. Bumbaru and V. Palade In The Annual Scientific Bulletin of the University of Galati. Vol. 3. Pages 43–48. 1999. |
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[78] |
A fuzzy neural network based controller implementation using standard neurons V. Palade‚ V. Ariton and V. Mazilescu In The Annual Scientific Bulletin of the University of Galati. Vol. 3. Pages 56–61. 1999. |
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[79] |
Neural network−based control by inverting neural models V. Palade‚ G. Puscasu and D. Neagu In Journal of Control Engineering and Applied Informatics. Vol. 12/01/08. Pages 25–35. 1999. |
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[80] |
Fault recognition to a DC motor using neural networks G. Puscasu and V. Palade In Proceedings of the 2nd Int. Conference on Electromechanical Systems − SIELMEC'99. Pages 249–252. 1999. |
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[81] |
Aspects of integration of explicit and implicit knowledge in connectionist expert systems D. Neagu‚ M. G. Negoita and V. Palade In Proc. of the 6th IEEE International Conference on Neural Information Processing – ICONIP99. Vol. 2. Pages 759–764. 1999. |
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[82] |
A neural network based method for controlling a DC motor V. Palade and G. Puscasu In Proceedings of the 2nd Int. Conference on Electromechanical Systems – SIELMEC'99. Pages 51–54. 1999. |
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[83] |
Genetic algorithm optimization of knowledge extraction from neural networks V. Palade‚ M.G. Negoita and V. Ariton In Proc. of the 6th IEEE International Conference on Neural Information Processing – ICONIP99. Vol. 2. Pages 752–758. 1999. |
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[84] |
Predictability of fuzzy compiled models for real time expert control systems V. Mazilescu‚ C. Novac and V. Palade In The Annual Scientific Bulletin of the University of Galati. Vol. 3. Pages 101–110. 1998. |
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[85] |
On fuzzy rule acquiring using fuzzy neural networks V. Palade‚ V. Ariton and G. Puscasu In The Annual Scientific Bulletin of the University of Galati. Vol. 3. Pages 116–120. 1998. |
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[86] |
A fuzzy approach in pattern recognition using potential function method G. Puscasu‚ C. Milos and V. Palade In Proceedings of the 10th International Symposium on Modelling‚ Simulation and Identification Systems – SIMSIS10. Pages 35–38. 1998. |
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[87] |
Eliminating redundant rules in fuzzy neural networks V. Palade and G. Puscasu In Proceedings of the 10th Int. Symposium on Modelling‚ Simulation and System Identification – SIMSIS10. Pages 22–25. 1998. |
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[88] |
A method for compiling neural networks into fuzzy rules using genetic algorithms and hierarchical approach V. Palade‚ S. Bumbaru and M.G. Negoita In Proceedings of the 2nd IEEE International Conference on Knowledge−Based Intelligent Electronic Systems− KES1998. Vol. 2. Pages 353–358. 1998. |
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[89] |
A hierarchical approach for mapping neural networks into fuzzy rules V. Palade‚ V. Ariton and G. Puscasu In The Annual Scientific Bulletin of the University of Galati. Vol. 3. Pages 64–69. 1997. |
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[90] |
Case−based fault detection – a method for parallel processing V. Ariton‚ V. Palade and F. Popescu In Proceedings of the IFAC International Workshop on Manufacturing Systems: Modelling‚ Management and Control – MIM'97. Pages 485–490. 1997. |