Vasile Palade : Publications
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[1]
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). 2013.
Details about Class Imbalance Learning Methods for Support Vector Machines | BibTeX data for Class Imbalance Learning Methods for Support Vector Machines | Download (pdf) of Class Imbalance Learning Methods for Support Vector Machines
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[2]
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.
in press 2013
Details about An Insight into Classification with Imbalanced Data: Empirical Results and Current Trends on Using Data Intrinsic Characteristics | BibTeX data for An Insight into Classification with Imbalanced Data: Empirical Results and Current Trends on Using Data Intrinsic Characteristics | Link to An Insight into Classification with Imbalanced Data: Empirical Results and Current Trends on Using Data Intrinsic Characteristics
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[3]
Solving the Power Economic Dispatch Problem with Generator Constraints by Random Drift Particle Swarm Optimization
J. Sun‚ V. Palade‚ X. Wu‚ W. Fang and Z. Wang
In IEEE Trans. on Industrial Informatics. 2013.
in press‚ available online
Details about Solving the Power Economic Dispatch Problem with Generator Constraints by Random Drift Particle Swarm Optimization | BibTeX data for Solving the Power Economic Dispatch Problem with Generator Constraints by Random Drift Particle Swarm Optimization | Link to Solving the Power Economic Dispatch Problem with Generator Constraints by Random Drift Particle Swarm Optimization
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[4]
Dense Structural Expectation Maximisation with Parallelisation for Efficient Large−Network Structural Inference
C. Fogelberg and V. Palade
In International Journal on Artificial Intelligence Tools. Vol. 22. No. 3. 2013.
Details about Dense Structural Expectation Maximisation with Parallelisation for Efficient Large−Network Structural Inference | BibTeX data for Dense Structural Expectation Maximisation with Parallelisation for Efficient Large−Network Structural Inference | Link to Dense Structural Expectation Maximisation with Parallelisation for Efficient Large−Network Structural Inference
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[5]
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.
Details about Advanced Techniques in Web Intelligence −2: Web User Browsing Behaviour and Preference Analysis | BibTeX data for Advanced Techniques in Web Intelligence −2: Web User Browsing Behaviour and Preference Analysis
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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.
Details about Tracking Multiple Optima in Dynamic Environments by Quantum−Behavior Particle Swarm using Speciation | BibTeX data for Tracking Multiple Optima in Dynamic Environments by Quantum−Behavior Particle Swarm using Speciation
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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
Details about Convergence Analysis and Improvements of Quantum−Behaved Particle Swarm Optimization | BibTeX data for Convergence Analysis and Improvements of Quantum−Behaved Particle Swarm Optimization | Download (pdf) of Convergence Analysis and Improvements of Quantum−Behaved Particle Swarm Optimization
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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.
Details about Adjusted Geometric−mean: A Novel Performance Measure for Imbalanced Bioinformatics Datasets Learning | BibTeX data for Adjusted Geometric−mean: A Novel Performance Measure for Imbalanced Bioinformatics Datasets Learning | Link to Adjusted Geometric−mean: A Novel Performance Measure for Imbalanced Bioinformatics Datasets Learning
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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.
Details about Selection of Significant On−Road Sensor Data for Short−Term Traffic Flow Forecasting Using the Taguchi Method. | BibTeX data for Selection of Significant On−Road Sensor Data for Short−Term Traffic Flow Forecasting Using the Taguchi Method.
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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.
Details about Using Structural Information and Citation Evidence to Detect Significant Plagiarism Cases in Scientific Publications | BibTeX data for Using Structural Information and Citation Evidence to Detect Significant Plagiarism Cases in Scientific Publications | Download (pdf) of Using Structural Information and Citation Evidence to Detect Significant Plagiarism Cases in Scientific Publications
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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.
Details about Quantum−Behaved Particle Swarm Optimization: Analysis of the Individual Particle’s Behavior and Parameter Selection | BibTeX data for Quantum−Behaved Particle Swarm Optimization: Analysis of the Individual Particle’s Behavior and Parameter Selection | Download (pdf) of Quantum−Behaved Particle Swarm Optimization: Analysis of the Individual Particle’s Behavior and Parameter Selection
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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.
Details about Modeling and Optimization of Fermentation Processes with Genetic Programming and Quantum−Behaved Particle Swarm Optimization | BibTeX data for Modeling and Optimization of Fermentation Processes with Genetic Programming and Quantum−Behaved Particle Swarm Optimization
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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.
Details about Quantum−Behaved Particle Swarm Optimization with Gaussian Distributed Local Attractor Point | BibTeX data for Quantum−Behaved Particle Swarm Optimization with Gaussian Distributed Local Attractor Point | Download (pdf) of Quantum−Behaved Particle Swarm Optimization with Gaussian Distributed Local Attractor Point
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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.
Details about Building Interpretable Fuzzy Models for High Dimensional Data Analysis in Cancer Diagnosis | BibTeX data for Building Interpretable Fuzzy Models for High Dimensional Data Analysis in Cancer Diagnosis | Download (pdf) of Building Interpretable Fuzzy Models for High Dimensional Data Analysis in Cancer Diagnosis
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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.
Details about A customizable fuzzy system for offline handwritten character recognition | BibTeX data for A customizable fuzzy system for offline handwritten character recognition | Link to A customizable fuzzy system for offline handwritten character recognition
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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.
Details about Ensemble of Elman Neural Networks and Support Vector Machines for Reverse Engineering of Gene Regulatory Networks | BibTeX data for Ensemble of Elman Neural Networks and Support Vector Machines for Reverse Engineering of Gene Regulatory Networks
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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.
Details about iPlag: Intelligent Plagiarism Reasoner in Scientific Publications | BibTeX data for iPlag: Intelligent Plagiarism Reasoner in Scientific Publications
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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.
Details about Web Ad−Slot Offline Scheduling Using an Ant Colony Algorithm | BibTeX data for Web Ad−Slot Offline Scheduling Using an Ant Colony Algorithm
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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.
Details about FSVM−CI: Fuzzy Support Vector Machines for Class Imbalance Learning | BibTeX data for FSVM−CI: Fuzzy Support Vector Machines for Class Imbalance Learning | Link to FSVM−CI: Fuzzy Support Vector Machines for Class Imbalance Learning
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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.
Details about Using Classifier Fusion Techniques for Protein Secondary Structure Prediction | BibTeX data for Using Classifier Fusion Techniques for Protein Secondary Structure Prediction | Download (pdf) of Using Classifier Fusion Techniques for Protein Secondary Structure Prediction
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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.
Details about Efficient resampling methods for training support vector machines with imbalanced datasets | BibTeX data for Efficient resampling methods for training support vector machines with imbalanced datasets | Download (pdf) of Efficient resampling methods for training support vector machines with imbalanced datasets
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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
Details about GreenSim: A network simulator for comprehensively validating and evaluating new machine learning techniques for network structural inference | BibTeX data for GreenSim: A network simulator for comprehensively validating and evaluating new machine learning techniques for network structural inference
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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 about microPred: Effective classification of pre−miRNAs for human miRNA gene prediction | BibTeX data for microPred: Effective classification of pre−miRNAs for human miRNA gene prediction | DOI (doi:10.1093/bioinformatics/btp107) | Link to microPred: Effective classification of pre−miRNAs for human miRNA gene prediction
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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.
Details about Model−based fault detection and isolation of a steam generator using neuro−fuzzy networks | BibTeX data for Model−based fault detection and isolation of a steam generator using neuro−fuzzy networks
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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.
Details about Signal denoising in engineering problems through the Minimum Gradient Method | BibTeX data for Signal denoising in engineering problems through the Minimum Gradient Method
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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.
Details about Evaluating Clustering Algorithms for Genetic Regulatory Network Structural Inference | BibTeX data for Evaluating Clustering Algorithms for Genetic Regulatory Network Structural Inference
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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.
Details about AGm: A new performance measure for class imbalance learning. Application to Bioinformatics problems. | BibTeX data for AGm: A new performance measure for class imbalance learning. Application to Bioinformatics problems.
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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.
Details about Machine Learning and Genetic Regulatory Networks: A Review and a Roadmap | BibTeX data for Machine Learning and Genetic Regulatory Networks: A Review and a Roadmap | Download (pdf) of Machine Learning and Genetic Regulatory Networks: A Review and a Roadmap
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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
Details about Noise Reduction in a Non−Homogenous Ground Penetrating Radar Problem by Multiobjective Neural Networks | BibTeX data for Noise Reduction in a Non−Homogenous Ground Penetrating Radar Problem by Multiobjective Neural Networks
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[30]
Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
J. D. Velasquez and V. Palade
2008.
Details about Adaptive Web Sites: A Knowledge Extraction from Web Data Approach | BibTeX data for Adaptive Web Sites: A Knowledge Extraction from Web Data Approach | Link to Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
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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.
Details about The Q−norm Complexity Measure and the Minimum Gradient Method: A Novel Approach to the Machine Learning Structural Risk Minimization Problem | BibTeX data for The Q−norm Complexity Measure and the Minimum Gradient Method: A Novel Approach to the Machine Learning Structural Risk Minimization Problem | Link to The Q−norm Complexity Measure and the Minimum Gradient Method: A Novel Approach to the Machine Learning Structural Risk Minimization Problem
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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.
Details about The Minimum Gradient Complexity Control Applied to Sensitivity Extraction of Electromagnetic Devices | BibTeX data for The Minimum Gradient Complexity Control Applied to Sensitivity Extraction of Electromagnetic Devices
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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.
Details about An improved non−comparative classification method for human microRNA gene prediction | BibTeX data for An improved non−comparative classification method for human microRNA gene prediction
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[34]
Advances in Evolutionary Computing for System Design
L. Jain‚ V. Palade and D. Srinivasan, editors
Springer. May, 2007.
Details about Advances in Evolutionary Computing for System Design | BibTeX data for Advances in Evolutionary Computing for System Design | DOI (10.1007/978-3-540-72377-6)
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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.
Details about A Comprehensive Fuzzy−Based Framework for Cancer Microarray Data Gene Expression Analysis | BibTeX data for A Comprehensive Fuzzy−Based Framework for Cancer Microarray Data Gene Expression Analysis
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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.
Details about Building a Knowledge Base for Implementing a Web−based Computerized Recommendation System | BibTeX data for Building a Knowledge Base for Implementing a Web−based Computerized Recommendation System
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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.
Details about A Knowledge Base for the Maintenance of Knowledge Extracted from Web Data | BibTeX data for A Knowledge Base for the Maintenance of Knowledge Extracted from Web Data
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[38]
Computational Intelligence in Fault Diagnosis
V. Palade‚ C.D. Bocaniala and L. Jain, editors
Springer. August, 2006.
Details about Computational Intelligence in Fault Diagnosis | BibTeX data for Computational Intelligence in Fault Diagnosis | DOI (10.1007/978-1-84628-631-5)
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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.
Details about Genetic Algorithm Convergence Analysis Using a Unified Representation of Genes and the Hamming Distance | BibTeX data for Genetic Algorithm Convergence Analysis Using a Unified Representation of Genes and the Hamming Distance
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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.
Details about Multi−Classifier Systems: Review and a Roadmap for Developers | BibTeX data for Multi−Classifier Systems: Review and a Roadmap for Developers
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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 The 10th Int. Conf. on Knowledge Based Intelligent Information & Engineering Systems. LNAI − Springer. 2006.
Details about Testing online navigation recommendations in a web site | BibTeX data for Testing online navigation recommendations in a web site
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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.
Details about Neuro−Fuzzy Ensemble Approach for Microarray Cancer Gene Expression Data Analysis | BibTeX data for Neuro−Fuzzy Ensemble Approach for Microarray Cancer Gene Expression Data Analysis
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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.
Details about Optimized Precision − A New Measure for Classifier Performance Evaluation | BibTeX data for Optimized Precision − A New Measure for Classifier Performance Evaluation
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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.
Details about Experimental Validation of a Novel Fuzzy Classifier Performance | BibTeX data for Experimental Validation of a Novel Fuzzy Classifier Performance
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[45]
Computational Intelligence: Engineering of Hybrid Systems
M. Negoita‚ D. Neagu and V. Palade
Springer−Verlag. 2005.
Details about Computational Intelligence: Engineering of Hybrid Systems | BibTeX data for Computational Intelligence: Engineering of Hybrid Systems
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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.
Details about Human−like fault diagnosis using a neural network implementation of plausibility and relevance | BibTeX data for Human−like fault diagnosis using a neural network implementation of plausibility and relevance
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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.
Details about A Neural Network Based Multi−Classifier System for Gene Identification in DNA Sequences | BibTeX data for A Neural Network Based Multi−Classifier System for Gene Identification in DNA Sequences
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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.
Details about Fuzzy−Based Refinement of the Fault Diagnosis Task in Industrial Devices | BibTeX data for Fuzzy−Based Refinement of the Fault Diagnosis Task in Industrial Devices
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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.
Details about Automatic Fuzzy Rule Base Generation for On−line Handwritten Alphanumeric Character Recognition | BibTeX data for Automatic Fuzzy Rule Base Generation for On−line Handwritten Alphanumeric Character Recognition
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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.
Details about Blind Separation of Mixed Kurtosis Signed Signals using Partial Observations and Low Complexity Activation Functions | BibTeX data for Blind Separation of Mixed Kurtosis Signed Signals using Partial Observations and Low Complexity Activation Functions
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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.
Details about A Novel Fuzzy Classification Solution for Fault Diagnosis | BibTeX data for A Novel Fuzzy Classification Solution for Fault Diagnosis
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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.
Details about Neural Network Based Optimal Control of a Biosynthesis Process | BibTeX data for Neural Network Based Optimal Control of a Biosynthesis Process
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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.
Details about MultinNNProm: A multi−classifier system for finding genes | BibTeX data for MultinNNProm: A multi−classifier system for finding genes
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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 Based Intelligent Information & Engineering Systems. 2004.
Details about Refinement of the diagnosis process performed with a fuzzy classifier | BibTeX data for Refinement of the diagnosis process performed with a fuzzy classifier
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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 Based Intelligent Information & Engineering Systems. 2004.
Details about An efficient fuzzy method for handwritten character recognition | BibTeX data for An efficient fuzzy method for handwritten character recognition
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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 Based Intelligent Information & Engineering Systems. 2004.
Details about Diagnosing the population state in a genetic algorithm using Hamming distance | BibTeX data for Diagnosing the population state in a genetic algorithm using Hamming distance
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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.
Details about Proceedings of KES 2003− The 7th Int. Conf. on Knowledge−Based Intelligent Information and Engineering Systems | BibTeX data for Proceedings of KES 2003− The 7th Int. Conf. on Knowledge−Based Intelligent Information and Engineering Systems
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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.
Details about A Neuro−Fuzzy Approach for Functional Genomics Data Interpretation and Analysis | BibTeX data for A Neuro−Fuzzy Approach for Functional Genomics Data Interpretation and Analysis
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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.
Details about Low complexity functions for stationary independent component mixtures | BibTeX data for Low complexity functions for stationary independent component mixtures
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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.
Details about Sequential Source Separation of Mixed Kurtosis Sign Sources | BibTeX data for Sequential Source Separation of Mixed Kurtosis Sign Sources
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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.
Details about Neural and Neuro−Fuzzy Integration in a Knowledge−Based System for Air Quality Prediction | BibTeX data for Neural and Neuro−Fuzzy Integration in a Knowledge−Based System for Air Quality Prediction
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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.
Details about Neuro−fuzzy based fault diagnosis applied to an electro−pneumatic valve | BibTeX data for Neuro−fuzzy based fault diagnosis applied to an electro−pneumatic valve | Download (pdf) of Neuro−fuzzy based fault diagnosis applied to an electro−pneumatic valve
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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.
Details about Modular neuro−fuzzy networks used in explicit and implicit knowledge integration | BibTeX data for Modular neuro−fuzzy networks used in explicit and implicit knowledge integration | Download (pdf) of Modular neuro−fuzzy networks used in explicit and implicit knowledge integration
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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.
Details about Fault diagnosis of an industrial gas turbine using neuro−fuzzy methods | BibTeX data for Fault diagnosis of an industrial gas turbine using neuro−fuzzy methods | Download (pdf) of Fault diagnosis of an industrial gas turbine using neuro−fuzzy methods
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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.
Details about Neuro−fuzzy based analysis of gene expression data | BibTeX data for Neuro−fuzzy based analysis of gene expression data
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[66]
Hybrid Intelligent Systems
V. Palade and D. Neagu
Matrix ROM Publishers, Bucharest. 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 authors: D. Neagu & V. Palade.
Details about Hybrid Intelligent Systems | BibTeX data for Hybrid Intelligent Systems
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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.
Details about Analysis of a neuro−fuzzy aproach of air pollution: building a case study | BibTeX data for Analysis of a neuro−fuzzy aproach of air pollution: building a case study
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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.
Details about Interpretation of trained neural networks by rule extraction | BibTeX data for Interpretation of trained neural networks by rule extraction | Download (pdf) of Interpretation of trained neural networks by rule extraction
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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.
Details about An interactive fuzzy operator used in rule extraction from neural networks | BibTeX data for An interactive fuzzy operator used in rule extraction from neural networks
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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.
Details about A neuro−fuzzy aproach to photochemical pollution prediction | BibTeX data for A neuro−fuzzy aproach to photochemical pollution prediction
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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.
Details about A procedure of fault detection for driving systems using self−organizing neural networks | BibTeX data for A procedure of fault detection for driving systems using self−organizing neural networks | Download (pdf) of A procedure of fault detection for driving systems using self−organizing neural networks
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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
Details about An interactive fuzzy operator used in rule extraction from neural networks | BibTeX data for An interactive fuzzy operator used in rule extraction from neural networks
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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.
Details about Using fuzzy neural networks for process modelling | BibTeX data for Using fuzzy neural networks for process modelling | Download (pdf) of Using fuzzy neural networks for process modelling
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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.
Details about An aproach of DC driving system neural control by inverting forward model | BibTeX data for An aproach of DC driving system neural control by inverting forward model | Download (pdf) of An aproach of DC driving system neural control by inverting forward model
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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.
Details about Rule extraction from neural networks by interval propagation | BibTeX data for Rule extraction from neural networks by interval propagation | Download (pdf) of Rule extraction from neural networks by interval propagation
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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.
Details about Bond Graphs and the Semi−Qualitative Encoding of the Faulty Behaviour in Conductive Flow Systems | BibTeX data for Bond Graphs and the Semi−Qualitative Encoding of the Faulty Behaviour in Conductive Flow Systems
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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.
Details about A fuzzy neural network based controller implementation using standard neurons | BibTeX data for A fuzzy neural network based controller implementation using standard neurons
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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.
Details about Neural network−based control by inverting neural models | BibTeX data for Neural network−based control by inverting neural models | Download (pdf) of Neural network−based control by inverting neural models
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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.
Details about Fault recognition to a DC motor using neural networks | BibTeX data for Fault recognition to a DC motor using neural networks
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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.
Details about Aspects of integration of explicit and implicit knowledge in connectionist expert systems | BibTeX data for Aspects of integration of explicit and implicit knowledge in connectionist expert systems | Download (pdf) of Aspects of integration of explicit and implicit knowledge in connectionist expert systems
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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.
Details about A neural network based method for controlling a DC motor | BibTeX data for A neural network based method for controlling a DC motor
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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.
Details about Genetic algorithm optimization of knowledge extraction from neural networks | BibTeX data for Genetic algorithm optimization of knowledge extraction from neural networks | Download (pdf) of Genetic algorithm optimization of knowledge extraction from neural networks
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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.
Details about Predictability of fuzzy compiled models for real time expert control systems | BibTeX data for Predictability of fuzzy compiled models for real time expert control systems
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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.
Details about On fuzzy rule acquiring using fuzzy neural networks | BibTeX data for On fuzzy rule acquiring using fuzzy neural networks
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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.
Details about A fuzzy approach in pattern recognition using potential function method | BibTeX data for A fuzzy approach in pattern recognition using potential function method
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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.
Details about Eliminating redundant rules in fuzzy neural networks | BibTeX data for Eliminating redundant rules in fuzzy neural networks
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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.
Details about A method for compiling neural networks into fuzzy rules using genetic algorithms and hierarchical approach | BibTeX data for A method for compiling neural networks into fuzzy rules using genetic algorithms and hierarchical approach | Download (pdf) of A method for compiling neural networks into fuzzy rules using genetic algorithms and hierarchical approach
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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.
Details about A hierarchical approach for mapping neural networks into fuzzy rules | BibTeX data for A hierarchical approach for mapping neural networks into fuzzy rules
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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.
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