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publications

(82)   

• Feature extraction using multi-objective genetic programming
  Yang Zhang and Peter I. Rockett Multi-Objective Machine Learning, volume16ofStudies in Computational Intelligence, chapter 4, Springer, Invited chapter . (2006)
  to Learning Evolutionary programming, Machine Multi-objective genetic algorithms, Optimisation, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Proceedings of the 2000 Congress on Evolutionary Computation CEC00
  La Jolla Marriott Hotel La Jolla, California, USA, IEEE Press, 6-9 July2000.
  to agents, intelligent controlling control, neural design, classifiers, search, foundations, time medical hardware, search techniques, evolutionary processing systems control games information modelling, scheduling, ecological image optimization, modelling evolving like ec, and breast system biological cancer, fitness, record, coevolution, hybrid systems, devices robotic novel applications, dynamic series processing, cultural theory constraint signal tasks, engineering network ec revisiting programming, algorithms, parallel multi-objective developement markets, spaces, the evolvable game learning networks, research image/ new multi-agent paradigms, modeling/ stroganoff, genetic modeling representations, fossil handling, ecosystems, operations local themes, design by brazovayeye on Jun 19, 2008, 5:46 PM
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• Effects of Learning to Interact on the Evolution of Social Behavior of Agents in Continuous Predators-prey Pursuit Problem
  Ivan Tanev and Katsunori Shimohara Proceedings of the 7th European Conference on Artificial Life (ECAL 2003), (2003)
  to multi-agent programming, genetic emergence, learning algorithms, systems, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Fingerprint classification based on learned features
  Xuejun Tan and B. Bhanu and Yingqiang Lin IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews35(3):287--300(Aug)
  to extraction, Bayes feature-learning classification, fingerprint methods, programming, method, discovery, processing NIST-4 feature algorithms, primitive Bayesian algorithm, image (artificial learning operator composite intelligence), visual databases genetic classification identification, database, operations classifier, by brazovayeye on Jun 19, 2008, 5:46 PM
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• Genetic Programming with a Genetic Algorithm for Feature Construction and Selection
  Matthew G. Smith and Larry Bull Genetic Programming and Evolvable Machines6(3):265--281September2005. Published online: 17 August 2005 .
  to construction, programming, genetic selection, feature learning algorithms, machine classification, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Regularization Approach to Inductive Genetic Programming
  Nikolay Y. Nikolaev and Hitoshi Iba IEEE Transactions on Evolutionary Computing54(4):359--375August2001.
  to series searching, bias, data mining, (artificial learning statistical prediction, inductive intelligence), time regularization, tree structures, programming, search genetic multivariate algorithms, nodes, STROGANOFF,local Kolmogorov-Gabor polynomials, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Neural network and genetic programming for modelling coastal algal blooms
  Nitin Muttil and Kwok-Wing Chau International Journal of Environment and Pollution28(3/4):223--2386 November2006.
  to water harmful Hong modelling, biomass, neural algal learning networks, machine simulation pollution, environmental blooms, programming, genetic techniques, quality Kong, algorithms, artificial by brazovayeye on Jun 19, 2008, 5:46 PM
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• Genetic programming for simultaneous feature selection and classifier design
  Durga Prasad Muni and Nikhil R. Pal and Jyotirmoy Das IEEE Transactions on Systems, Man and Cybernetics, Part B36(1):106--117February2006.
  to extraction, algorithm, scheme, (artificial learning c-class selection classification, online Classification, intelligence), programming, pattern problem, genetic evolutionary classifier feature algorithms, ranking design classifier, by brazovayeye and 2 other people on Jun 19, 2008, 5:46 PM
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• Learning to Control the Program Evolution Process with Cultural Algorithms
  Elena Zannoni and Robert G. Reynolds Evolutionary Computation5(2):181--211summer1997.
  to concept reuse cultural metrics, concepts, learning machine of software programming, genetic methodologies, algorithms, design by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Discovering Knowledge from Noisy Databases using Genetic Programming
  Man Leung Wong and K. S. Leung and K. S. Cheng Journal of the American Society for Information Science(2000)
  to Data Learning Evolutionary programming, Computation, genetic mining, Rule algorithms, by brazovayeye on Jun 19, 2008, 5:35 PM
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• Discovering knowledge from medical databases using evolutionory algorithms
  Man Leung Wong and Wai Lam and Kwong Sak Leung and Po Shun Ngan and Jack C. Y. Cheng IEEE Engineering in Medicine and Biology Magazine19(4):45--55July-August2000.
  to knowledge causality knowledge, tasks, fracture classification, network child errors medical programming, discovery, evolutionary process, advanced clinical algorithms, scoliosis Bayesian continuous learning networks, database relationship fractures, genetic variables, databases, database, systems, management models, novel by brazovayeye on Jun 19, 2008, 5:35 PM
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• Evolving Readable Perl
  Mark S. Withall and Chris J. Hinde and Roger G. Stone GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, page894. New York, Morgan Kaufmann Publishers, 9-13 July2002.
  to Perl, programming, genetic symbolic regression classifier learning algorithms, systems, readable, by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Crossover context in page-based linear genetic programming
  Garnett Wilson and Malcolm Heywood Canadian Journal of Electrical and Computer Engineering27(3):113--116(2002)
  to programming, genetic strategy learning algorithms, by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Crossover Context in Page-based Linear Genetic Programming
  G. C. Wilson and M. I. Heywood IEEE CCECE 2002: IEEE Canadian Conference on Electrical and Computer Engineering, 2, page809--814. IEEE Press, 12-15 May2002.
  to fitness simple trail, strategies, change, effective crossover programming, search sequences, operator, algorithms, instructions, Learning, problems, memories, Strategy strategy (artificial code learning Mateo San register intelligence), genetic artificial ants, based by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Rule-based Genetic Programming
  Thomas Weise and Michael Zapf and Kurt Geihs Proceedings of BIONETICS 2007, 2nd International Conference on Bio-Inspired Models of Network, Information, and Computing Systems, Radisson SAS Beke Hotel, 43. Terez krt., Budapest H-1067, Hungary, Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (ICST), IEEE, ACM, December~102007.
  to Section, Systems, Learning Programming, Classifier Critical Genetic Rule-based programming, Distributed genetic algorithms, Neutrality, Systems GP, Epistasis, by brazovayeye on Jun 19, 2008, 5:35 PM
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• Evolving Classifiers -- Evolutionary Algorithms in Data Mining
  Thomas Weise and Stefan Achler and Martin Göb and Christian Voigtmann and Michael Zapf Kasseler Informatikschriften (KIS), volume2007. University of Kassel, University of Kassel, September~28,2007.
  to Evolutionary Learning Computation, Classifier Algorithm, Genetic Data Mining, Data-Mining-Cup, System, DMC System 2007, by brazovayeye on Jun 19, 2008, 5:35 PM
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• Training genetic programming on half a million patterns: an example from anomaly detection
  Dong Song and Malcolm I. Heywood and A. Nur Zincir-Heywood IEEE Transactions on Evolutionary Computation9(3):225--239June2005.
  to KDD-99 fitness data filtering, mining, security RSS-DSS subset hierarchical of programming programming, sets algorithms, data, function, algorithm, dynamical set,Dynamic functions, (artificial learning training, cost selection anomaly intelligence), detection dataset genetic real-world detection, (DSS), large intrusion by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Constructive Induction of Fuzzy Cartesian Granule Feature Models using Genetic Programming with Applications
  James G. Shanahan and James F. Baldwin and Trevor P. Martin Proceedings of the Congress on Evolutionary Computation, 1, page218--226. Mayflower Hotel, Washington D.C., USA, IEEE Press, 6-9 July1999.
  to programming, genetic learning algorithms, by brazovayeye on Jun 19, 2008, 5:35 PM
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• Constructive induction and genetic algorithms for learning concepts with complex interaction
  Leila Shila Shafti and Eduardo Pérez Pérez GECCO 2005: Proceedings of the 2005 conference on Genetic and evolutionary computation, 2, page1811--1818. Washington DC, USA, ACM Press, 25-29 June2005.
  to shared Genetics-Based Learning, Systems, construction, Learning experimentation, Machine Classifier attribute interaction, design, genetic constructive selection, feature algorithms, attributes induction, by brazovayeye on Jun 19, 2008, 5:35 PM
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• Comparing learning classifier systems and Genetic Programming: a case study
  S. Sette and B. Wyns and L. Boullart Engineering Applications of Artificial Intelligence17(2):199--204(2004)
  to Learning programming, genetic process, classifier learning algorithms, systems, machine production Textile Rule-based by brazovayeye on Jun 19, 2008, 5:35 PM
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