Evolutionary multiobjective optimization and multiobjective fuzzy system design
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Genetic Feature Selection for Optimal Functional Link Artificial Neural Network in Classification
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Evolutionary multiobjective fuzzy system design
Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems
Evolutionary many-objective optimization by NSGA-II and MOEA/D with large populations
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A notable swarm approach to evolve neural network for classification in data mining
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Fuzzy clustering algorithms for unsupervised change detection in remote sensing images
Information Sciences: an International Journal
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Data Mining (DM) is the most commonly used name to describe such computational analysis of data and the results obtained must conform to several objectives such as accuracy, comprehensibility, interest for the user etc. Though there are many sophisticated techniques developed by various interdisciplinary fields only a few of them are well equipped to handle these multi-criteria issues of DM. Therefore, the DM issues have attracted considerable attention of the well established multiobjective genetic algorithm community to optimize the objectives in the tasks of DM. The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.