Applying genetic algorithms to set the optimal combination of forest fire related variables and model forest fire susceptibility based on data mining models. The case of Dayu County, China

Feature Selection task is one of most complicated and actual in Data Mining area. Any approaches for it solving are based on non-mathematical and presentative hypothesis. New approach for evaluation of medical features information quantity, based on optimal combination of Feature Selection and Feature Extraction methods. This approach permits to produce optimal reduced number of features with linguistic interpreting of each ones. Hybrid system of Feature Selection/Extraction is proposed. This system is numerically simple, can produce Feature Selection/ Extraction with any number of features using standard method of principal component analysis and calculating distance between first principal component and all medical features.

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MO-Miner: A Data Mining Tool Based on Multi-Objective Genetic Algorithms

Advances in Robotics, Automation and Control ◽

10.5772/5522 ◽

2008 ◽

Author(s):

Gina M. B. de Oliveira ◽

Luiz G. A. Martins ◽

Maria C. S. Takiguti

Keyword(s):

Data Mining ◽

Genetic Algorithms ◽

Multi Objective ◽

Data Mining Tool ◽

Mining Tool

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Special Issue on Intelligent Technologies, Fuzzy Systems and Applications

Journal of Advanced Computational Intelligence and Intelligent Informatics ◽

10.20965/jaciii.2003.p0251 ◽

2003 ◽

Vol 7 (3) ◽

pp. 251-251

Author(s):

Nguyen Hoang Phuong ◽

Keyword(s):

Data Mining ◽

Genetic Algorithms ◽

Soft Computing ◽

Fuzzy Systems ◽

Wide Spectrum ◽

Support Vector ◽

Equivalent Transformation ◽

Self Organizing Map ◽

Special Issue

In this issue, we are featuring fifteen papers devoted to intelligent technologies, fuzzy systems and their applications as a special issue of the journal. The papers are selected from papers accepted and presented at the joint Third International Conference on Intelligent Technologies and Third Vietnam-Japan Symposium on Fuzzy Systems and Applications (InTech/VJFuzzy'2002) that was held in Hanoi, Vietnam on December 3-5, 2002. In InTech/VJFuzzy'2002, there was a wide spectrum of research topics on artificial intelligence, fuzzy systems, soft computing, and related fields such as"fuzzy logic", "fuzzy set theory", "fuzzy systems", "AI techniques", "Bayesian networks", "genetic algorithms", "neural networks", "knowledge discovery and data mining", "speech recognition", "soft computing in medicine", among others. More than 60 papers were accepted and presented by authors from many countries, including Australia, China, India, Korea, Germany, France, Thailand, Taiwan, Japan, Vietnam, and U.S.A. Fifteen papers that received outstanding recommendations from its reviews were selected in this special issue. The topics addressed by these selected papers include fuzzy rule systems, fuzzy inference methods, fuzzy and rough models, problem solving with equivalent transformation, genetic algorithms, reinforcement learning, non–monotonic reasoning, support vector machines, Hedge algebra, intelligent control, natural language understanding, self–organizing map learning, soft computing and data mining in medicine. As editors of this special issue, we would like to express our sincere gratitude to paper's authors in this issue. Our special thanks go to the anonymous referees for their excellent job, Ms. Kumiko Sato for her help in coordinating the publication of the issue, the Editorial Board of JACIII, especially Professor Kaoru Hirota for his great support and encouragement. Finally, we wish to thank Professors Hung T. Nguyen, Michio Sugeno and Pratit Santiprabhob for their help and contribution to InTech/VJFuzzy'2002. Without their support, the InTech/VJFuzzy'2002 and this issue would not be possible.

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