International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
A genetic algorithm for optimizing Takagi-Sugeno fuzzy rule bases
Fuzzy Sets and Systems
Computers and Operations Research
A Handwritten Numeral Character Classification Using Tolerant Rough Set
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Three objective genetics-based machine learning for linguisitc rule extraction
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Neural Network Training Using Genetic Algorithms
Neural Network Training Using Genetic Algorithms
Genetic Algorithms: Concepts and Designs with Disk
Genetic Algorithms: Concepts and Designs with Disk
Using the analytic network process (ANP) in a SWOT analysis - A case study for a textile firm
Information Sciences: an International Journal
Evaluating digital video recorder systems using analytic hierarchy and analytic network processes
Information Sciences: an International Journal
Genetic algorithms for determining fuzzy measures from data
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Information Sciences: an International Journal
Computers and Industrial Engineering
Hybridization of fuzzy GBML approaches for pattern classification problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Information Sciences: an International Journal
A linear programming approximation to the eigenvector method in the analytic hierarchy process
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
GPSO versus GA in facial emotion detection
International Journal of Artificial Intelligence and Soft Computing
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The analytic network process (ANP) is a useful technique for multi-attribute decision analysis (MCDA) that employs a network representation to describe interrelationships between diverse attributes. Owing to effectiveness of the ANP in allowing for complex interrelationships between attributes, this paper develops an ANP-based classifier for pattern classification problems with interdependence or independence among attributes. To deal with interdependence, this study employs genetic algorithms (GAs) to automatically determine elements in the supermatrix that are not easily user-specified, to find degrees of importance of respective attributes. Then, with the relative importance for each attribute in the limiting supermatrix, the current work determines the class label of a pattern by its synthetic evaluation. Experimental results obtained by the proposed ANP-based classifier are comparable to those obtained by other fuzzy or non-fuzzy classification methods.