Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Handbook of Granular Computing
Handbook of Granular Computing
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
Linguistic models and linguistic modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Linguistic models as a framework of user-centric system modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Genetically optimized fuzzy polynomial neural networks
IEEE Transactions on Fuzzy Systems
The Development of Incremental Models
IEEE Transactions on Fuzzy Systems
Conditional fuzzy clustering in the design of radial basis function neural networks
IEEE Transactions on Neural Networks
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In this paper, we present an optimization method of GN (Granular Network) based on evolutionary methods such as PSO (Particle Swarm optimization) and GA (Genetic Algorithm). The GN is constructed by linguistic model using CFCM (Context-based Fuzzy C-Means) clustering algorithm while forming a unified conceptual and computing platform of granular computing. This network performs relationship between fuzzy sets defined in the input and output space while building information granules, and accomplishes user-centric system. Here, the number of cluster obtained in each context and fuzzification factor are optimized by PSO and GA. Finally, we compare and analyze the predication performance between the presented networks and other models for coagulant dosing process in a water purification plant.