A Design and Optimization of a CGK-Based Fuzzy Granular Model Based on the Generation of Rational Information Granules
Source abstract
Abstract
This study proposes an optimized context-based Gustafson Kessel (CGK)-based fuzzy granular model based on the generation of rational information granules and an optimized CGK-based fuzzy granular model with the aggregated structure. The conventional context-based fuzzy-c-means (CFCM) clustering generates clusters considering the input and output spaces. However, the prediction performance decreases when the specific data points with geometric features are used. The CGK clustering solves the above situation by generating valid clusters considering the geometric attributes of data in input and output spaces with the aid of the Mahalanobis distance. However, it is necessary to generate rational information granules (IGs) because there is a significant change in performance according to the context generated in the output space and the shape, size, and several clusters generated in the input space. As a result, the rational IGs are obtained by considering the relationship between the coverage and specificity of IG using the genetic algorithm (GA). Thus, the optimized CGK-based fuzzy granular models with the aggregated structure are designed based on rational IGs. The prediction performance was compared using the two databases to verify the validity of the proposed method. Finally, the experiments revealed that the performance of the proposed method is higher than that of the previous model.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Clustering Algorithms Research · Rough Sets and Fuzzy Logic · Text and Document Classification Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Center for IT-Bio Convergence System Agriculture, Chonnam University, Gwangju 61186, Korea
Department of Electronics Engineering IT-Bio Convergence System, Chosun University, Gwangju 61452, Korea
Funding
Chosun University
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