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(2302-7893) Improving the genetic algorithm in fuzzy cluster analysis for numerical data and its applications | ||
| Iranian Journal of Fuzzy Systems | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 13 شهریور 1402 اصل مقاله (896.66 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2023.7834 | ||
| نویسندگان | ||
| D. Pham Toan1؛ T. Vo Van* 2 | ||
| 1Faculty of Mechanical - Electrical and Computer Engineering, School of Technology, Van Lang University, Ho Chi Minh City, Vietnam | ||
| 2College of Natural Science, Can Tho University, Can Tho City, Vietnam | ||
| چکیده | ||
| This study proposes an automatic genetic algorithm in fuzzy cluster analysis for numerical data. In this algorithm, a new measure called the FB index is used as the objective function of the genetic algorithm. In addition, the algorithm not only determines the appropriate number of groups but also improves the steps of traditional genetic algorithm as crossover, mutation and selection operators. The proposed algorithm is shown the step by step throughout the numerical example, and can perform fast by the established Matlab procedure. The result from experiments show the superiority of the proposed algorithm when it overcomes the existing algorithms. Moreover, it has been applied in recognizing the image data, and building the fuzzy time series model. These show the potential of this study for many real applications of the different fields. | ||
| کلیدواژه‌ها | ||
| Fuzzy clustering؛ genetic algorithm؛ image recognition؛ time series | ||
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آمار تعداد مشاهده مقاله: 35 تعداد دریافت فایل اصل مقاله: 40 |
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