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Das, S., Chakraborty, D., Koczy, T.. (1401). (2205-7392) Forward and backward fuzzy rule base interpolation using fuzzy geometry. نشریه علمی دانشگاه سیستان و بلوچستان, (), -. doi: 10.22111/ijfs.2023.7400
S. Das; D. Chakraborty; T. Koczy. "(2205-7392) Forward and backward fuzzy rule base interpolation using fuzzy geometry". نشریه علمی دانشگاه سیستان و بلوچستان, , , 1401, -. doi: 10.22111/ijfs.2023.7400
Das, S., Chakraborty, D., Koczy, T.. (1401). '(2205-7392) Forward and backward fuzzy rule base interpolation using fuzzy geometry', نشریه علمی دانشگاه سیستان و بلوچستان, (), pp. -. doi: 10.22111/ijfs.2023.7400
Das, S., Chakraborty, D., Koczy, T.. (2205-7392) Forward and backward fuzzy rule base interpolation using fuzzy geometry. نشریه علمی دانشگاه سیستان و بلوچستان, 1401; (): -. doi: 10.22111/ijfs.2023.7400

(2205-7392) Forward and backward fuzzy rule base interpolation using fuzzy geometry

Iranian Journal of Fuzzy Systems
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 17 بهمن 1401  XML اصل مقاله (343.64 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/ijfs.2023.7400
نویسندگان
S. Das* 1؛ D. Chakraborty2؛ T. Koczy3
1School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore
2Department of Mathematics, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India
3Department of Information Technology, Sz'echenyi Istv'an University, Gyor, Hungary
چکیده
Fuzzy rule interpolation (FRI) predicts an accountable outcome of a possible course of action in sparse fuzzy rule base system (FRBS). The geometry based linear fuzzy rule interpolation (GLFRI) is extended for multi-dimensional fuzzy rule base interpolation. Expansion/contraction (EC) of triangular, trapezoidal and complex polygonal fuzzy sets has been also proposed which enables the proposed FRI method to incorporate with fuzzy rules which include triangular, trapezoidal, hexagonal or complex fuzzy sets. The study further extends to introduce the process of backward rule base interpolation.
It has been shown that the scale and move transformation-based FRI method can yield a non-convex fuzzy consequent which can be avoided by using the proposed method. The proposed method performs better without any risk of obtaining non-convex fuzzy consequent. The efficiency of proposed forward and backward FRI methods is projected with several numerical examples. A detailed comparison of EC transformation with scale and move transformation is also presented here.
کلیدواژه‌ها
Inverse rule base interpolation؛ scale and move transformation؛ transformation of fuzzy point؛ translation of fuzzy number؛ multi-dimensional rule base interpolation
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تعداد مشاهده مقاله: 26
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