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An approximation algorithm for fuzzy polynomial interpolation with Artificial Bee Colony algorithm
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DOI：10.1016/j.asoc.2012.11.040.png)
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摘要
En 中文
In this paper, a novel approximation algorithm for fuzzy polynomial interpolation using Artificial Bee Colony algorithm to interpolate fuzzy data is discussed. However, we use our modified ABC (MABC; Mansouri et al. [13]) to perform the required task. Some examples (including the benchmark functions Griewank and Rastrigin) illustrate the rationality of the method and the validity of the solution. We compare our results with other methods including Genetic Algorithm (GA), Particle Swarm Algorithm (PSO). The results show that proposed method outperforms the other algorithms. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Fuzzy polynomial interpolation
Artificial Bee Colony algorithm
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期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
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