… This study proposes a modified differential evolution (MODE) for an ANFN (ANFN-MODE).
The proposed MODE learning algorithm has two crucial ideas. First, MODE adopts a method …

… In this paper we have proposed a scheme based on differential evolution for multiple … , still
2-D histogram based approaches and fuzzy, rough set theory based approaches could also …

… model called the Fuzzy Clustering Chaotic-based Differential Evolution for solving multiple
… Fuzzy Clustering Chaotic-based Differential Evolution (FCDE) algorithm integrates fuzzy c-…

… The quality of the final fuzzy clusters depends heavily on … fuzzy C-means algorithm in which
a validity index based on the concepts of maximum fuzzy energy and minimum fuzzy entropy …

… The hybrid method combines the BBO algorithm with differential evolution, to avoid premature
convergence. Kim et al. [27] employed the BBO algorithm to optimize job scheduling in …

… In this paper, we propose a multiobjective differential evolution (MODE)-based feature …
on advances in intelligent systems, fuzzy systems, evolutionary computation, pp 293–298 …

… using synergetic differential evolution (SDE), an advanced version of differential evolution
(… It utilizes two criteria (1) entropy and (2) approximation of normalized histogram of an image …

… It is much less than traditional fuzzy model with 81 rules in … fuzzy model are optimally
identified with differential evolution … fuzzy model are optimally identified with differential evolution …

… matched filter response that maximize the fuzzy entropy are considered to be the optimal …
Differential Evolution algorithm is used to specify the optimal combination of the fuzzy …

… In the present study, only the index of fuzzy entropy was selected as the feature in the
classification, yielding a detection accuracy of up to 98%. From the point of computational efficiency…