By Xiaolei Wang, Xiao-Zhi Gao, Kai Zenger
This short presents a close creation, dialogue and bibliographic overview of the nature1-inspired optimization set of rules referred to as concord seek. It makes use of numerous simulation effects to illustrate some great benefits of concord seek and its variations and likewise their drawbacks. The authors convey how weaknesses might be amended via hybridization with different optimization equipment. The concord seek approach with purposes may be of price to researchers in computational intelligence in demonstrating the cutting-edge of study on an set of rules of present curiosity. It additionally is helping researchers and practitioners of electric and laptop engineering extra quite often in acquainting themselves with this system of vector-based optimization.
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Extra info for An Introduction to Harmony Search Optimization Method
L; L is the number of fuzzy rules, m ¼ 1; . ; M; M is the number of data classes, n is the number of input variables, and Alj ðj ¼ 1; 2; . ; nÞ is a fuzzy Â Ã set associated with feature variable xj : Here, vector X ¼ x1; x2 ; . ; xn in the antecedent part consists of the input variables, and Cm in the consequent part is the class label. We only consider the asymmetric triangular membership function for those input variables: x À a c À x ; lðx; a; b; cÞ ¼ max 0; min ; bÀa cÀb ð5:38Þ 52 5 The Hybrid Strategies of Harmony Search… where a; b; and c are the adaptive membership function parameters.
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