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CCEO: cultural cognitive evolution optimization algorithm
Faculty
Computer Science
Year:
2019
Type of Publication:
ZU Hosted
Pages:
Authors:
Mohammed Abdel Basset Metwally Attia
Staff Zu Site
Abstract In Staff Site
Journal:
Soft Computing Springer
Volume:
Keywords :
CCEO: cultural cognitive evolution optimization algorithm
Abstract:
Cognitive behavior is an indispensable factor in the history of human evolution; through cognitive behavior, human development has evolved from the Stone Age to the present high-tech information era. By simulating the process of cultural evolution, a cultural algorithm can reflect the evolutionary process of society accurately, which can speed up the process of solving problems. In this paper, cognitive behavior evolution and a cultural algorithm are combined to form the cultural cognitive evolution optimization (CCEO) algorithm. A cultural algorithm with the double-layer structure of the belief space and population space is transformed into a three-layer evolution mechanism in a CCEO so that the belief space improves on the next layer of careful guidance of the evolutionary process. Twenty-three benchmark test functions and two engineering problems were used to test the CCEO algorithm, and the results demonstrate that the culture cognitive evolution algorithm has a high convergence speed and calculation precision.
Author Related Publications
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Department Related Publications
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Saber Mohamed, "Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization", ELSEVEIR, 2015
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Saber Mohamed, "An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems", IEEE, 2013
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Saber Mohamed, "Differential Evolution with Dynamic Parameters Selection for Optimization Problems", IEEE, 2014
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