2021
DOI: 10.1155/2021/8896794
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An Adaptive Fuzzy Chicken Swarm Optimization Algorithm

Abstract: The chicken swarm optimization (CSO) algorithm is a new swarm intelligence optimization (SIO) algorithm and has been widely used in many engineering domains. However, there are two apparent problems with the CSO algorithm, i.e., slow convergence speed and difficult to achieve global optimal solutions. Aiming at attacking these two problems of CSO, in this paper, we propose an adaptive fuzzy chicken swarm optimization (FCSO) algorithm. The proposed FCSO uses the fuzzy system to adaptively adjust the number of c… Show more

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Cited by 9 publications
(7 citation statements)
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“…(2) Some classic mathematical and physical theories have been used to enhance the performance of NIOAs, such as fuzzy theory [ 133 ], chaos theory [ 56 ] and quantum theory [ 48 , 132 ], and the exploration and exploitation abilities of NIOAs.…”
Section: Theoretical Comparison and Analysis Of The 11 Nioasmentioning
confidence: 99%
“…(2) Some classic mathematical and physical theories have been used to enhance the performance of NIOAs, such as fuzzy theory [ 133 ], chaos theory [ 56 ] and quantum theory [ 48 , 132 ], and the exploration and exploitation abilities of NIOAs.…”
Section: Theoretical Comparison and Analysis Of The 11 Nioasmentioning
confidence: 99%
“…The bio-inspired chicken swarm optimization (CSO) algorithm [23,24] is an advanced intelligent algorithm which represents the different behaviors related to chickens, hens and cocks in their process of food search. It is a random search algorithm that resembles the hierarchical structure and behaviour of the chicken swarm.…”
Section: Fuzzy Based Chicken Swarm Optimization (F-cso)mentioning
confidence: 99%
“…Next, the fuzzification technique is performed with the major sets of fuzzy value and membership functions of both systems inputs and outputs. Mamdani inference mechanism is used to identify relationships between input and output 26 , 27 .…”
Section: Fuzzy Controllermentioning
confidence: 99%
“…A mix of conventional and flexible procedures is developed and provided to effectively construct and get the robotic handler that tackles the difficulties of similarity between regular and Fuzzy logic methods. Depending on the input variables, the fuzzy logical control system has been designed with two inputs to identify the selection of input variables, which is a more single task 9 . The new fuzzy input PD and PI control error change and error control signals, with similar input variables by type PI, position, and speed controller type 10 13 .…”
Section: Introductionmentioning
confidence: 99%