Projection Pursuit Evaluation Model of Regional Surface Water Environment Based on Improved Chicken Swarm Optimization Algorithm

2017 ◽  
Vol 32 (4) ◽  
pp. 1325-1342 ◽  
Author(s):  
Dong Liu ◽  
Chunlei Liu ◽  
Qiang Fu ◽  
Tianxiao Li ◽  
Muhammad Imran Khan ◽  
...  
Keyword(s):  
Surface Water ◽  
Optimization Algorithm ◽  
Evaluation Model ◽  
Water Environment ◽  
Projection Pursuit ◽  
Swarm Optimization ◽  
Chicken Swarm Optimization

Spiral-based chaotic chicken swarm optimization algorithm for parameters identification of photovoltaic models

2021 ◽  
Vol 25 (20) ◽  
pp. 12875-12898
Author(s):  
Miao Li ◽  
Chunquan Li ◽  
Zhengyu Huang ◽  
Jiehui Huang ◽  
Gaige Wang ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Parameters Identification ◽  
Swarm Optimization ◽  
Chicken Swarm Optimization

scholarly journals Truss Structure Optimization Based on Improved Chicken Swarm Optimization Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Yancang Li ◽  
Shiwen Wang ◽  
Muxuan Han
Keyword(s):  
Optimization Algorithm ◽  
Optimization Design ◽  
Learning Strategy ◽  
Differential Evolution Algorithm ◽  
Structure Optimization ◽  
Weighting Factor ◽  
Truss Structure ◽  
Swarm Optimization ◽  
Learning Factor ◽  
Chicken Swarm Optimization

To improve the efficiency of the structural optimization design in truss calculation, an improved chicken swarm optimization algorithm was proposed for truss structure optimization. The chicken swarm optimization is a novel swarm intelligence algorithm. In the basic chicken swarm optimization algorithm, the concept of combining chaos strategy and reverse learning strategy was introduced in the initialization to ensure the global search ability. And the inertia weighting factor and the learning factor were introduced into the chick position update process, so as to better combine the global and local search. Finally, the overall individual position of the algorithm was optimized by the differential evolution algorithm. The improved algorithm was tested by multipeak function and applied to the truss simulation experiment. The study provided a new method for the truss structure optimization.

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