Optimal angle of polycrystalline silicon solar panels placed in a building using the ant colony optimization algorithm

Saouane, I.; Chaker, Abla; Zaidi, B.; Shekhar, Chander

doi:10.1140/epjp/i2017-11381-4

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…(3) Until: Procedure 8: determine the objective function (i.e., fitness function) [15] to determine the convergence conditions max T h…”

Section: Cma-es Algorithmmentioning

confidence: 99%

Simulation Research on the Palm Mechanism of Volleyball Robot Based on Artificial Intelligence and Ant Colony Optimization Algorithm

Jiao

2022

Security and Communication Networks

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The study of mobile robots, which began in the late 1960s, is the most dramatic development in human history in the twentieth century, and the invention has undergone radical changes in just over 50 years. The robot body is developing in the direction of flexibility and miniaturization. This is because the robot application is mostly oriented to the family and service industries, and it needs to adapt to a more complex environment. This manuscript aims to improve further the ant colony optimization algorithm by using rough set theory to improve the convergence speed and accuracy of the algorithm in robot path planning on the basis of an in-depth diagnosis on the shortcomings and its causes of development of the ant colony optimization algorithm. It overcomes the drawbacks of the algorithm that easily get trapped in partial optimality solution, the search time is much slower and the search effect is not good. In this paper, the CMA-ES algorithm, the modified ant colony, and the BK method are proposed, which have high theoretical value and exploration significance. In addition, simulation experiments are conducted to obtain the stage results on the basis of artificial information. The results of the present paper indicate the GWO algorithm performs more stable in the optimization results of each experiment when there are 14 robots and the communication range is 1.6, compared with the PSO algorithm and BA algorithm.

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“…(3) Until: Procedure 8: determine the objective function (i.e., fitness function) [15] to determine the convergence conditions max T h…”

Section: Cma-es Algorithmmentioning

confidence: 99%

Simulation Research on the Palm Mechanism of Volleyball Robot Based on Artificial Intelligence and Ant Colony Optimization Algorithm

Jiao

2022

Security and Communication Networks

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“…These perovskite solar cells employ organic-inorganic metal halide based hybrids as the medium to absorb electromagnetic radiation. Due to low input material costs, high cell efficiency and inexpensive fabrication methods, these organicinorganic metal halide based hybrids are considered promising materials for solar cell applications [8,9]. Lead or tin halide based material, which crystallizes in the perovskite structure, is used as a light-harvesting active layer in perovskite solar cells [10].…”

Section: Introductionmentioning

confidence: 99%