多种群遗传算法在篦冷机二次风温预测中的应用

doi:10.3969/j.issn.1000-1158.2019.02.13

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Abstract Aiming at the problem of poor diversity and poor local optimization ability of the genetic algorithm, a multi-population genetic algorithm (MGA) was proposed. According to the theory of Punctuated Equilibria, the algorithm took the manipulation of multiple populations, and multiple crossover operators. Meanwhile, the MGA algorithm had also composed of the local search method and population dynamics adjustment strategy to improve the local search ability and speed. Compared with GA and ISGA algorithms, MGA running time is short and has a better optimization performance. Finally, the MGA algorithm was applied to optimize the multi-kernal least square vector mechaine(MKLSSVM) parameters. And then established the secondary air temperature model of the cement grate cooler based on MGA-MKLSSVM. The results show that this model has high recognition precision and strong generalization ability.

Key words： metrology multi-population genetic algorithm secondary air temperature multiple crossover operators local search grate coller

Received: 11 September 2017 Published: 07 March 2019

PACS:	TB94
	TB973

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	Articles by authors
	LIU Bin
	ZHANG Chun-ran
	SUN Chao
	GU Xin-feng
	LIU Hao-ran

Cite this article:

LIU Bin,ZHANG Chun-ran,SUN Chao, et al. The Application of Multi-population Genetic Algorithm in Secondary Air Temperature of Grate Cooler[J]. Acta Metrologica Sinica, 2019, 40(2): 252-258.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2019.02.13 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2019/V40/I2/252

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