混合教与学算法在空间直线度评定中的应用

doi:10.3969/j.issn.1000-1158.2018.01.04

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Abstract In order to improve the accuracy of spatial straightness evaluation under minimum zone principle condition, a method of spatial straightness error evaluation based on teaching-learning-based optimization(TLBO) algorithm is proposed. To increases the ability of information interaction between students and local search , the population grouping strategy, shuffle strategy and local update strategy of shuffled frog leaping algorithm are used in teaching-learning-based algorithm and it is called hybrid teaching-learning-based optimization(HTLBO) algorithm. Finally, two groups of spatial straightness error examples are used by HTLBO algorithm, and the results are compared to other traditional algorithms . The results show that the HTLBO algorithm has high searching ability and fast convergence speed in the process of spatial straightness error evaluation.

Key words： metrology HTLBO spatial straightness error evaluation minimum zone principle shuffled frog leaping algorithm

Received: 24 February 2017 Published: 29 December 2017

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TB92

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	Articles by authors
	YANG Yang
	LI Ming
	GU Jing-jun
	WANG Chen
	WEI Qing-yue

Cite this article:

YANG Yang,LI Ming,GU Jing-jun, et al. Application of Hybrid Teaching-learning-based Optimization Algorithm in Spatial Straightness Evaluation[J]. Acta Metrologica Sinica, 2018, 39(1): 15-19.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2018.01.04 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2018/V39/I1/15

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