Open AccessVariable Screening Optimization Algorithm for Mahalanobis-Taguchi System
Author(s) -
Xiaohong Peng,
Rui Zheng,
Jiufu Liu
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2179/1/012036
Subject(s) - mahalanobis distance , taguchi methods , particle swarm optimization , metric (unit) , algorithm , orthogonalization , multi swarm optimization , mathematical optimization , variable (mathematics) , binary number , computer science , mathematics , artificial intelligence , engineering , machine learning , mathematical analysis , operations management , arithmetic
This paper proposes a Mahalanobis-Taguchi system variable screening optimization method based on binary quantum behavior particle swarm.The main procedures and methods are as follows, Firstly, the Mahalanobis distance value is calculated by the Gram-Schmidt orthogonalization method.We build the multi-objective mixed planning model. The binary quantum behavior particle swarm optimization algorithm is used to solve the optimal combination. A new prediction system based on Mahalanobis-Taguchi metric is established, and the task of accurate discrimination is accomplished.