Variable Screening Optimization Algorithm for Mahalanobis-Taguchi System

Abstract

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.