棉纺织技术2024，Vol.52Issue(6)：1-7,7.
基于粒子群遗传算法的纱线生产过程参数反演
Yarn production parameter inversion based on particle swarm genetic algorithm
摘要
Abstract
In order to solve the problems of slow convergence and low precision in the traditional forward and inversion models of yarn quality,and the defect of local extremum in standard particle swarm optimization algorithm,a particle swarm genetic hybrid algorithm was proposed.The algorithm was used to optimize the weights and thresholds of BP neural network and establish the forward yarn evenness model.On this basis,the inverse model of particle swarm genetic algorithm was constructed based on the CV value of yarn evenness.Historical production data was used to inverse production parameters.The results showed that the average relative error of the inversion results of each production parameter was kept below 4%.It is considered that the inversion method is feasible and accurate.关键词
粒子群算法/遗传算法/生产过程参数反演/纱线条干/BP神经网络Key words
particle swarm optimization/genetic algorithm/production parameter inversion/yarn evenness/BP neural network分类
轻工业引用本文复制引用
梁棋,张立杰..基于粒子群遗传算法的纱线生产过程参数反演[J].棉纺织技术,2024,52(6):1-7,7.基金项目
新疆维吾尔自治区科技重大专项(2022A01008-1) （2022A01008-1）
