Genetic Algorithm to Optimize the Design of High Temperature Protective Clothing Based on BP Neural Network

For the clothing design for high-temperature operation, the theory or method such as partial differential, nonlinear programming and finite difference method was first applied to construct the overall heat transfer model of "high temperature environment--clothing--air layer--skin" and draw the temperature distribution map. Secondly, according to the human body burn model, the optimal parameters of fabric thickness are obtained preliminarily. Finally, the weights and thresholds of BP neural network were optimized by genetic algorithm, and these optimized values were assigned to the optimized BP neural network, and the nonlinear thickness function was approximated and optimized with MATLAB.