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.

对于高温工作的服装设计，首先采用偏微分，非线性规划和有限差分法等理论或方法来构建“高温环境-服装-空气层-皮肤”的整体传热模型。并绘制温度分布图。其次，根据人体燃烧模型，初步获得织物厚度的最佳参数。最后，利用遗传算法对BP神经网络的权重和阈值进行了优化，并将这些优化后的值分配给优化后的BP神经网络，并利用MATLAB对非线性厚度函数进行了近似和优化。