基于神经网络遗传算法的木薯秸秆切割优化设计

Optimization Design of Cassava Straw Cutting Based on Neural Network and Genetic Algorithm

选取木薯秸秆切割试验中的切割角度、切割速度、切割部位、木薯直径等控制变量及相关响应变量,通过非线性回归模型和BP神经网络模型进行拟合,分别研究响应变量与控制变量之间的作用机理;对模型进行对比,优化响应变量的作用机理。

Based on the data of controlled variables including the cutting angle,cutting speed,cutting position,object diameter and response variables,this paper studied the mechanism of action between the response variable and those controlled variables respectively by using of nonlinear regression and BP neural network model. It also gives optimal action mechanism of optimizing response variable by comparing the effects of two models.