基于BP神经网络的马铃薯收获机挖掘铲的参数优化

Parameters optimization of potato harvester digger blade based on BP neural network

以马铃薯收获机的挖净率和伤薯率为目标,对挖掘铲的主要参数进行试验。在试验数据的基础上建立BP神经网络的数学模型,应用MATLAB神经网络工具箱对该模型进行优化,得出挖掘铲主要参数的最佳组合,从而为解决挖掘铲的性能优化问题提供了一种新方法。

It is a target with digging net rate and injury rate of potato harvester, in order to test the main parameters of digging blade. The mathematical model is built with BP neural network based on experiment, and by using the MATLAB artificial network toolbox for optimizing of the model, so the main parameters of digging blade obtained the best combination.Besides,a new method for optimizing of digger blade is given.