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基于神经网络和遗传算法的脱粒装置参数优化
Optimizing of threshing performance based on artificial neural network and genetic algorithm
【摘要】 在自制脱粒试验装置上,以未脱净率和谷粒损伤率为目标,进行了脱粒试验。通过MATLAB神经网络工具箱,建立了优化设计的数学模型。针对传统的优化方法存在求解过程复杂、寻优过程易陷入局部最优解的问题,应用MATLAB遗传算法工具箱对该模型进行了优化,求得了该脱粒试验装置脱粒元件线速度和脱粒间隙的最佳组合。提出了一条解决脱粒装置性能优化问题的新方法。同时,MATLAB神经网络和遗传算法工具箱的应用解决了其它高级语言繁重的编程任务。
【Abstract】 On a self-designed test equipment, The experiment of relationship between thresher’s velocities, concave clearance and threshing performance is conducted for paddy rice. The mathematical of the Threshing performance is built with artificial neural network based on experiments. The globe optimum solution is obtained by Matlab genetic algorithm toolbox. A new method for Optimizing of threshing performance is given. Besides, the programming work will be easy by using the Matlab artificial neural network toolbox and genetic algorithm toolbox for Optimizing of threshinperformance.
【Key words】 Agricultural equipment; Threshing performance; Optimizing; Artificial neural network; Genetic algorithm;
- 【文献出处】 机械设计与制造 ,Machinery Design & Manufacture , 编辑部邮箱 ,2008年02期
- 【分类号】S226.1
- 【被引频次】4
- 【下载频次】177