threshing performance中文什么意思
脱净率
- thresh: vt.,vi. ＝ thrash. ...
- performance: n. 1.执行，实行，履行；完成；实 ...
- threshing: 打谷, 脱粒; 打叶; 脱谷; 脱粒 ...
例句与用法
更多例句： 下一页- At the same time , we give a neural network ' s topological structure , which will use to solve the concrete problem oriented to threshing performance modeling
同时针对脱粒装置性能建模这一具体问题，分析给出了用于对脱粒性能进行建模的基于ga - bp算法神经网络的实现。 - Seed - husking plant is the key unit of combine , whose improvement and perfection is mainly based on the nonlinear mathematical model of the threshing performance with its influencing factors
脱粒装置是联合收获机械的核心部件，它的改进与完善是以脱粒性能与其影响因素之间的非线性模型为基础的。 - Under the uncertain conditions , the purpose of setting up nonlinear mathematical model of the threshing performance with its influencing factors is to optimize all parameters of construction and motion so that we can get the optimum threshing performances
建立脱粒装置性能与其影响因素之间非线性模型的目的就是在不确定环境下，对影响脱粒性能的各因素进行优化使脱粒装置的各个性能指标达到最佳要求。 - In the process of threshing , the significance of factors , which influence threshing performance , not only include some certain factors such as feed quantity , cylinder rotary speed , distance between cylinder and concave , thresher concave radian but also include some uncertain factors such as the crop ' s variety , water content and the proportion of cereal straw . for this reason , the seed - husking plant is system with a character of uncertain , multi - input - output and complex nonlinear
脱粒装置的工作过程极为复杂，影响脱粒性能的因素很多，除了喂入量、滚筒转速、凹板长度与入口间隙等确定性因素外，还有作物品种、作物含水率以及谷草比等一些不确定性因素，因此脱粒装置是一个具有不确定性、多输入多输出的复杂非线性系统。 - In this paper , we first analyze each factor of influencing threshing performance , and deficiency of all traditional methods such as single factor , orthogonal experiment , variance analysis and regression analysis , which have been used to study the threshing performance . in the basis of above analysis , we propose a new method of threshing performance modeling - a bp neural network . by use the new ways of threshing performance modeling - a bp neural network , we can obtain the optimum model of threshing performance , which can better describe the seed - husking plant ' s feature of complex nonlinear , multi - input - output and indefinite
本文首先分析了影响脱粒装置性能的各个因素以及传统研究脱粒性能的各种方法如单因素法、正交试验法、方差分析法以及回归分析法的缺陷，在此基础上提出了采用bp神经网络对脱粒装置性能模型进行优化，采用这种方法优化脱粒装置性能模型可以更好地刻划脱粒装置所具有的多输入多输出、复杂非线性以及不确定性等特征。
