拆分组 meaning in English
depacketizing
Examples
- A decision tree is composed of a series of splits , with the most important split , as determined by the algorithm , at the left of the viewer in the
决策树由一系列拆分组成，最重要的拆分由算法确定，位于 - An " entity transaction " is a transaction transferring control of an organization , or substantially all assets of one , or subdividing an organization , or merging organizations
“实体事务”指转移一个组织的控制权或全部资产，或者拆分组织，或者合并组织的事务。 - This article puts forward a solution named divide - assemble by deducing the size of bp neural network to overcome entering the local best point , the dividing process is that a big bp neural network is divided into several small bp neural networks , every small bp neural network can study alone , after all small bp neural networks finish their study , we can assemble all these small bp neural networks into the quondam big bp neural networks ; on the basis of divide - assemble solution , this article discusses the preprocessing of input species and how to deduce the size of bp neural network further to make it easy to overcome entering the local best point ; for the study of every small bp neural network , this article adopts a solution named gdr - ga algorithm , which includes two algorithms . gdr ? a algorithm makes the merits of the two algorithms makeup each other to increase searching speed . finally , this article discusses the processing of atm band - width distribution dynamically
本文从bp网的结构出发，以减小bp神经网络的规模为手段来克服陷入局部极小点，提出了bp神经网络的拆分组装方法，即将一个大的bp网有机地拆分为几个小的子bp网，每个子网的权值单独训练，训练好以后，再将每个子网的单元和权值有机地组装成原先的bp网，从理论和实验上证明了该方法在解决局部极小值这一问题时是有效的；在拆分组装方法基础上，本文详细阐述了输入样本的预处理过程，更进一步地减小了bp网络的规模，使子网的学习更加容易了；对于子网的学习，本文采用了最速梯度? ?遗传混合算法(即gdr ? ? ga算法) ，使gdr算法和ga算法的优点互为补充，提高了收敛速度；最后本文阐述了用以上方法进行atm带宽动态分配的过程。 - The paper includes the contents as follows : the second chapter introduces the basic theory of bp neural network , chapter 3 puts forward a solution named divide - assemble , chapter 4 introduces the preprocessing of input population , chapter 5 introduces the basic theory of genetic algorithms , chapter 6 discusses gdr - ga algorithms , 7 part introduces the processing of atm band - width distribution dynamically and gives several program modules among them . chapter 8 introduces the interface , running and results about the software system , the last chapter summarizes research work of this dissertation and further researches arc prospected
本文主要包括以下内容：第2部分阐述bp神经网络基本理论，第3部分介绍了拆分组装方法，第4部分主要介绍了bp神经网络输入样本的预处理，第5部分介绍了遗传算法的发展及其基本理论，第6章介绍的是最速梯度? ?遗传算法，第7部分介绍了atm带宽动态分配过程、子网与总网的学习过程和其中的一些关键程序模块，第8部分介绍的是该系统界面和运行情况，最后一部分总结了论文所做的工作和进一步工作设想。