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The Study of Fuzzy Neural Networks in Train Section Following Space Interval Model under MAS

机译：MAS下空间区间模型的列车区间模糊神经网络研究

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Train tracing space interval model system is the base of train dynamic run space control system. Owing to the uncertainly factors in the train run process, the math model based on draught account is difficult to satisfy the need of the practical system. Combining the characteristics of train dynamic run in MAS, this paper proposes a new train section tracing space interval model—based on neural networks and fuzzy control, whose name is the Multi-Input fuzzy neural network model. At last the paper point out its practical meaning and also proves the designed system's practicability by the simulation.

机译：列车跟踪空间间隔模型系统是列车动态运行空间控制系统的基础。由于列车运行过程中存在不确定因素，基于草稿账的数学模型难以满足实际系统的需要。结合MAS中列车动态运行的特点，提出了一种新的基于神经网络和模糊控制的列车区间跟踪空间区间模型，即多输入模糊神经网络模型。最后指出了其实用意义，并通过仿真验证了所设计系统的实用性。

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来源
《》|2005年|P.1244-1247|共4页
会议地点 Beijing(CN)
作者
Hai-wangYI; Hua-shen WANG; Xia LI;
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作者单位

Beijiing Jiaotong University, Beijing 100044, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类无线通信;
关键词
MAS; fuzzy neural networks; tracing interval model; simulation;

机译：MAS；模糊神经网络；跟踪间隔模型；仿真;

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The Study of Fuzzy Neural Networks in Train Section Following Space Interval Model under MAS

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