发明授权
US5404423A Method and apparatus for indetification, forecast, and control of a
non-linear flow on a physical system network using a neural network
失效
使用神经网络对物理系统网络上的非线性流进行独特,预测和控制的方法和装置
- 专利标题: Method and apparatus for indetification, forecast, and control of a non-linear flow on a physical system network using a neural network
- 专利标题(中): 使用神经网络对物理系统网络上的非线性流进行独特,预测和控制的方法和装置
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申请号: US48793申请日: 1993-04-16
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公开(公告)号: US5404423A公开(公告)日: 1995-04-04
- 发明人: Tadasu Uchiyama , Noboru Sonehara , Yukio Tokunaga
- 申请人: Tadasu Uchiyama , Noboru Sonehara , Yukio Tokunaga
- 申请人地址: JPX Tokyo
- 专利权人: Nippon Telegraph and Telephone Corporation
- 当前专利权人: Nippon Telegraph and Telephone Corporation
- 当前专利权人地址: JPX Tokyo
- 优先权: JPX4-156796 19920616; JPX4-279997 19921019
- 主分类号: G05B13/02
- IPC分类号: G05B13/02 ; G05B23/02 ; G06F15/18
摘要:
A neural network system for identifying forecasting, and controlling a non-linear flow on a physical system network, in which each branch between nodes in the physical system network is divided by a plurality of division points; a flow at each of the division points and a terminal point of each branch is calculated according to neural network model parameters specifying connections among the division points and the terminal point in a neural network model; an actual flow is measured at the terminal point of said each branch; an error of the calculated flow at the terminal point with respect to the measured actual flow at the terminal point is calculated; the neural network model parameters are adjusted to minimize the calculated error; and system dynamics parameters specifying dynamics of the physical system are determined according to the adjusted neural network model parameters. In addition, a target function to be optimized is calculated in terms of flows at terminal points of branches as a function of a control parameter specifying connecting and disconnecting of connections among branches at each node; and connections among branches at each node are connected/disconnected to optimize the calculated target function.
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