发明申请
US20140143189A1 ON-DEMAND POWER CONTROL SYSTEM, ON-DEMAND POWER CONTROL SYSTEM PROGRAM, AND COMPUTER-READABLE RECORDING MEDIUM RECORDING THE SAME PROGRAM
审中-公开
需求功率控制系统,需求功率控制系统程序以及记录相同程序的计算机可读记录介质
- 专利标题: ON-DEMAND POWER CONTROL SYSTEM, ON-DEMAND POWER CONTROL SYSTEM PROGRAM, AND COMPUTER-READABLE RECORDING MEDIUM RECORDING THE SAME PROGRAM
- 专利标题(中): 需求功率控制系统,需求功率控制系统程序以及记录相同程序的计算机可读记录介质
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申请号: US14131722申请日: 2012-07-13
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公开(公告)号: US20140143189A1公开(公告)日: 2014-05-22
- 发明人: Takashi Matsuyama , Takekazu Kato , Yusuke Yamada
- 申请人: Takashi Matsuyama , Takekazu Kato , Yusuke Yamada
- 申请人地址: JP Ibaraki-shi, Osaka
- 专利权人: NITTO DENKO CORPORATION
- 当前专利权人: NITTO DENKO CORPORATION
- 当前专利权人地址: JP Ibaraki-shi, Osaka
- 优先权: JP2011-154494 20110713
- 国际申请: PCT/JP2012/068002 WO 20120713
- 主分类号: G06N5/04
- IPC分类号: G06N5/04 ; G06N99/00
摘要:
In order to estimate behavior of a person at home from a feature and a power consumption pattern of an electrical device, an on-demand power control system of the present invention includes initial human-induced probability value estimation means that estimates a state of the electrical device, and estimates an initial value of a human-induced probability of the electrical device based on the estimated state of the electrical device, human position estimation means for calling up the initial value of the human-induced probability of the electrical device and a likelihood map of this device from a memory, performing, for all samples, a process of referring to a sample human position selected from the likelihood map and calculating a weight of the device by multiplying a human position and the human-induced probability of the device, and estimating a probability of a human position at each time point until a final time; and human-induced probability re-estimation means for performing recalculation of the human-induced probability based on the human-induced probability and a human position probability, performing the recalculation of the human-induced probability until a value of the recalculation converges, and outputting the human-induced probability and the human position probability when the value converges.
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