发明授权
- 专利标题： Systems and methods for utilizing machine learning to identify non-technical loss
-
申请号： US16376976申请日： 2019-04-05
-
公开(公告)号： US11449315B2公开(公告)日： 2022-09-20
- 发明人: Thomas M. Siebel , Edward Y. Abbo , Houman Behzadi , Avid Boustani , Nikhil Krishnan , Kuenley Chiu , Henrik Ohlsson , Louis Poirier , Zico Kolter
- 申请人： C3.ai, Inc.
- 申请人地址： US CA Redwood City
- 专利权人： C3.ai, Inc.
- 当前专利权人： C3.ai, Inc.
- 当前专利权人地址： US CA Redwood City
- 代理机构： Wilson Sonsini Goodrich & Rosati
- 主分类号： G06N20/00
- IPC分类号： G06N20/00 ; G06F8/34 ; H04W52/04 ; H04B17/391 ; G06Q50/06 ; G01R21/00
摘要：
Various embodiments of the present disclosure can include systems, methods, and non-transitory computer readable media configured to select a set of signals relating to a plurality of energy usage conditions. Signal values for the set of signals can be determined. Machine learning can be applied to the signal values to identify energy usage conditions associated with non-technical loss.
公开/授权文献
信息查询
