WO2006084151A3 - Identify data sources for neural network - Google Patents

Identify data sources for neural network Download PDF

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Publication number
WO2006084151A3
WO2006084151A3 PCT/US2006/003872 US2006003872W WO2006084151A3 WO 2006084151 A3 WO2006084151 A3 WO 2006084151A3 US 2006003872 W US2006003872 W US 2006003872W WO 2006084151 A3 WO2006084151 A3 WO 2006084151A3
Authority
WO
WIPO (PCT)
Prior art keywords
module
determining
measure
neural network
local
Prior art date
Application number
PCT/US2006/003872
Other languages
French (fr)
Other versions
WO2006084151A2 (en
Inventor
Dingguo Chen
Original Assignee
Siemens Power Transm & Distrib
Dingguo Chen
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens Power Transm & Distrib, Dingguo Chen filed Critical Siemens Power Transm & Distrib
Priority to EP06720242.4A priority Critical patent/EP1856657B8/en
Publication of WO2006084151A2 publication Critical patent/WO2006084151A2/en
Publication of WO2006084151A3 publication Critical patent/WO2006084151A3/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods

Abstract

A system, method, and device for identifying data sources for a neural network are disclosed. The exemplary system may have a module for determining load curves for each selected data set. The system may also have a module for determining a global difference measure and a global similarity measure for each load curve of each selected data set. The system may have a module for determining a set of data sets with lowest value global difference measure. The system may also have a module for determining a set of data sets with largest value global similarity measure. The system may also have a module for determining a union of the sets of lowest value difference measure and the sets of largest value similarity measure. The system may also have a module for determining for each set in the union one of a local similarity measure and a local difference measure and a module for selecting a set of reduced data sets based on one of the local similarity measure and the local difference measure
PCT/US2006/003872 2005-02-03 2006-02-02 Identify data sources for neural network WO2006084151A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP06720242.4A EP1856657B8 (en) 2005-02-03 2006-02-02 Identify data sources for neural network

Applications Claiming Priority (10)

Application Number Priority Date Filing Date Title
US64987605P 2005-02-03 2005-02-03
US64980305P 2005-02-03 2005-02-03
US64967705P 2005-02-03 2005-02-03
US64987705P 2005-02-03 2005-02-03
US60/649,877 2005-02-03
US60/649,677 2005-02-03
US60/649,876 2005-02-03
US60/649,803 2005-02-03
US11/345,438 US7403928B2 (en) 2005-02-03 2006-02-01 Identify data sources for neural network
US11/345,438 2006-02-01

Publications (2)

Publication Number Publication Date
WO2006084151A2 WO2006084151A2 (en) 2006-08-10
WO2006084151A3 true WO2006084151A3 (en) 2007-07-12

Family

ID=36694386

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2006/003872 WO2006084151A2 (en) 2005-02-03 2006-02-02 Identify data sources for neural network

Country Status (4)

Country Link
US (1) US7403928B2 (en)
EP (1) EP1856657B8 (en)
CN (1) CN103729679A (en)
WO (1) WO2006084151A2 (en)

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US7787995B2 (en) * 2006-03-07 2010-08-31 Siemens Energy, Inc. Method and system for controlling an operation of an electrical power network
TWI411975B (en) * 2008-11-06 2013-10-11 Ind Tech Res Inst Method of predicting level of customer amount, and method of controlling temperature of aircondiction by using the same
US8311680B2 (en) * 2008-12-26 2012-11-13 Industrial Technology Research Institute Method of determining demand threshold, and method and system of demand control
US8578507B2 (en) * 2009-09-09 2013-11-05 Varonis Systems, Inc. Access permissions entitlement review
US10474950B2 (en) 2015-06-29 2019-11-12 Microsoft Technology Licensing, Llc Training and operation of computational models
CN106127303A (en) * 2016-06-15 2016-11-16 国网山东省电力公司菏泽供电公司 A kind of short-term load forecasting method towards multi-source data
CN109389238B (en) * 2017-08-14 2022-08-09 中国电力科学研究院 Ridge regression-based short-term load prediction method and device
US10922584B2 (en) 2019-01-30 2021-02-16 Walmart Apollo, Llc Systems, methods, and techniques for training neural networks and utilizing the neural networks to detect non-compliant content
US10810726B2 (en) 2019-01-30 2020-10-20 Walmart Apollo, Llc Systems and methods for detecting content in images using neural network architectures
CN110377617B (en) * 2019-06-11 2024-02-02 中国平安财产保险股份有限公司 Data processing method, device, computer equipment and storage medium
US11758069B2 (en) 2020-01-27 2023-09-12 Walmart Apollo, Llc Systems and methods for identifying non-compliant images using neural network architectures

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EP1478073A2 (en) * 2003-05-13 2004-11-17 Siemens Power Transmission & Distribution, Inc. System for monitoring and maintaining the provision of electrical power

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US6397166B1 (en) * 1998-11-06 2002-05-28 International Business Machines Corporation Method and system for model-based clustering and signal-bearing medium for storing program of same
US20040133531A1 (en) * 2003-01-06 2004-07-08 Dingding Chen Neural network training data selection using memory reduced cluster analysis for field model development
EP1478073A2 (en) * 2003-05-13 2004-11-17 Siemens Power Transmission & Distribution, Inc. System for monitoring and maintaining the provision of electrical power

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Also Published As

Publication number Publication date
EP1856657B8 (en) 2017-04-05
EP1856657B1 (en) 2016-12-07
US7403928B2 (en) 2008-07-22
WO2006084151A2 (en) 2006-08-10
US20060184472A1 (en) 2006-08-17
EP1856657A2 (en) 2007-11-21
CN103729679A (en) 2014-04-16

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