DE60217663D1 - Verbesserte künstliche neuronalnetzmodelle in der anwesenheit von instrumentengeräuschen und messfehlern - Google Patents

Verbesserte künstliche neuronalnetzmodelle in der anwesenheit von instrumentengeräuschen und messfehlern

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Publication number
DE60217663D1
DE60217663D1 DE60217663T DE60217663T DE60217663D1 DE 60217663 D1 DE60217663 D1 DE 60217663D1 DE 60217663 T DE60217663 T DE 60217663T DE 60217663 T DE60217663 T DE 60217663T DE 60217663 D1 DE60217663 D1 DE 60217663D1
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DE
Germany
Prior art keywords
measurement errors
network models
neuronal network
improved artificial
instrument noise
Prior art date
Legal status (The legal status 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 status listed.)
Expired - Lifetime
Application number
DE60217663T
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English (en)
Other versions
DE60217663T2 (de
Inventor
Dattatray Kulkarni
Shrikrishna Tambe
Budhaji Lonari
Neelamkumar Valecha
Vasantrao Dheshmukh
Bhavanishankar Shenoy
Sivaraman Ravichandran
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Council of Scientific and Industrial Research CSIR
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Council of Scientific and Industrial Research CSIR
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Publication of DE60217663D1 publication Critical patent/DE60217663D1/de
Application granted granted Critical
Publication of DE60217663T2 publication Critical patent/DE60217663T2/de
Anticipated expiration legal-status Critical
Expired - Lifetime legal-status Critical Current

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/086Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/084Backpropagation, e.g. using gradient descent

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computing Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • General Engineering & Computer Science (AREA)
  • Biophysics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Physiology (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Complex Calculations (AREA)
DE60217663T 2002-03-26 2002-03-26 Verbesserte künstliche neuronalnetzmodelle in der anwesenheit von instrumentengeräuschen und messfehlern Expired - Lifetime DE60217663T2 (de)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/IB2002/001147 WO2003081527A1 (en) 2002-03-26 2002-03-26 Improved performance of artificial neural network models in the presence of instrumental noise and measurement errors

Publications (2)

Publication Number Publication Date
DE60217663D1 true DE60217663D1 (de) 2007-03-08
DE60217663T2 DE60217663T2 (de) 2007-11-22

Family

ID=28053165

Family Applications (1)

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DE60217663T Expired - Lifetime DE60217663T2 (de) 2002-03-26 2002-03-26 Verbesserte künstliche neuronalnetzmodelle in der anwesenheit von instrumentengeräuschen und messfehlern

Country Status (7)

Country Link
EP (1) EP1382012B1 (de)
JP (1) JP4157477B2 (de)
KR (1) KR100869516B1 (de)
CN (1) CN100520817C (de)
AU (1) AU2002247918A1 (de)
DE (1) DE60217663T2 (de)
WO (1) WO2003081527A1 (de)

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US7840287B2 (en) * 2006-04-13 2010-11-23 Fisher-Rosemount Systems, Inc. Robust process model identification in model based control techniques
CN103324085B (zh) * 2013-06-09 2016-03-02 中国科学院自动化研究所 基于监督式强化学习的最优控制方法
CN104347066B (zh) * 2013-08-09 2019-11-12 上海掌门科技有限公司 基于深层神经网络的婴儿啼哭声识别方法及系统
WO2016025887A2 (en) * 2014-08-14 2016-02-18 University Of North Dakota Flight parameter prediction using neural networks
CN106019359A (zh) * 2016-05-17 2016-10-12 浪潮集团有限公司 一种基于神经网络的地震预测系统
US10558204B2 (en) * 2016-09-19 2020-02-11 Palo Alto Research Center Incorporated System and method for scalable real-time micro-object position control with the aid of a digital computer
CN108108506B (zh) * 2016-11-24 2021-05-14 南方电网科学研究院有限责任公司 一种多端直流工程主回路参数的优化方法
KR101877161B1 (ko) * 2017-01-09 2018-07-10 포항공과대학교 산학협력단 문서 문맥정보를 고려하는 상황기반 추천 방법 및 장치
US10997492B2 (en) 2017-01-20 2021-05-04 Nvidia Corporation Automated methods for conversions to a lower precision data format
US10832135B2 (en) * 2017-02-10 2020-11-10 Samsung Electronics Co., Ltd. Automatic thresholds for neural network pruning and retraining
CN107007279B (zh) * 2017-03-17 2019-11-05 浙江大学 一种基于堆栈式自编码器的无创心内异常激动点定位方法
CN107389732B (zh) * 2017-07-14 2019-08-27 中国计量大学 一种激光扫描热成像裂纹检测方法
CN108104807A (zh) * 2017-12-16 2018-06-01 中国石油大学(华东) 一种海洋油气资源勘探系统及其使用方法
CN110162807B (zh) * 2018-02-12 2023-09-12 沈阳理工大学 基于改进蚁群优化bp神经网络弹药贮存可靠性评估方法
CN110222834B (zh) * 2018-12-27 2023-12-19 杭州环形智能科技有限公司 一种基于噪声遮蔽的发散式人工智能记忆模型系统
SG10201900755WA (en) * 2019-01-28 2020-08-28 Wilmar International Ltd Methods and system for processing lipid contents of at least one oil sample and simulating at least one training sample, and for predicting a blending formula, amongst others
CN110006664A (zh) * 2019-04-03 2019-07-12 上海好耐电子科技有限公司 基于神经网络的汽车制动噪声专家检测方法
CN110942144B (zh) * 2019-12-05 2023-05-02 深圳牛图科技有限公司 集自动化训练、校验、重构于一体的神经网络构建方法
CN111030180B (zh) * 2019-12-26 2023-08-25 河南牧业经济学院 基于无线传感器网络的双馈风电机组风能集成控制方法
CN111160667B (zh) * 2020-01-02 2023-05-30 北京工商大学 一种提高食品安全预测模型鲁棒性的方法及装置
KR102648937B1 (ko) * 2020-09-14 2024-03-20 한국전력공사 전력망 상태예측 모델 성능 관리 장치 및 방법
US11893327B2 (en) 2020-12-14 2024-02-06 Xerox Corporation System and method for machine-learning enabled micro-assembly control with the aid of a digital computer
US11921488B2 (en) 2020-12-15 2024-03-05 Xerox Corporation System and method for machine-learning-enabled micro-object density distribution control with the aid of a digital computer
CN113243915A (zh) * 2021-05-10 2021-08-13 西北工业大学 一种基于音频注入的烦恼感抑制定量评价方法

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WO1992007325A1 (en) * 1990-10-15 1992-04-30 E.I. Du Pont De Nemours And Company Apparatus and method for on-line prediction of unmeasurable process information
JPH04262453A (ja) 1991-02-15 1992-09-17 Hitachi Ltd ニュ−ロ学習制御方法及び装置
US5412256A (en) * 1994-01-06 1995-05-02 Bell Communications Research, Inc. Neuron for use in self-learning neural network

Also Published As

Publication number Publication date
EP1382012B1 (de) 2007-01-17
CN1571982A (zh) 2005-01-26
JP4157477B2 (ja) 2008-10-01
AU2002247918A1 (en) 2003-10-08
KR100869516B1 (ko) 2008-11-19
EP1382012A1 (de) 2004-01-21
JP2005521167A (ja) 2005-07-14
KR20040099092A (ko) 2004-11-26
WO2003081527A1 (en) 2003-10-02
CN100520817C (zh) 2009-07-29
DE60217663T2 (de) 2007-11-22

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