JP7724861B2 - 油ポンプ管理のためのマルチ・ラベル分類モデルのための連合学習 - Google Patents

油ポンプ管理のためのマルチ・ラベル分類モデルのための連合学習

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JP7724861B2
JP7724861B2 JP2023534934A JP2023534934A JP7724861B2 JP 7724861 B2 JP7724861 B2 JP 7724861B2 JP 2023534934 A JP2023534934 A JP 2023534934A JP 2023534934 A JP2023534934 A JP 2023534934A JP 7724861 B2 JP7724861 B2 JP 7724861B2
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JP2023553909A (ja
JP2023553909A5 (https=
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ゾウ、ニアンジュン
パテル、ダーヴァルクマール
バーミディパティ、アヌラーダ
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International Business Machines Corp
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
    • F04B49/00—Control, e.g. of pump delivery, or pump pressure of, or safety measures for, machines, pumps, or pumping installations, not otherwise provided for, or of interest apart from, groups F04B1/00 - F04B47/00
    • F04B49/06—Control using electricity
    • F04B49/065—Control using electricity and making use of computers
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
    • F04B51/00—Testing machines, pumps, or pumping installations
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/098—Distributed learning, e.g. federated learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Molecular Biology (AREA)
  • Mathematical Physics (AREA)
  • Evolutionary Computation (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • General Business, Economics & Management (AREA)
  • Tourism & Hospitality (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Mechanical Engineering (AREA)
  • Computer Hardware Design (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Databases & Information Systems (AREA)
JP2023534934A 2020-12-15 2021-12-02 油ポンプ管理のためのマルチ・ラベル分類モデルのための連合学習 Active JP7724861B2 (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US17/123,088 2020-12-15
US17/123,088 US12182771B2 (en) 2020-12-15 2020-12-15 Federated learning for multi-label classification model for oil pump management
PCT/IB2021/061237 WO2022130098A1 (en) 2020-12-15 2021-12-02 Federated learning for multi-label classification model for oil pump management

Publications (3)

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JP2023553909A JP2023553909A (ja) 2023-12-26
JP2023553909A5 JP2023553909A5 (https=) 2025-07-10
JP7724861B2 true JP7724861B2 (ja) 2025-08-18

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US (1) US12182771B2 (https=)
JP (1) JP7724861B2 (https=)
CN (1) CN116601632A (https=)
DE (1) DE112021005868T5 (https=)
WO (1) WO2022130098A1 (https=)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7818908B2 (ja) * 2021-07-14 2026-02-24 キヤノンメディカルシステムズ株式会社 情報処理装置、情報処理システム、情報処理方法、及びプログラム
CN115623433B (zh) * 2022-09-07 2025-11-25 山东电力工程咨询院有限公司 基于5g和联邦学习的整县光伏数据共享增值系统及方法
KR102569454B1 (ko) * 2022-12-06 2023-08-23 한국전자통신연구원 탈중앙 학습 환경에서의 클라이언트 모델 학습 방법 및 이를 수행하는 클라이언트 장치
CN116432040B (zh) * 2023-06-15 2023-09-01 上海零数众合信息科技有限公司 基于联邦学习的模型训练方法、装置、介质以及电子设备
TW202509356A (zh) * 2023-06-21 2025-03-01 義大利商沙斯格特斯公司 用於非蒸發型集氣真空泵之預測維護方法
WO2025090070A1 (en) * 2023-10-23 2025-05-01 Halliburton Energy Services, Inc. Real-time feedback and machine learning system for downhole environments
US20250392459A1 (en) * 2024-06-25 2025-12-25 Crossbar, Inc. Backup and recovery system and methods for cryptocurrency hardware wallet

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120023043A1 (en) 2010-07-21 2012-01-26 Ozgur Cetin Estimating Probabilities of Events in Sponsored Search Using Adaptive Models
JP2017027329A (ja) 2015-07-22 2017-02-02 ルネサスエレクトロニクス株式会社 故障予測装置および故障予測方法
KR101827108B1 (ko) 2016-05-04 2018-02-07 두산중공업 주식회사 플랜트 이상 감지 학습 시스템 및 방법
WO2019120578A1 (en) 2017-12-22 2019-06-27 Huawei Technologies Co., Ltd. Client, server, and client-server system adapted for generating personalized recommendations
US20200285980A1 (en) 2019-03-08 2020-09-10 NEC Laboratories Europe GmbH System for secure federated learning
JP2020528589A (ja) 2017-08-11 2020-09-24 グーグル エルエルシー オンデバイス機械学習プラットフォーム
JP2020170596A (ja) 2019-04-01 2020-10-15 大阪瓦斯株式会社 故障予兆検知システム

Family Cites Families (28)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6155840A (en) 1998-09-18 2000-12-05 At Home Corporation System and method for distributed learning
US6708163B1 (en) * 1999-02-24 2004-03-16 Hillol Kargupta Collective data mining from distributed, vertically partitioned feature space
US7610264B2 (en) 2005-02-28 2009-10-27 International Business Machines Corporation Method and system for providing a learning optimizer for federated database systems
US8401282B2 (en) 2010-03-26 2013-03-19 Mitsubishi Electric Research Laboratories, Inc. Method for training multi-class classifiers with active selection and binary feedback
US8924313B2 (en) 2010-06-03 2014-12-30 Xerox Corporation Multi-label classification using a learned combination of base classifiers
US10325220B2 (en) 2014-11-17 2019-06-18 Oath Inc. System and method for large-scale multi-label learning using incomplete label assignments
US20170308802A1 (en) 2016-04-21 2017-10-26 Arundo Analytics, Inc. Systems and methods for failure prediction in industrial environments
CN109716346A (zh) 2016-07-18 2019-05-03 河谷生物组学有限责任公司 分布式机器学习系统、装置和方法
US10460255B2 (en) 2016-07-29 2019-10-29 Splunk Inc. Machine learning in edge analytics
US20180089587A1 (en) 2016-09-26 2018-03-29 Google Inc. Systems and Methods for Communication Efficient Distributed Mean Estimation
US20180107791A1 (en) 2016-10-17 2018-04-19 International Business Machines Corporation Cohort detection from multimodal data and machine learning
US11086918B2 (en) 2016-12-07 2021-08-10 Mitsubishi Electric Research Laboratories, Inc. Method and system for multi-label classification
US10536437B2 (en) 2017-01-31 2020-01-14 Hewlett Packard Enterprise Development Lp Performing privacy-preserving multi-party analytics on vertically partitioned local data
US10565524B2 (en) 2017-01-31 2020-02-18 Hewlett Packard Enterprise Development Lp Performing privacy-preserving multi-party analytics on horizontally partitioned local data
US20190197411A1 (en) 2017-12-21 2019-06-27 Microsoft Technology Licensing, Llc Characterizing model performance using global and local feature contributions
US20190279132A1 (en) * 2018-03-08 2019-09-12 General Electric Company Analytics core and aggregation
US10241992B1 (en) 2018-04-27 2019-03-26 Open Text Sa Ulc Table item information extraction with continuous machine learning through local and global models
US11170320B2 (en) 2018-07-19 2021-11-09 Adobe Inc. Updating machine learning models on edge servers
US11300481B2 (en) * 2019-01-25 2022-04-12 Wipro Limited Method and system for predicting failures in diverse set of asset types in an enterprise
US20200364608A1 (en) 2019-05-13 2020-11-19 International Business Machines Corporation Communicating in a federated learning environment
CN111369042B (zh) 2020-02-27 2021-09-24 山东大学 一种基于加权联邦学习的无线业务流量预测方法
CN111382706B (zh) 2020-03-10 2025-01-24 深圳前海微众银行股份有限公司 基于联邦学习的预测方法、装置、存储介质及遥感设备
CN111798002A (zh) 2020-05-31 2020-10-20 北京科技大学 一种局部模型占比可控的联邦学习全局模型聚合方法
US20230177349A1 (en) * 2020-06-01 2023-06-08 Intel Corporation Federated learning optimizations
CN111754000B (zh) 2020-06-24 2022-10-14 清华大学 质量感知的边缘智能联邦学习方法及系统
CN111737749A (zh) 2020-06-28 2020-10-02 南方电网科学研究院有限责任公司 基于联邦学习的计量装置告警预测方法及设备
US11704942B2 (en) * 2020-10-29 2023-07-18 Caterpillar Inc. Undercarriage wear prediction using machine learning model
US20220138260A1 (en) * 2020-10-30 2022-05-05 Here Global B.V. Method, apparatus, and system for estimating continuous population density change in urban areas

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120023043A1 (en) 2010-07-21 2012-01-26 Ozgur Cetin Estimating Probabilities of Events in Sponsored Search Using Adaptive Models
JP2017027329A (ja) 2015-07-22 2017-02-02 ルネサスエレクトロニクス株式会社 故障予測装置および故障予測方法
KR101827108B1 (ko) 2016-05-04 2018-02-07 두산중공업 주식회사 플랜트 이상 감지 학습 시스템 및 방법
JP2020528589A (ja) 2017-08-11 2020-09-24 グーグル エルエルシー オンデバイス機械学習プラットフォーム
WO2019120578A1 (en) 2017-12-22 2019-06-27 Huawei Technologies Co., Ltd. Client, server, and client-server system adapted for generating personalized recommendations
US20200285980A1 (en) 2019-03-08 2020-09-10 NEC Laboratories Europe GmbH System for secure federated learning
JP2020170596A (ja) 2019-04-01 2020-10-15 大阪瓦斯株式会社 故障予兆検知システム

Also Published As

Publication number Publication date
DE112021005868T5 (de) 2023-08-24
US12182771B2 (en) 2024-12-31
JP2023553909A (ja) 2023-12-26
CN116601632A (zh) 2023-08-15
WO2022130098A1 (en) 2022-06-23
US20220188775A1 (en) 2022-06-16

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