DE112021005868T5 - Föderales lernen für ein multi-label-klassifizierungsmodell zur ölpumpenverwaltung - Google Patents

Föderales lernen für ein multi-label-klassifizierungsmodell zur ölpumpenverwaltung Download PDF

Info

Publication number
DE112021005868T5
DE112021005868T5 DE112021005868.1T DE112021005868T DE112021005868T5 DE 112021005868 T5 DE112021005868 T5 DE 112021005868T5 DE 112021005868 T DE112021005868 T DE 112021005868T DE 112021005868 T5 DE112021005868 T5 DE 112021005868T5
Authority
DE
Germany
Prior art keywords
local
model
models
cohorts
computer
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.)
Pending
Application number
DE112021005868.1T
Other languages
German (de)
English (en)
Inventor
Nianjun Zhou
Dhavalkumar Patel
Anuradha Bhamidipaty
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.)
International Business Machines Corp
Original Assignee
International Business Machines Corp
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 International Business Machines Corp filed Critical International Business Machines Corp
Publication of DE112021005868T5 publication Critical patent/DE112021005868T5/de
Pending legal-status Critical Current

Links

Images

Classifications

    • 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
    • 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
    • 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]

Landscapes

  • 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)
DE112021005868.1T 2020-12-15 2021-12-02 Föderales lernen für ein multi-label-klassifizierungsmodell zur ölpumpenverwaltung Pending DE112021005868T5 (de)

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 (1)

Publication Number Publication Date
DE112021005868T5 true DE112021005868T5 (de) 2023-08-24

Family

ID=81941542

Family Applications (1)

Application Number Title Priority Date Filing Date
DE112021005868.1T Pending DE112021005868T5 (de) 2020-12-15 2021-12-02 Föderales lernen für ein multi-label-klassifizierungsmodell zur ölpumpenverwaltung

Country Status (5)

Country Link
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

Family Cites Families (35)

* 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
US8392343B2 (en) * 2010-07-21 2013-03-05 Yahoo! Inc. Estimating probabilities of events in sponsored search using adaptive models
US10325220B2 (en) 2014-11-17 2019-06-18 Oath Inc. System and method for large-scale multi-label learning using incomplete label assignments
JP6622497B2 (ja) * 2015-07-22 2019-12-18 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
US20170308802A1 (en) 2016-04-21 2017-10-26 Arundo Analytics, Inc. Systems and methods for failure prediction in industrial environments
KR101827108B1 (ko) * 2016-05-04 2018-02-07 두산중공업 주식회사 플랜트 이상 감지 학습 시스템 및 방법
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
US11403540B2 (en) * 2017-08-11 2022-08-02 Google Llc On-device machine learning platform
US20190197411A1 (en) 2017-12-21 2019-06-27 Microsoft Technology Licensing, Llc Characterizing model performance using global and local feature contributions
WO2019120578A1 (en) * 2017-12-22 2019-06-27 Huawei Technologies Co., Ltd. Client, server, and client-server system adapted for generating personalized recommendations
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
US11836643B2 (en) * 2019-03-08 2023-12-05 Nec Corporation 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
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

Also Published As

Publication number Publication date
US12182771B2 (en) 2024-12-31
JP7724861B2 (ja) 2025-08-18
JP2023553909A (ja) 2023-12-26
CN116601632A (zh) 2023-08-15
WO2022130098A1 (en) 2022-06-23
US20220188775A1 (en) 2022-06-16

Similar Documents

Publication Publication Date Title
DE112021005868T5 (de) Föderales lernen für ein multi-label-klassifizierungsmodell zur ölpumpenverwaltung
DE112021004908T5 (de) Computerbasierte systeme, rechenkomponenten und rechenobjekte, die eingerichtet sind, dynamische ausreisser-verzerrungs-verringerung bei maschinenlernmodellen zu implementieren
DE202017007517U1 (de) Aggregatmerkmale für maschinelles Lernen
DE112011101559T5 (de) Dynamische adaptive Erkennung von Prozessen und deren Einhaltung
DE102014113692A1 (de) Verdichtung von longitudinalen epa für eine verbesserte phänotypisierung
EP3699704B1 (de) System und verfahren zum überprüfen von systemanforderungen von cyber-physikalischen systemen
DE112021002866T5 (de) Modelltreueüberwachung und -neuerstellung zur entscheidungsunterstützung eines fertigungsverfahrens
DE112021004958T5 (de) Skalierbares modellieren bei grossen sammlungen von zeitreihen
DE112018001757T5 (de) Betriebs-/Wartungsmanagementverfahren, Programm und Betriebs-/Wartungsmanagementsystem
DE202025104704U1 (de) System zur dynamischen Immobilienbewertung auf Basis von multiparametrischen Marktindikatoren
DE112020005732T5 (de) Erzeugen von trainingsdaten zur objekterkennung
EP3901713B1 (de) Verfahren und system zum betrieb einer technischen anlage mit einem optimalen modell
CH698890B1 (de) Modellierung eines komplexen Systems.
DE112021001767T5 (de) Rationalisieren von datenverarbeitungsoptimierungen für arbeitslasten mit maschinellem lernen
AT412678B (de) Verfahren zur rechnergestützten erstellung von prognosen für operative systeme sowie system zur erstellung von prognosen für operative systeme
DE102020215589A1 (de) Steuern eines deep-sequence-modells mit prototypen
DE112018005620T5 (de) Auftragsverwaltung in einem datenverarbeitungssystem
DE202023106319U1 (de) Ein Niederschlagsvorhersagesystem
DE112022003696T5 (de) Verfahren und systeme zur erzeugung von modellen für die bildanalyse pipeline prediction
DE112021001565T5 (de) Sortieren von datenelementen eines bestimmten satzes von datenelementen
WO2024156387A1 (de) Verfahren zum überwachen eines automatisierungssystems
EP3716058A1 (de) Verfahren zum ansteuern eines geräts mit einem neuen programmcode
DE112021007856T5 (de) Vorrichtung für maschinelles Lernen, Vorrichtung zum Vorhersagen eines Schweregrades und Verfahren für maschinelles Lernen
EP4235481A1 (de) Verfahren zum erstellen eines lastprofils
CH714168B1 (de) Computerimplementiertes Verfahren, System, Computerprogramm und Datenträger zum Erstellen eines Leistungsrangordnungsdatensatzes.

Legal Events

Date Code Title Description
R012 Request for examination validly filed
R084 Declaration of willingness to licence