MY204803A - Continuous learning of simulation trained deep neural network model - Google Patents

Continuous learning of simulation trained deep neural network model

Info

Publication number
MY204803A
MY204803A MYPI2020006529A MYPI2020006529A MY204803A MY 204803 A MY204803 A MY 204803A MY PI2020006529 A MYPI2020006529 A MY PI2020006529A MY PI2020006529 A MYPI2020006529 A MY PI2020006529A MY 204803 A MY204803 A MY 204803A
Authority
MY
Malaysia
Prior art keywords
data
simulation
neural network
network model
real world
Prior art date
Application number
MYPI2020006529A
Other languages
English (en)
Inventor
James Francis O'sullivan
Djoni Eka Sidarta
Ho Joon Lim
Original Assignee
Technip France
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 Technip France filed Critical Technip France
Publication of MY204803A publication Critical patent/MY204803A/en

Links

Classifications

    • 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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
    • B63B21/00—Tying-up; Shifting, towing, or pushing equipment; Anchoring
    • B63B21/50—Anchoring arrangements or methods for special vessels, e.g. for floating drilling platforms or dredgers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
    • B63B71/00—Designing vessels; Predicting their performance
    • B63B71/10—Designing vessels; Predicting their performance using computer simulation, e.g. finite element method [FEM] or computational fluid dynamics [CFD]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine 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
    • G06N3/04—Architecture, e.g. interconnection topology
    • 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
    • G06N3/0499—Feedforward 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
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Computational Linguistics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • Ocean & Marine Engineering (AREA)
  • Fluid Mechanics (AREA)
  • Computer Hardware Design (AREA)
  • Geometry (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
MYPI2020006529A 2018-06-08 2019-06-06 Continuous learning of simulation trained deep neural network model MY204803A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US16/003,443 US11315015B2 (en) 2018-06-08 2018-06-08 Continuous learning of simulation trained deep neural network model
PCT/IB2019/000748 WO2019234505A1 (en) 2018-06-08 2019-06-06 Continuous learning of simulation trained deep neural network model for floating production platforms, vessels and other floating systems.

Publications (1)

Publication Number Publication Date
MY204803A true MY204803A (en) 2024-09-14

Family

ID=67997650

Family Applications (1)

Application Number Title Priority Date Filing Date
MYPI2020006529A MY204803A (en) 2018-06-08 2019-06-06 Continuous learning of simulation trained deep neural network model

Country Status (8)

Country Link
US (1) US11315015B2 (https=)
EP (1) EP3802310B1 (https=)
JP (1) JP7129498B2 (https=)
KR (1) KR102809829B1 (https=)
CN (1) CN112424063B (https=)
BR (1) BR112020024951A2 (https=)
MY (1) MY204803A (https=)
WO (1) WO2019234505A1 (https=)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12275146B2 (en) * 2019-04-01 2025-04-15 Nvidia Corporation Simulation of tasks using neural networks
CN113711179A (zh) * 2019-04-09 2021-11-26 索尼集团公司 信息处理设备、信息处理方法和程序
JP2023512591A (ja) * 2020-02-07 2023-03-27 シングル・ブイ・ムアリングズ・インコーポレイテッド データ転送システムを備えた係留ブイ
WO2022000430A1 (zh) * 2020-07-02 2022-01-06 深圳市欢太科技有限公司 服务器威胁评定方法及相关产品
CN113541126B (zh) * 2021-06-17 2025-03-25 国网湖南综合能源服务有限公司 适用于验证高级算法的配电网仿真系统及算法验证方法
US11614075B2 (en) * 2021-08-09 2023-03-28 Technip Energies France Method of monitoring and advising for a group of offshore floating wind platforms

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CN1121607A (zh) * 1994-10-28 1996-05-01 中国船舶工业总公司第七研究院第七○二研究所 船舶动力定位的神经网络控制系统及其方法
US5920852A (en) 1996-04-30 1999-07-06 Grannet Corporation Large memory storage and retrieval (LAMSTAR) network
US6376831B1 (en) * 2000-02-24 2002-04-23 The United States Of America As Represented By The Secretary Of The Navy Neural network system for estimating conditions on submerged surfaces of seawater vessels
JP2003022134A (ja) 2001-07-06 2003-01-24 Mitsubishi Heavy Ind Ltd 浮体位置制御システム及び浮体位置制御シミュレータ
US8756047B2 (en) 2010-09-27 2014-06-17 Sureshchandra B Patel Method of artificial nueral network loadflow computation for electrical power system
US20140063061A1 (en) * 2011-08-26 2014-03-06 Reincloud Corporation Determining a position of an item in a virtual augmented space
KR101518720B1 (ko) * 2015-02-15 2015-05-08 (주)부품디비 해양자원 생산장비의 예지보전을 위한 고장유형관리 장치 및 방법
US10372976B2 (en) * 2016-05-05 2019-08-06 Brunswick Corporation Person detection in a marine environment
US10521677B2 (en) * 2016-07-14 2019-12-31 Ford Global Technologies, Llc Virtual sensor-data-generation system and method supporting development of vision-based rain-detection algorithms
CA3069299C (en) * 2017-08-21 2023-03-14 Landmark Graphics Corporation Neural network models for real-time optimization of drilling parameters during drilling operations
CN107545250A (zh) 2017-08-31 2018-01-05 哈尔滨工程大学 一种基于海浪图像遥感和人工智能的海洋浮体运动实时预报系统
US10800040B1 (en) * 2017-12-14 2020-10-13 Amazon Technologies, Inc. Simulation-real world feedback loop for learning robotic control policies

Also Published As

Publication number Publication date
KR20210019006A (ko) 2021-02-19
JP2021527258A (ja) 2021-10-11
US20190378005A1 (en) 2019-12-12
WO2019234505A1 (en) 2019-12-12
EP3802310A1 (en) 2021-04-14
JP7129498B2 (ja) 2022-09-01
KR102809829B1 (ko) 2025-05-16
BR112020024951A2 (pt) 2021-03-09
EP3802310B1 (en) 2024-09-04
CN112424063A (zh) 2021-02-26
US11315015B2 (en) 2022-04-26
CN112424063B (zh) 2023-12-22

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