Automatic Deep Vector Learning Model Applied for Oil-Well-Testing Feature Mining, Purification and Classification-Reference-Cited by-同舟云学术

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Automatic Deep Vector Learning Model Applied for Oil-Well-Testing Feature Mining, Purification and Classification

Published:2020 Issue: Volume:8 Page:151634-151649
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Feng Xin^ORCID,Feng Qiang^ORCID,Li Shaohui^ORCID,Hou Xingwei^ORCID,Zhang Mengqiu^ORCID,Liu Shugui^ORCID

Funder

National Natural Science Foundation of China

Research on Key Measurement Standards and Traceability Technology of Water Transport Engineering, National Key Research and Development Plan

Special Fund for Basic Scientific Research Business Expenses of Central Public Welfare Scientific Research Institutes

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09169874.pdf?arnumber=9169874

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Well Performance Classification and Prediction: Deep Learning and Machine Learning Long Term Regression Experiments on Oil, Gas, and Water Production;Sensors;2022-07-16

2. Support Vector Regression Based on the Particle Swarm Optimization Algorithm for Tight Oil Recovery Prediction;ACS Omega;2021-11-16

3. Vibration-based Processing and Classification Method for Oil Well-testing Data from Downhole Pressure Gauges;E3S Web of Conferences;2020

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