Recurrent Neural Networks for Oil Well Event Prediction-Reference-Cited by-同舟云学术

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Recurrent Neural Networks for Oil Well Event Prediction

Published:2023-03 Issue:2 Volume:38 Page:73-80
ISSN:1541-1672
Container-title:IEEE Intelligent Systems
language:
Short-container-title:IEEE Intell. Syst.

Author:

Magnusson Lars Vidar¹^ORCID,Olsson J. Roland¹^ORCID,Tran Chau Thi Thuy²

Affiliation:

1. Østfold University College, Department of Computer Science and Communication, Halden, Norway

2. Institute for Energy Technology, Halden, Norway

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/9670/10111508/10058896.pdf?arnumber=10058896

Reference18 articles.

1. Adam: A method for stochastic optimization;kingma,2014

2. Searching for activation functions;ramachandran,2017

3. Using automatic programming to improve gradient boosting for classification;olsson;Proc Int Conf Artif Intell Soft Comput,2022

4. Incorporating Nesterov momentum into ADAM;dozat;Proc Int Conf Learn Representations,2016

5. Automatic synthesis of neurons for recurrent neural nets;olsson,2022

Cited by 4 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. Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators;IEEE Open Journal of the Industrial Electronics Society;2024

2. Enhancing fault diagnosis of undesirable events in oil & gas systems: A machine learning approach with new criteria for stability analysis and classification accuracy;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2023-11-15

3. The 3W Project and its Strategy to Foster the Development of Data-Driven Solutions for the Offshore Sector;Day 1 Tue, October 24, 2023;2023-10-17

4. Deep Anomaly Analytics: Advancing the Frontier of Anomaly Detection;IEEE Intelligent Systems;2023-03

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