An Enhanced Generative Adversarial Network Prediction Model Based on LSTM and Attention for Corrosion Rate in Pipelines

An Enhanced Generative Adversarial Network Prediction Model Based on LSTM and Attention for Corrosion Rate in Pipelines

To address the pervasive issue of internal pipeline corrosion in the oil and gas industry, this paper proposes a hybrid intelligent model for predicting corrosion rates. This model integrates an improved Generative Adversarial Network with Grey Wolf Optimization and Support Vector Regression (LAGAN-...

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Bibliographic Details
Main Authors: Pujun Long, Mi Liang, Hongjian Chen, Qin Yang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Internal pipeline corrosion
grey wolf optimization
support vector regression
generative adversarial network
Online Access:https://ieeexplore.ieee.org/document/10930449/
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https://ieeexplore.ieee.org/document/10930449/

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