Forecasting Corrosion Rate on Pipeline using Artificial Neural Network

• 第一著者: Zolkifli, Nur Anissa
• フォーマット: Final Year Project
• 言語: English
• 出版事項: 2022
• 主題: T Technology (General)
• オンライン･アクセス: http://utpedia.utp.edu.my/id/eprint/24539/1/Forecasting%20Corrosion%20Rate%20on%20Pipeline%20using%20Artificial%20Neural%20Network.pdf; http://utpedia.utp.edu.my/id/eprint/24539/

Large amounts of oil and gas are transported every day and distributed throughout the world through pipelines. They are considered the safest method of transporting oil and gas because they rarely fail. Nevertheless, pipelines could lead to deterioration and degradation. Therefore, it is crucial to...