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1D CNN Model for Corrosion Prediction

Zaini, Nurfaraheen (2020) 1D CNN Model for Corrosion Prediction. IRC, Universiti Teknologi PETRONAS. (Submitted)

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The large number of pipelines that have in this world have led to create a prediction system which can help in keep maintaining the condition of pipelines. Then, the used of advanced analytics can help to uncover patterns that not revealed by conventional analytics and predictive analytics are the future pipeline condition assessment and monitoring that will provide stakeholders with a better overview of operations, more control and flexibility for managing pipeline assets. Besides, it is to develop a machine learning of predictive analytics algorithm with a visualization dashboard for the predicted of internal and external corrosion levels of pipelines. It can help to enhance the integrity management of strategic pipelines as well.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > Q Science (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 24 Sep 2021 09:56
Last Modified: 24 Sep 2021 09:56
URI: http://utpedia.utp.edu.my/id/eprint/21797

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