ANALYSIS OF SMOTE-BASED DATA AUGMENTATION AND MACHINE LEARNING MODELS FOR BURST PRESSURE PREDICTION OF OIL AND GAS PIPELINES
Saved in:
Main Author: | SOOMRO, AFZAL AHMED |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | http://utpedia.utp.edu.my/id/eprint/28967/1/AfzalAhmedSoomro_20000277.pdf http://utpedia.utp.edu.my/id/eprint/28967/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Burst pressure prediction of multiple cracks in pipelines
by: Norhaida, Ab. Razak, et al.
Published: (2013) -
Analysis of machine learning models and data sources to forecast burst pressure of petroleum corroded pipelines: A comprehensive review
by: Ahmed Soomro, A., et al.
Published: (2024) -
Burst pressure prediction of collinear crack in steel pipeline
by: Muhammad Alif Hafiz, Abd Murad
Published: (2013) -
Thunderstorm Prediction Model Using SMOTE Sampling and Machine Learning Approach
by: Shirley, Rufus, et al.
Published: (2023) -
Thunderstorm prediction model using SMOTE sampling and machine learning approach.
by: Rufus, Shirley Anak, et al.
Published: (2023)