id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-19160	Yuan, Wei; Zhang, Liang; Ren, Hao	Application of Improved Support Vector Machine in Predicting Failure Pressure of Oil and Gas Pipelines with Internal Corrosion Defects	2024	13	.pdf	application/pdf	7115	435	59	In this modeling process, we studied the effects of four parameters, namely seawater depth, corrosion defect depth, corrosion defect length, and corrosion defect width, on the failure pressure of 119 submarine pipelines affected by corrosion defects. The performance of ANN-LM in the test set is similar to that of SVM, but much lower than that of SVM derivative model, which confirms its under-fitting in the training stage.	cache/ajst-19160.pdf	txt/ajst-19160.txt