... variable, respectively. The support vector machines (SVM) is introduced to predict the monthly electric energy consumption of crude oil pipelines driving oil pumps. However, the generalization capability of SVM is highly dependent on appropriate parameter setting, such as penalty coefficient and kernel...

... Abstract Internal CO 2 /H 2 S corrosion of gathering pipelines is a serious problem in natural gas plant. It is important for field engineers to assess the corrosion degree and control corrosion risk. A multi-kernel support-vector-machine (SVM) method is presented to rank internal corrosion...

... pipeline network, a hybrid optimization strategy of integrated genetic optimization algorithm and support vector machine are proposed. Factors such as holidays, date types and weather were taken into account to build a natural gas daily load prediction model based on GA-SVM was established. A natural gas...

... as features in support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) logistic regression methodologies to detect changes in the pipe condition from its baseline state. SVM classification accuracy averaged 99% for all models. LASSO classification accuracy averaged 99% for all...