Publication Date

1-1-2022

Document Type

Contribution to a Book

Department

Applied Data Science

Publication Title

Machine Learning for Societal Improvement, Modernization, and Progress

Editor

Vishnu Pendyala

DOI

10.4018/978-1-6684-4045-2.ch010

First Page

200

Last Page

224

Abstract

The formation of gas hydrates in the pipelines of oil, gas, chemical, and other industries has been a significant problem for many years because the formation of gas hydrates may block the pipelines. Hence, the knowledge of the phase equilibrium conditions of gas hydrate became necessary for the economic and safe working of oil, gas, chemical industries. Various thermodynamic approaches with various mathematical techniques are available for the prediction of formation conditions of gas hydrates. In this chapter, the authors have discussed the least square support vector machine and artificial neural network models for the prediction of stability conditions of gas hydrates and the use of genetic programming (GP) and genetic algorithm (GA) to develop a generalized correlation for predicting equilibrium conditions of gas hydrates.

Comments

This is the Version of Record, and has been used with the permission of IGI Global, under their Fair Use Policy.

Share

COinS