Publication Date
1-1-2022
Document Type
Contribution to a Book
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.
Department
Applied Data Science
Recommended Citation
Anupama Kumari, Mukund Madhaw, and Vishnu S. Pendyala. "Prediction of Formation Conditions of Gas Hydrates Using Machine Learning and Genetic Programming" Machine Learning for Societal Improvement, Modernization, and Progress (2022): 200-224. https://doi.org/10.4018/978-1-6684-4045-2.ch010
Comments
This is the Version of Record, and has been used with the permission of IGI Global, under their Fair Use Policy.