IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Artificial Neural Network: A New Tool for the Prediction of Hydrate Formation Conditions

Artificial Neural Network: A New Tool for the Prediction of Hydrate Formation Conditions
View Sample PDF
Author(s): Anupama Kumari (Indian Institute of Technology, Roorkee, India), Mukund Madhaw (DHC Trading India Private Limited, Delhi, India), C. B. Majumder (Indian Institute of Technology, Roorkee, India)and Amit Arora (Shaheed Bhagat Singh State University, Ferozepur, India)
Copyright: 2022
Pages: 21
Source title: Applications of Nature-Inspired Computing in Renewable Energy Systems
Source Author(s)/Editor(s): Mohamed Arezki Mellal (M'Hamed Bougara University, Algeria)
DOI: 10.4018/978-1-7998-8561-0.ch006

Purchase

View Artificial Neural Network: A New Tool for the Prediction of Hydrate Formation Conditions on the publisher's website for pricing and purchasing information.

Abstract

The analysis and collection of data is an integral part of all research fields of the modern world. There is a need to perform forward mathematical modeling to improve the operations and calculations with modern technologies. Artificial neural network signifies the structure of the human brain. They can provide reasonable solutions quickly for the problems that classical programming cannot solve. An in-depth systematic study is presented in this chapter related to artificial neural network applications (ANN) for predicting the equilibrium conditions for gas hydrate formation, which can assist in designing future dissociation technology for gas hydrate so that this white gold can make world energy free for the future generation. This chapter can also help to develop a novel inhibitor for gas hydrate formation and save millions of dollars for the oil and gas industry.

Related Content

P. Chitra, A. Saleem Raja, V. Sivakumar. © 2024. 24 pages.
K. Ezhilarasan, K. Somasundaram, T. Kalaiselvi, Praveenkumar Somasundaram, S. Karthigai Selvi, A. Jeevarekha. © 2024. 36 pages.
Kande Archana, V. Kamakshi Prasad, M. Ashok. © 2024. 17 pages.
Ritesh Kumar Jain, Kamal Kant Hiran. © 2024. 23 pages.
U. Vignesh, R. Elakya. © 2024. 13 pages.
S. Karthigai Selvi, R. Siva Shankar, K. Ezhilarasan. © 2024. 16 pages.
Vemasani Varshini, Maheswari Raja, Sharath Kumar Jagannathan. © 2024. 20 pages.
Body Bottom