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Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies - Couverture souple

 
9780128197424: Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies
Couverture souple
ISBN 10 : 0128197420 ISBN 13 : 9780128197424
Editeur : Elsevier Science Publishing Co Inc, 2021

Synopsis

Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study-driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting.

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À propos de l'auteur

Dr. Patrick Bangert is the Vice President of Artificial Intelligence at Samsung SDS where he leads both the AI software development and AI consulting groups that each provide various offerings to the industry. He is the founder and Board Chair of Algorithmica Technologies, providing real-time process modeling, optimization, and predictive maintenance solutions to the process industry with a focus on chemistry and power generation. His doctorate from UCL specialized in applied mathematics, and his academic positions at NASA's Jet Propulsion Laboratory and Los Alamos National Laboratory made use of optimization and machine learning for magnetohydrodynamics and particle accelerator experiments. He has published extensively across optimization and machine learning and their relevant applications in the real world.

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Éditeur
Elsevier Science Publishing Co Inc
Date d'édition
2021
Langue
anglais
ISBN 10 
0128197420
ISBN 13 
9780128197424
Reliure
Broché
Nombre de pages
274
Éditeur
Bangert Patrick
Coordonnées du fabricant
ELSEVIER
https://www.elsevier.com/es-es

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