Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies - Image 1

£93.28

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

Name: Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies
Brand: Elsevier
Price: 93.28 GBP
Availability: InStock

Higher Education

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Product Description 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. Review Explores cutting-edge research in machine learning and applies it to problems in the power-generation industry to highlight current best practices From the Back Cover 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 studydriven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. About the Author 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.

Product Specifications

Brand: Elsevier
Format: Paperback
ASIN: 0128197420
Category: Books > Subjects > Science, Nature & Maths > Engineering & Technology > Education > Higher Education
Domain: Amazon UK
Release Date: 25 January 2021
Listed Since: 01 October 2019

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

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