Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigm: With Artificial Intelligence Integration in Energy and Other Use Cases - Softcover

Zohuri, Bahman; Rahmani, Farhang Mossavar; Behgounia, Farahnaz

Softcover

ISBN 10: 0323951120 ISBN 13: 9780323951128

Publisher: Academic Press, 2022

Synopsis

Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigms, Forecasting Energy for Tomorrow’s World with Mathematical Modeling and Python Programming Driven Artificial Intelligence delivers knowledge on key infrastructure topics in both AI technology and energy. Sections lay the groundwork for tomorrow’s computing functionality, starting with how to build a Business Resilience System (BRS), data warehousing, data management, and fuzzy logic. Subsequent chapters dive into the impact of energy on economic development and the environment and mathematical modeling, including energy forecasting and engineering statistics.  Energy examples are included for application and learning opportunities.

A final section deliver the most advanced content on artificial intelligence with the integration of machine learning and deep learning as a tool to forecast and make energy predictions. The reference covers many introductory programming tools, such as Python, Scikit, TensorFlow and Kera.

• Helps users gain fundamental knowledge in technology infrastructure, including AI, machine learning and fuzzy logic
• Compartmentalizes data knowledge into near-term and long-term forecasting models, with examples involving both renewable and non-renewable energy outcomes
• Advances climate resiliency and helps readers build a business resiliency system for assets

About this title

About the Authors

Prof. Bahman Zohuri is an accomplished scientist, engineer, and academic with deep expertise in nuclear engineering, thermodynamics, and applied physics. He serves as an Adjunct Professor at Golden Gate University, where he teaches courses in artificial intelligence and machine learning. Prof. Zohuri holds degrees in Applied Mathematics, Physics, Mechanical Engineering, and Nuclear Engineering from institutions including the University of Illinois and the University of New Mexico. Early in his career, he contributed to advanced research projects at Westinghouse, and later in defense and semiconductor industries, before founding Galaxy Advanced Engineering, Inc. in 1991. Over his career, Prof. Zohuri has authored dozens of technical books and published over a hundred journal articles. He continues to pursue research in fields such as heat transfer, reactor design, computational methods, data mining, and AI-driven engineering solutions.

Farahnaz Behgounia is presently a graduate student at Golden Gate University at San Francisco, California and in the process of obtaining her Master of Science degree from the school of Business Analytics. She has obtained her Bachlor Degreee (BS) in pure mathematics and have taught the subject at various schools as an instructor. Ms. Behgounia’s present interest is in Artificial Intelligence (AL) and its application in industry along with its sub-component such as Machine Learning (ML) and Deep Leaning (DL). Her recent interest in the subject of AI has directed her into more innovative research in AI and writing various algorithim by utilizing python language for various applications such as E-Commerce,the medical field and others.

From the Back Cover

Many industries are aggressively growing their digital infrastructure and with it comes an increased demand on electricity driven by both renewable and non-renewable sources of energy. Energy engineers are quickly learning processing information, such as deep learning and AI, but there is a gap on how to utilize AI technology while maintaining sustainable energy needs and invest in the most efficient decisions for energy companies. Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigm with Artificial Intelligence Integration in Energy and Other Use Cases is the first volume in a series that delivers knowledge on key infrastructure in both AI technology and energy, showcasing a scientific method to model and make stronger energy forecasts and decisions.

Structured into four development components, the reference lays the groundwork on tomorrow’s computing functionality starting with how to build a Business Resilience System (BRS). Data warehousing, data management, and fuzzy logic are included. In part II, the authors dive further into the impact of energy on economic development and the environment. Chapters are organized by energy sources with each chapter covering definition, present data, future data, technology, and the advantages and disadvantages for each before rounding out with storage technology. Part III adds a layer of mathematical modeling combined with energy forecasting. Starting with engineering statistics, the reference progresses into various kinds of forecasting and plots, starting with the simplest such as linear regression and then advances into the principles of forecasting. Energy examples are included for application and learning opportunities. Last, Part IV delivers the most advanced content into artificial intelligence with integration of machine learning and deep learning as a tool to forecast and make energy predictions. The reference covers many introductory programming tools such as Python, Scikit, TensorFlow, Keras and more to utilize linear and non-linear regression models for the purpose of forecasting. Big data in structured and unstructured processing are included, helping the engineer understand the right information for real-time processing. Packed with examples, Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigm with Artificial Intelligence Integration in Energy and Other Use Cases gives today’s engineers the knowledge of information to make more trusted decisions, forecast energy needs, and build climate resiliency within their operations.

Edition details

• Publisher: Academic Press
• Publication date: 2022
• Language: English
• ISBN 10: 0323951120
• ISBN 13: 9780323951128
• Binding: Paperback
• Edition number: 1
• Number of pages: 998