Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigm
Language: English
Published by Elsevier Science and Technology, GB, 2022
- Softcover
- New

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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.…
Seller Inventory # LU-9780323951128
- Title
- Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigm
- Author
- Farhang Mossavar Rahmani, Farahnaz Behgounia, Bahman Zohuri
- Publisher
- Elsevier Science and Technology, GB
- Publication year
- 2022
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0323951120
- ISBN 13
- 9780323951128
- Item weight
- 450 grams
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
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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