Overview

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.

Full Product Details

Author:   Bahman Zohuri (Adjunct Professor, Golden Gate University, San Francisco, USA) ,  Farhang Mossavar Rahmani ,  Farahnaz Behgounia (Graduate Student, Golden Gate University at San Francisco, California, USA)
Publisher:   Elsevier Science & Technology
Imprint:   Academic Press Inc
Weight:   0.450kg
ISBN:  

9780323951128

ISBN 10:   0323951120
Pages:   998
Publication Date:   12 July 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Part I: Infrastructure Concepts 1. Knowledge is Power 2. A General Approach to Business Resilience System (BRS) 3. Data Warehousing, Data Mining, Data Modeling, and Data Analytics 4. Structured and Unstructured Data Processing 5. Mathematical Modeling Driven Predication 6. Fuzzy Logics: A New Method of Predictions 7. Neural Network Concept 8. Population - Human Growth Driving Ecology 9. Economic Factors 10. Risk Management, Risk Assessment, and Risk Analysis 11. Today’s Fast-Paced Technology Part II: The Impact of Energy on Tomorrow’s World 12. Understanding of Energy 13. Economic Impact of Energy 14. Renewable Energy 15. Non-Renewable Energy 16. Nuclear Energy as Non-Renewable Energy Source 17. Energy Storage Technologies and their Role in Renewable Integration Part III: The Mathematical Approach and Modeling 18. Predictive Analytics 19. Engineering Statistics 20. Data and Data Collection Driven Information 21. Statistical Forecasting - Regression and Time Series Analysis 22. Introduction to Forecasting: The Simplest Models 23. Notes on Linear Regression Analysis 24. Principles and Risks of Forecasting 25. Artificial Intelligence Driving Predictive and Forecasting Paradigm Part IV: Python Programming Driven Artificial Intelligence 26. Python Programming Driven Artificial Intelligence 27. Artificial Intelligence, Machine Learning and Deep Learning Driving Big Data 28. Artificial Intelligence, Machine Learning and Deep Learning Use Cases

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Author Information

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.

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