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Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigm

With Artificial Intelligence Integration in Energy and Other Use Cases

  • 1st Edition - July 12, 2022
  • Latest edition
  • Authors: Bahman Zohuri, Farhang Mossavar Rahmani, Farahnaz Behgounia
  • Language: English

Knowledge is Power in Four Dimensions: Models to Forecast Future Paradigms, Forecasting Energy for Tomorrow’s World with Mathematical Modeling and Python Programming Driven Artif… Read more

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Description

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.

Key features

  • 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

Readership

Energy engineers; electrical engineers; data scientists; environmental engineers; alternative energy researchers

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
Appendix
A: Pendulum Problem
B: Fluorescence Microscopy
C: Factors Contributed to the Financial Crisis 2008 - 2009
D: Factors contributing to the financial crisis of 2008
E: Forecasting the Future by the OECD
F: The 2025 Global Landscape
G: The World in 2050
H: Risk

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
Appendix
A: Fission Nuclear Energy Research and Development Roadmap
B: Thermonuclear Fusion Reaction Driving Electrical Power Generation

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
Appendix
A: The Weibull Distribution
B: The Logarithm Transformation
C: Geometric Random Walk Model
D: Random Walk Model
E: Examples of Forecasting Driven by Artificial Intelligence and Machine Learning
F: Examples of Python Programming Driving Artificial Intelligence and Machine Learning

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
Appendix
A: Artificial Intelligence and Human Intelligence
B: Deep Learning, Machine Learning Limitations and Flaws
C: Machine Learning Driven an E-Commerce
D: From Business Intelligence to Artificial Intelligence

Product details

  • Edition: 1
  • Latest edition
  • Published: July 14, 2022
  • Language: English

About the authors

BZ

Bahman Zohuri

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.
Affiliations and expertise
Adjunct Professor, Golden Gate University, San Francisco, USA

FB

Farahnaz Behgounia

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.
Affiliations and expertise
Graduate Student, Golden Gate University at San Francisco, California, USA

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