Knowledge Is Power in Four Dimensions: Models to Forecast Future Paradigm: With Artificial Intelligence Integration in Energy and Other Use Cases
- 22h
- Bahman Zohuri, Farahnaz Behgounia, Farhang Mossavar Rahmani
- Elsevier Science and Technology Books, Inc.
- 2022
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 the Author
Dr. Bahman Zohuri is currently an Adjunct Professor in Artificial Intelligence Science at Golden Gate University, San Francisco, California, who runs his own consulting company and was previously a consultant at Sandia National Laboratory. Dr. Zohuri earned his bachelor’s and master’s degrees in physics from the University of Illinois. He earned his second master’s degree in mechanical engineering, and also his doctorate in nuclear engineering from the University of New Mexico. He owns three patents and has published more than 40 textbooks and numerous journal publications.
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.
In this Book
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Knowledge is Power
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A General Approach to Business Resilience System (BRS)
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Data Warehousing, Data Mining, Data Modeling, and Data Analytics
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Structured and Unstructured Data Processing
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Mathematical Modeling Driven Predication
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Fuzzy Logics: A New Method of Predictions
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Neural Network Concept
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Population—Human Growth Driving Ecology
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Economic Factors
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Risk Management, Risk Assessment, and Risk Analysis
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Today's Fast-Paced Technology
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Understanding of Energy
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Economic Impact of Energy
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Renewable Energy
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Nonrenewable Energy
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Nuclear Energy as Nonrenewable Energy Source
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Energy Storage Technologies and Their Role in Renewable Integration
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Predictive Analytics
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Engineering statistics
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Data and Data Collection Driven Information
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Statistical Forecasting—Regression and Time Series Analysis
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Introduction to Forecasting: The Simplest Models
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Notes on Linear Regression Analysis
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Principles and Risks of Forecasting
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Artificial Intelligence Driving Predictive and Forecasting Paradigm
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Python Programming–Driven Artificial Intelligence
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Artificial Intelligence, Machine Learning, and Deep Learning Driving Big Data
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Artificial Intelligence, Machine Learning, and Deep Learning Use Cases
