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.
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
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