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Hands-On Artificial Intelligence for IoT

You're reading from   Hands-On Artificial Intelligence for IoT Expert machine learning and deep learning techniques for developing smarter IoT systems

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788836067
Length 390 pages
Edition 2nd Edition
Languages
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Author (1):
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Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
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Table of Contents (14) Chapters Close

Preface 1. Principles and Foundations of IoT and AI FREE CHAPTER 2. Data Access and Distributed Processing for IoT 3. Machine Learning for IoT 4. Deep Learning for IoT 5. Genetic Algorithms for IoT 6. Reinforcement Learning for IoT 7. Generative Models for IoT 8. Distributed AI for IoT 9. Personal and Home IoT 10. AI for the Industrial IoT 11. AI for Smart Cities IoT 12. Combining It All Together 13. Other Books You May Enjoy

Electrical load forecasting in industry


Electricity is presently the most important energy vector in both the domestic and industrial sectors. Since, unlike fuels, it is hard and expensive to store electricity, there is a need for a precise coupling between its generation and demand. Electrical energy load forecasting, hence, is very vital. Depending upon the time range (forecasting horizon) electrical load forecasting is classified into the following three categories:

  • Short-term load forecasting: The forecast is made for one hour to a few weeks
  • Medium-term load forecasting: The forecast duration spreads from a few weeks to a few months
  • Long-term load forecasting: Here, the forecasting is done from a few months to years

Depending upon the need and application one may have to plan either one or all of the previous load forecasting categories. In recent years, a lot of research work has been done in the area of short-term load forecasting (STLF). STLF can assist industries by providing an accurate...

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