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You're reading from  Practical Machine Learning Cookbook

Product typeBook
Published inApr 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781785280511
Edition1st Edition
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Author (1)
Atul Tripathi
Atul Tripathi
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Atul Tripathi

Atul Tripathi has spent more than 11 years in the fields of machine learning and quantitative finance. He has a total of 14 years of experience in software development and research. He has worked on advanced machine learning techniques, such as neural networks and Markov models. While working on these techniques, he has solved problems related to image processing, telecommunications, human speech recognition, and natural language processing. He has also developed tools for text mining using neural networks. In the field of quantitative finance, he has developed models for Value at Risk, Extreme Value Theorem, Option Pricing, and Energy Derivatives using Monte Carlo simulation techniques.
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Chapter 14. Case Study - Forecast of Electricity Consumption

Introduction


Electricity is the only commodity that is produced and consumed simultaneously; therefore, a perfect balance between supply and consumption in the electricity power market must always be maintained. Forecasting electricity consumption is of national interest to any country since electricity is a key source of energy. A reliable forecast of energy consumption, production, and distribution meets the stable and long-term policy. The presence of economies of scale, focus on environmental concerns, regulatory requirements, and a favorable public image, coupled with inflation, rapidly rising energy prices, the emergence of alternative fuels and technologies, changes in life styles, and so on, has generated the need to use modeling techniques which capture the effect of factors such as prices, income, population, technology, and other economic, demographic, policy, and technological variables.

Underestimation could lead to under-capacity utilization, which would result in poor quality...

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Author (1)

author image
Atul Tripathi

Atul Tripathi has spent more than 11 years in the fields of machine learning and quantitative finance. He has a total of 14 years of experience in software development and research. He has worked on advanced machine learning techniques, such as neural networks and Markov models. While working on these techniques, he has solved problems related to image processing, telecommunications, human speech recognition, and natural language processing. He has also developed tools for text mining using neural networks. In the field of quantitative finance, he has developed models for Value at Risk, Extreme Value Theorem, Option Pricing, and Energy Derivatives using Monte Carlo simulation techniques.
Read more about Atul Tripathi