76,67 €
85,19 €
-10% with code: EXTRA
Advanced Methods of Power Load Forecasting
Advanced Methods of Power Load Forecasting
76,67
85,19 €
  • We will send in 10–14 business days.
This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting ar…
  • Publisher:
  • ISBN-10: 3036542183
  • ISBN-13: 9783036542188
  • Format: 17 x 24.4 x 1.3 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

Advanced Methods of Power Load Forecasting (e-book) (used book) | bookbook.eu

Reviews

Description

This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting are presented. These models are applied in different circumstances and show highly positive results. This reprint is intended for both researchers related to energy management and those related to forecasting, especially power load.

EXTRA 10 % discount with code: EXTRA

76,67
85,19 €
We will send in 10–14 business days.

The promotion ends in 9d.13:23:45

The discount code is valid when purchasing from 10 €. Discounts do not stack.

Log in and for this item
you will receive 0,85 Book Euros!?
  • Publisher:
  • ISBN-10: 3036542183
  • ISBN-13: 9783036542188
  • Format: 17 x 24.4 x 1.3 cm, hardcover
  • Language: English English

This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting are presented. These models are applied in different circumstances and show highly positive results. This reprint is intended for both researchers related to energy management and those related to forecasting, especially power load.

Reviews

  • No reviews
0 customers have rated this item.
5
0%
4
0%
3
0%
2
0%
1
0%
(will not be displayed)