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Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality.
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
This work performs a comparative study on the problem of Short-Term Load Forecast, by using different classes of state-of-the-art Recurrent Neural Networks.
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
... short-term wind power forecasting. ISA Trans 108:58–68 69. Vidya S, Janani ESV (2021) Wind speed multistep forecasting model using ... long short-term memory neural network. Energy 214:118980 71. Emeksiz C, Tan M (2022) Multi-step wind ...
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
Succinct and understandable, this book is a step-by-step guide to the mathematics and construction of electrical load forecasting models.
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
This book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations.
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks.
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
... data analytical demand response scheme for peak load reduction in smart grid. IEEE Trans Indus Electron 65(11):8993–9004 21. Keles D, Scelle J, Paraschiv F, Fichtner W (2016) Extended forecast methods for day-ahead electricity spot ...
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting.
Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks from books.google.com
... Networks, 5(2), 157–166. doi:10.1109/72.279181 PMID:18267787 Bi, J.-W., Han, T.-Y., & Li, H. (2020). International tourism demand forecasting with ... Long Short-Term Memory. Neural 36 Deep Learning and Machine Learning Techniques.