Cited By
View all- Khan PByun Y(2020)Genetic Algorithm Based Optimized Feature Engineering and Hybrid Machine Learning for Effective Energy Consumption PredictionIEEE Access10.1109/ACCESS.2020.30341018(196274-196286)Online publication date: 2020
Electrical load forecasting is an integral tool used by the grid operator to operate the smart power network. The information related to the electrical load is a prerequisite towards the effective and optimal operation of the power ...
Load forecasting has always played a particularly important role in the power industry. In this article, we proposed a hybrid model based on Ensemble Empirical Mode Decomposition (EEMD) and Bidirectional Long Short-Term memory (Bi-LSTM). The original ...
A suitable combination of linear and nonlinear models provides a more accurate prediction model than an individual linear or nonlinear model for forecasting time series data originating from various applications. The linear autoregressive integrated ...
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