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Decomposition-based hybrid wind speed forecasting model using deep bidirectional LSTM networks
The goal of sustainable development can be attained by the efficient management of
renewable energy resources. Wind energy is attracting attention worldwide due to its …
renewable energy resources. Wind energy is attracting attention worldwide due to its …
Short term wind speed forecasting using artificial and wavelet neural networks with and without wavelet filtered data based on feature selections technique
Wind speed forecasting plays a crucial role in enhancing the efficiency, reliability, and
profitability of renewable energy systems. Accurate wind speed forecasting optimizes energy …
profitability of renewable energy systems. Accurate wind speed forecasting optimizes energy …
Patient visit forecasting in an emergency department using a deep neural network approach
Purpose This study aims to investigate the factors affecting daily demand in an emergency
department (ED) and to provide a forecasting tool in a public hospital for horizons of up to …
department (ED) and to provide a forecasting tool in a public hospital for horizons of up to …
[PDF][PDF] Prediction by a hybrid of wavelet transform and long-short-term-memory neural network
Data originating from some specific fields, for instance tourist arrivals, may exhibit a high
degree of fluctuations as well as non-linear characteristics due to time varying behaviors …
degree of fluctuations as well as non-linear characteristics due to time varying behaviors …
Short-term wind speed forecast with low loss of information based on feature generation of OSVD
N Huang, Y Wu, G Cai, H Zhu, C Yu, L Jiang… - Ieee …, 2019 - ieeexplore.ieee.org
Improving the accuracy of wind speed forecast can reduce the randomness and uncertainty
of the wind power output and effectively improve a system's wind power accommodation …
of the wind power output and effectively improve a system's wind power accommodation …
A Wavelet-based hybrid multi-step Wind Speed Forecasting model using LSTM and SVR
Wind energy, one of the greatest progressing renewable energy sources, becomes more
significant for sustainable development and environmental protection. Its intermittent nature …
significant for sustainable development and environmental protection. Its intermittent nature …
A range-based approach for long-term forecast of weather using probabilistic markov model
Weather forecasts serve to incline individual behaviors and interactions, commercial
intentions and organizational efforts. A normal user is usually indifferent to weather statistics …
intentions and organizational efforts. A normal user is usually indifferent to weather statistics …
Modeling and forecasting US presidential election using learning algorithms
The primary objective of this research is to obtain an accurate forecasting model for the US
presidential election. To identify a reliable model, artificial neural networks (ANN) and …
presidential election. To identify a reliable model, artificial neural networks (ANN) and …
EEMD-based Wind Speed Forecasting system using Bidirectional LSTM networks
Wind energy is enticing attention worldwide due to its renewable nature. For the stable
functioning of wind turbines in wind power generation, wind speed needs to be predicted …
functioning of wind turbines in wind power generation, wind speed needs to be predicted …
Time series forecasting of styrene price using a hybrid ARIMA and neural network model
AE Ghahnavieh - Independent Journal of Management & …, 2019 - paulorodrigues.pro.br
Every player in the market has a greater need to know about the smallest change in the
market. Therefore, the ability to see what is ahead is a valuable advantage. The purpose of …
market. Therefore, the ability to see what is ahead is a valuable advantage. The purpose of …