Decomposition-based hybrid wind speed forecasting model using deep bidirectional LSTM networks

KU Jaseena, BC Kovoor - Energy Conversion and Management, 2021‏ - Elsevier
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 …

Short term wind speed forecasting using artificial and wavelet neural networks with and without wavelet filtered data based on feature selections technique

Y Ali, HH Aly - Engineering Applications of Artificial Intelligence, 2024‏ - Elsevier
Wind speed forecasting plays a crucial role in enhancing the efficiency, reliability, and
profitability of renewable energy systems. Accurate wind speed forecasting optimizes energy …

Patient visit forecasting in an emergency department using a deep neural network approach

M Yousefi, M Yousefi, M Fathi, FS Fogliatto - Kybernetes, 2020‏ - emerald.com
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 …

[PDF][PDF] Prediction by a hybrid of wavelet transform and long-short-term-memory neural network

P Sugiartawan, R Pulungan… - International Journal of …, 2017‏ - researchgate.net
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 …

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 …

A Wavelet-based hybrid multi-step Wind Speed Forecasting model using LSTM and SVR

J KU, BC Kovoor - Wind Engineering, 2021‏ - journals.sagepub.com
Wind energy, one of the greatest progressing renewable energy sources, becomes more
significant for sustainable development and environmental protection. Its intermittent nature …

A range-based approach for long-term forecast of weather using probabilistic markov model

S Kaneriya, S Tanwar, S Buddhadev… - 2018 IEEE …, 2018‏ - ieeexplore.ieee.org
Weather forecasts serve to incline individual behaviors and interactions, commercial
intentions and organizational efforts. A normal user is usually indifferent to weather statistics …

Modeling and forecasting US presidential election using learning algorithms

M Zolghadr, SAA Niaki, STA Niaki - Journal of Industrial Engineering …, 2018‏ - Springer
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 …

EEMD-based Wind Speed Forecasting system using Bidirectional LSTM networks

KU Jaseena, BC Kovoor - 2021 International Conference on …, 2021‏ - ieeexplore.ieee.org
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 …

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 …