Short term wind speed prediction based on evolutionary support vector regression algorithms
S Salcedo-Sanz, EG Ortiz-Garcı… - Expert Systems with …, 2011 - Elsevier
Hyper-parameters estimation in regression Support Vector Machines (SVMr) is one of the
main problems in the application of this type of algorithms to learning problems. This is a hot …
main problems in the application of this type of algorithms to learning problems. This is a hot …
[HTML][HTML] Short-term wind speed forecasting using an optimized three-phase convolutional neural network fused with bidirectional long short-term memory network …
Wind energy is an environment friendly, low-carbon, and cost-effective renewable energy
source. It is, however, difficult to integrate wind energy into a mixed energy grid due to its …
source. It is, however, difficult to integrate wind energy into a mixed energy grid due to its …
A novel forecasting model based on a hybrid processing strategy and an optimized local linear fuzzy neural network to make wind power forecasting: A case study of …
As a crucial issue in the wind power industry, it is a tough and challenging task to predict the
wind power accurately because of its nonlinearity, non-stationary and chaos. In this paper …
wind power accurately because of its nonlinearity, non-stationary and chaos. In this paper …
A hybrid wind speed forecasting system based on a 'decomposition and ensemble'strategy and fuzzy time series
H Yang, Z Jiang, H Lu - Energies, 2017 - mdpi.com
Accurate and stable wind speed forecasting is of critical importance in the wind power
industry and has measurable influence on power-system management and the stability of …
industry and has measurable influence on power-system management and the stability of …
The prediction of the wind speed at different heights by machine learning methods
In Turkey, many enterprisers started to make investment on renewable energy systems after
new legal regulations and stimulus packages about production of renewable energy were …
new legal regulations and stimulus packages about production of renewable energy were …
A framework-based wind forecasting to assess wind potential with improved grey wolf optimization and support vector regression
SS Hameed, R Ramadoss, K Raju, GM Shafiullah - Sustainability, 2022 - mdpi.com
Wind energy is one of the most promising alternates of fossil fuels because of its abundant
availability, low cost, and pollution-free attributes. Wind potential estimation, wind …
availability, low cost, and pollution-free attributes. Wind potential estimation, wind …
Short‐Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm
This paper develops an effectively intelligent model to forecast short‐term wind speed
series. A hybrid forecasting technique is proposed based on recurrence plot (RP) and …
series. A hybrid forecasting technique is proposed based on recurrence plot (RP) and …
Modelling monthly mean air temperature using artificial neural network, adaptive neuro-fuzzy inference system and support vector regression methods: A case of study …
E Yakut, S Süzülmüş - Network: Computation in Neural Systems, 2020 - Taylor & Francis
The accurate modelling and prediction of air temperature values is an exceptionally
important meteorological variable that affects in many areas. The present study is aimed at …
important meteorological variable that affects in many areas. The present study is aimed at …
Research and application based on adaptive boosting strategy and modified CGFPA algorithm: a case study for wind speed forecasting
Wind energy is increasingly considered one of the most promising sustainable energy
sources for its characteristics of cleanliness without any pollution. Wind speed forecasting is …
sources for its characteristics of cleanliness without any pollution. Wind speed forecasting is …
[PDF][PDF] A hybrid GMDH and least squares support vector machines in time series forecasting
Time series consists of complex nonlinear and chaotic patterns that are difficult to forecast.
This paper proposes a novel hybrid forecasting model which combines the group method of …
This paper proposes a novel hybrid forecasting model which combines the group method of …