Research and Application of a Hybrid Wind Energy Forecasting System Based on Data Processing and an Optimized Extreme Learning Machine
出版年份 2018 全文链接
标题
Research and Application of a Hybrid Wind Energy Forecasting System Based on Data Processing and an Optimized Extreme Learning Machine
作者
关键词
-
出版物
Energies
Volume 11, Issue 7, Pages 1712
出版商
MDPI AG
发表日期
2018-07-02
DOI
10.3390/en11071712
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting
- (2018) Jingjing Song et al. APPLIED ENERGY
- A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting
- (2018) et al. Energies
- Innovative hybrid models for forecasting time series applied in wind generation based on the combination of time series models with artificial neural networks
- (2018) Henrique do Nascimento Camelo et al. ENERGY
- Research and application of a hybrid forecasting framework based on multi-objective optimization for electrical power system
- (2018) Jianzhou Wang et al. ENERGY
- Multi-step ahead forecasting in electrical power system using a hybrid forecasting system
- (2018) Pei Du et al. RENEWABLE ENERGY
- Research and application of a combined model based on multi-objective optimization for multi-step ahead wind speed forecasting
- (2017) Jianzhou Wang et al. ENERGY
- Research and application of a novel hybrid forecasting system based on multi-objective optimization for wind speed forecasting
- (2017) Pei Du et al. ENERGY CONVERSION AND MANAGEMENT
- An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed
- (2016) Jing Zhao et al. APPLIED ENERGY
- A combined model based on multiple seasonal patterns and modified firefly algorithm for electrical load forecasting
- (2016) Liye Xiao et al. APPLIED ENERGY
- Optimum wavelet based masking for the contrast enhancement of medical images using enhanced cuckoo search algorithm
- (2016) Ebenezer Daniel et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Using artificial neural networks for temporal and spatial wind speed forecasting in Iran
- (2016) Younes Noorollahi et al. ENERGY CONVERSION AND MANAGEMENT
- Wind speed forecasting using FEEMD echo state networks with RELM in Hebei, China
- (2016) Wei Sun et al. ENERGY CONVERSION AND MANAGEMENT
- Development of renewable energy in Australia and China: A comparison of policies and status
- (2016) Yaping Hua et al. RENEWABLE ENERGY
- Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method
- (2016) Shouxiang Wang et al. RENEWABLE ENERGY
- Wind speed forecasting approach using secondary decomposition algorithm and Elman neural networks
- (2015) Hui Liu et al. APPLIED ENERGY
- Recursive wind speed forecasting based on Hammerstein Auto-Regressive model
- (2015) Othman Ait Maatallah et al. APPLIED ENERGY
- A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting
- (2015) Liye Xiao et al. ENERGY
- A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model
- (2015) Jianzhou Wang et al. ENERGY
- Kalman filter-based method for Online Sequential Extreme Learning Machine for regression problems
- (2015) Jarley Palmeira Nobrega et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Improved extreme learning machine for multivariate time series online sequential prediction
- (2015) Xinying Wang et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Improved cuckoo search for reliability optimization problems
- (2012) Ehsan Valian et al. COMPUTERS & INDUSTRIAL ENGINEERING
- Australian renewable energy progress
- (2010) A. Zahedi RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- A hybrid statistical method to predict wind speed and wind power
- (2010) Hui Liu et al. RENEWABLE ENERGY
- Wind Power Density Forecasting Using Ensemble Predictions and Time Series Models
- (2009) James W. Taylor et al. IEEE TRANSACTIONS ON ENERGY CONVERSION
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started