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A review of applications of artificial intelligent algorithms in wind farms
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ARTIFICIAL INTELLIGENCE REVIEW (2020)
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Yongqi Liu et al.
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A novel deep learning ensemble model with data denoising for short-term wind speed forecasting
Zhiyun Peng et al.
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Application of hybrid model based on double decomposition, error correction and deep learning in short-term wind speed prediction
Zherui Ma et al.
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Wind power forecasting using attention-based gated recurrent unit network
Zhewen Niu et al.
ENERGY (2020)
A hybrid model based on data preprocessing strategy and error correction system for wind speed forecasting
Ying Deng et al.
ENERGY CONVERSION AND MANAGEMENT (2020)
A hybrid wind speed forecasting model using stacked autoencoder and LSTM
K. U. Jaseena et al.
JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY (2020)
Short-term wind speed forecasting framework based on stacked denoising auto-encoders with rough ANN
Hamidreza Jahangir et al.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS (2020)
Multi-step wind speed forecasting based on hybrid multi-stage decomposition model and long short-term memory neural network
Sinvaldo Rodrigues Moreno et al.
ENERGY CONVERSION AND MANAGEMENT (2020)
Wind speed forecasting using a new multi-factor fusion and multi-resolution ensemble model with real-time decomposition and adaptive error correction
Hui Liu et al.
ENERGY CONVERSION AND MANAGEMENT (2020)
A Prediction Model for Ultra-Short-Term Output Power of Wind Farms Based on Deep Learning
Y. S. Wang et al.
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL (2020)
Wind speed forecasting using deep neural network with feature selection
Xiangjie Liu et al.
NEUROCOMPUTING (2020)
Deterministic and probabilistic multi-step forecasting for short-term wind speed based on secondary decomposition and a deep learning method
Ling Xiang et al.
ENERGY CONVERSION AND MANAGEMENT (2020)
China in global wind power development: Role, status and impact
Shijie Zhang et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)
Forecasting energy consumption and wind power generation using deep echo state network
Huanling Hu et al.
RENEWABLE ENERGY (2020)
Short-Term Wind Speed Forecasting With Principle-Subordinate Predictor Based on Conv-LSTM and Improved BPNN
Gonggui Chen et al.
IEEE ACCESS (2020)
Wind speed and wind direction forecasting using echo state network with nonlinear functions
Mohammad Amin Chitsazan et al.
RENEWABLE ENERGY (2019)
Multifactor spatio-temporal correlation model based on a combination of convolutional neural network and long short-term memory neural network for wind speed forecasting
Yong Chen et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
LSTM-EFG for wind power forecasting based on sequential correlation features
Ruiguo Yu et al.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2019)
Wind power generation: A review and a research agenda
Soraida Aguilar Vargas et al.
JOURNAL OF CLEANER PRODUCTION (2019)
Wind Power Short-Term Prediction Based on LSTM and Discrete Wavelet Transform
Yao Liu et al.
APPLIED SCIENCES-BASEL (2019)
Long Short-Term Memory Network based on Neighborhood Gates for processing complex causality in wind speed prediction
Zhendong Zhang et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Data-driven wind speed forecasting using deep feature extraction and LSTM
Yu-Xi Wu et al.
IET RENEWABLE POWER GENERATION (2019)
A gated recurrent unit neural networks based wind speed error correction model for short-term wind power forecasting
Min Ding et al.
NEUROCOMPUTING (2019)
Data processing strategies in wind energy forecasting models and applications: A comprehensive review
Hui Liu et al.
APPLIED ENERGY (2019)
Wind speed prediction method using Shared Weight Long Short-Term Memory Network and Gaussian Process Regression
Zhendong Zhang et al.
APPLIED ENERGY (2019)
Hybrid forecasting system based on an optimal model selection strategy for different wind speed forecasting problems
Qingguo Zhou et al.
APPLIED ENERGY (2019)
Wind speed prediction method based on Empirical Wavelet Transform and New Cell Update Long Short-Term Memory network
Shaoqian Pei et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Deterministic wind energy forecasting: A review of intelligent predictors and auxiliary methods
Hui Liu et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Ensemble spatiotemporal forecasting of solar irradiation using variational Bayesian convolutional gate recurrent unit network
Yongqi Liu et al.
APPLIED ENERGY (2019)
A new hybrid framework for probabilistic wind speed prediction using deep feature selection and multi-error modification
Yan Jiang et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
A Review on Hybrid Empirical Mode Decomposition Models for Wind Speed and Wind Power Prediction
Neeraj Bokde et al.
ENERGIES (2019)
A novel combined model based on echo state network for multi-step ahead wind speed forecasting: A case study of NREL
Yanhua Chen et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Forecasting a short-term wind speed using a deep belief network combined with a local predictor
Y. Yu et al.
IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING (2019)
A cascaded deep learning wind power prediction approach based on a two-layer of mode decomposition
Hao Yin et al.
ENERGY (2019)
Repeated wavelet transform based ARIMA model for very short-term wind speed forecasting
Aasim et al.
RENEWABLE ENERGY (2019)
Synthesis of 4,5-Dihydropyrazoles via Palladium-Catalyzed Cyclization Reactions of β,γ-Unsaturated Hydrazones with Aryl Iodides
Rongcai Ding et al.
ORGANOMETALLICS (2019)
Smart wind speed deep learning based multi-step forecasting model using singular spectrum analysis, convolutional Gated Recurrent Unit network and Support Vector Regression
Hui Liu et al.
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Improving forecasting accuracy of daily energy consumption of office building using time series analysis based on wavelet transform decomposition
Chengkuan Fang et al.
SUSTAINABLE BUILT ENVIRONMENT CONFERENCE 2019 TOKYO (SBE19TOKYO) - BUILT ENVIRONMENT IN AN ERA OF CLIMATE CHANGE: HOW CAN CITIES AND BUILDINGS ADAPT? (2019)
A survey of artificial neural network in wind energy systems
Alberto Pliego Marugan et al.
APPLIED ENERGY (2018)
Wind Speed Prediction with Spatio-Temporal Correlation: A Deep Learning Approach
Qiaomu Zhu et al.
ENERGIES (2018)
Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory
Erick Lopez et al.
ENERGIES (2018)
Enhancing Short-Term Wind Power Forecasting through Multiresolution Analysis and Echo State Networks
Hugo Tavares Vieira Gouveia et al.
ENERGIES (2018)
Smart deep learning based wind speed prediction model using wavelet packet decomposition, convolutional neural network and convolutional long short term memory network
Hui Liu et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
Multi-step wind speed forecasting using EWT decomposition, LSTM principal computing, RELM subordinate computing and IEWT reconstruction
Yanfei Li et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network
Hui Liu et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM
Hui Liu et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
Pore-Scale Modeling of Mixing-Induced Reaction Transport through a Single Self-Affine Fracture
Zhi Dou et al.
GEOFLUIDS (2018)
Forecasting the High Penetration of Wind Power on Multiple Scales Using Multi-to-Multi Mapping
Jie Yan et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2018)
A novel wind speed prediction method: Hybrid of correlation-aided DWT, LSSVM and GARCH
Yan Jiang et al.
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS (2018)
Visual interpretability for deep learning: a survey
Quan-shi Zhang et al.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING (2018)
A vector autoregression weather model for electricity supply and demand modeling
Yixian Liu et al.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY (2018)
Multi-step ahead wind speed prediction based on optimal feature extraction, long short term memory neural network and error correction strategy
Jujie Wang et al.
APPLIED ENERGY (2018)
Deep belief network based k-means cluster approach for short-term wind power forecasting
Kejun Wang et al.
ENERGY (2018)
Wind Speed Forecasting Method Using EEMD and the Combination Forecasting Method Based on GPR and LSTM
Yuansheng Huang et al.
SUSTAINABILITY (2018)
A new high-dimensional time series approach for wind speed, wind direction and air pressure forecasting
Daniel Ambach et al.
ENERGY (2017)
Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine
Xiaohui Yuan et al.
ENERGY (2017)
Deep Multimodal Learning A survey on recent advances and trends
Dhanesh Ramachandram et al.
IEEE SIGNAL PROCESSING MAGAZINE (2017)
Rough Deep Neural Architecture for Short-Term Wind Speed Forecasting
Mahdi Khodayar et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2017)
One-day ahead wind speed/power prediction based on polynomial autoregressive model
Oktay Karakus et al.
IET RENEWABLE POWER GENERATION (2017)
Deterministic and probabilistic wind power forecasting using a variational Bayesian-based adaptive robust multi-kernel regression model
Yun Wang et al.
APPLIED ENERGY (2017)
Wind power prediction using deep neural network based meta regression and transfer learning
Aqsa Saeed Qureshi et al.
APPLIED SOFT COMPUTING (2017)
Deep learning based ensemble approach for probabilistic wind power forecasting
Huai-zhi Wang et al.
APPLIED ENERGY (2017)
Wind Power Fundamentals
Alexander Kalmikov
WIND ENERGY ENGINEERING: A HANDBOOK FOR ONSHORE AND OFFSHORE WIND TURBINES (2017)
Deep belief network based deterministic and probabilistic wind speed forecasting approach
H. Z. Wang et al.
APPLIED ENERGY (2016)
Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model
Erasmo Cadenas et al.
ENERGIES (2016)
A Gaussian process regression based hybrid approach for short-term wind speed prediction
Chi Zhang et al.
ENERGY CONVERSION AND MANAGEMENT (2016)
Linear and non-linear autoregressive models for short-term wind speed forecasting
M. Lydia et al.
ENERGY CONVERSION AND MANAGEMENT (2016)
ARIMA-Based Frequency-Decomposed Modeling of Wind Speed Time Series
Kalid Yunus et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2016)
A hybrid model of EMD and multiple-kernel RVR algorithm for wind speed prediction
Sheng-wei Fei
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2016)
Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models
Jianzhou Wang et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2016)
Transfer learning for short-term wind speed prediction with deep neural networks
Qinghua Hu et al.
RENEWABLE ENERGY (2016)
Recursive wind speed forecasting based on Hammerstein Auto-Regressive model
Othman Ait Maatallah et al.
APPLIED ENERGY (2015)
An EMD-recursive ARIMA method to predict wind speed for railway strong wind warning system
Hui Liu et al.
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS (2015)
Daily wind speed forecasting through hybrid KF-ANN model based on ARIMA
Osamah Basheer Shukur et al.
RENEWABLE ENERGY (2015)
Short-term wind speed forecasting based on spectral clustering and optimised echo state networks
Da Liu et al.
RENEWABLE ENERGY (2015)
Predictive Deep Boltzmann Machine for Multiperiod Wind Speed Forecasting
Chun-Yang Zhang et al.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2015)
A Hybrid Intelligent Model for Deterministic and Quantile Regression Approach for Probabilistic Wind Power Forecasting
Ashraf Ul Haque et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2014)
Techniques of applying wavelet de-noising into a combined model for short-term load forecasting
Jujie Wang et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2014)
Current status and future advances for wind speed and power forecasting
Jaesung Jung et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2014)
Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction
Hui Liu et al.
APPLIED ENERGY (2012)
Markov-switching autoregressive models for wind time series
Pierre Ailliot et al.
ENVIRONMENTAL MODELLING & SOFTWARE (2012)
An Efficient Learning Procedure for Deep Boltzmann Machines
Ruslan Salakhutdinov et al.
NEURAL COMPUTATION (2012)
Data mining and wind power prediction: A literature review
Ilhami Colak et al.
RENEWABLE ENERGY (2012)
Research on Fluidic Gyroscope Signal Processing Circuit
Xing Wang et al.
AUTOMATIC MANUFACTURING SYSTEMS II, PTS 1 AND 2 (2012)
ARMA based approaches for forecasting the tuple of wind speed and direction
Ergin Erdem et al.
APPLIED ENERGY (2011)
Spatio-temporal analysis and modeling of short-term wind power forecast errors
Julija Tastu et al.
WIND ENERGY (2011)
Review of Evaluation Criteria and Main Methods of Wind Power Forecasting
Xin Zhao et al.
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON SMART GRID AND CLEAN ENERGY TECHNOLOGIES (ICSGCE 2011) (2011)
Harnessing Web 2.0 for ERP Implementations
Harris Wu et al.
IEEE SOFTWARE (2009)
Day-ahead wind speed forecasting using f-ARIMA models
Rajesh G. Kavasseri et al.
RENEWABLE ENERGY (2009)
Regime-switching modelling of the fluctuations of offshore wind generation
P. Pinson et al.
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS (2008)
Using quantile regression to extend an existing wind power forecasting system with probabilistic forecasts
HA Nielsen et al.
WIND ENERGY (2006)
Forecast of hourly average wind speed with ARMA models in Navarre (Spain)
JL Torres et al.
SOLAR ENERGY (2005)
Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication
H Jaeger et al.
SCIENCE (2004)
Forecasting and simulating wind speed in Corsica by using an autoregressive model
P Poggi et al.
ENERGY CONVERSION AND MANAGEMENT (2003)
A comparison of various forecasting techniques applied to mean hourly wind speed time series
A Sfetsos
RENEWABLE ENERGY (2000)
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