标题
Wind Power Generation Forecast Based on Multi-Step Informer Network
作者
关键词
-
出版物
Energies
Volume 15, Issue 18, Pages 6642
出版商
MDPI AG
发表日期
2022-09-13
DOI
10.3390/en15186642
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。- Interpretable machine learning: Fundamental principles and 10 grand challenges
- (2022) Cynthia Rudin et al. Statistics Surveys
- Ultra‐short‐term multi‐step wind power forecasting based on CNN‐LSTM
- (2021) Qianyu Wu et al. IET Renewable Power Generation
- A novel genetic LSTM model for wind power forecast
- (2021) Farah Shahid et al. ENERGY
- Optimization scheme of wind energy prediction based on artificial intelligence
- (2021) Yagang Zhang et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- Application of autoregressive dynamic adaptive (ARDA) model in real-time wind power forecasting
- (2021) Fei Zhang et al. RENEWABLE ENERGY
- An engineer's guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating causality, forced goodness, and the false perception of inference
- (2021) M.Z. Naser AUTOMATION IN CONSTRUCTION
- A review of wind speed and wind power forecasting with deep neural networks
- (2021) Yun Wang et al. APPLIED ENERGY
- Short-term self consumption PV plant power production forecasts based on hybrid CNN-LSTM, ConvLSTM models
- (2021) Ali Agga et al. RENEWABLE ENERGY
- Adaptive VMD based optimized deep learning mixed kernel ELM autoencoder for single and multistep wind power forecasting
- (2021) Vijaya Krishna Rayi et al. ENERGY
- A novel wavenets long short term memory paradigm for wind power prediction
- (2020) Farah Shahid et al. APPLIED ENERGY
- Wind power forecasting of an offshore wind turbine based on high-frequency SCADA data and deep learning neural network
- (2020) Zi Lin et al. ENERGY
- A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets
- (2020) Gholamreza Memarzadeh et al. ENERGY CONVERSION AND MANAGEMENT
- Uncertain wind power forecasting using LSTM-based prediction interval
- (2020) Abhishek Banik et al. IET Renewable Power Generation
- Short-term wind speed forecasting based on the Jaya-SVM model
- (2020) Mingshuai Liu et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- An improved residual-based convolutional neural network for very short-term wind power forecasting
- (2020) Ceyhun Yildiz et al. ENERGY CONVERSION AND MANAGEMENT
- Deterministic and probabilistic wind speed forecasting with de-noising-reconstruction strategy and quantile regression based algorithm
- (2020) Jianming Hu et al. RENEWABLE ENERGY
- A Hybrid Deep Learning Model and Comparison for Wind Power Forecasting Considering Temporal-Spatial Feature Extraction
- (2020) Hao Zhen et al. Sustainability
- A Kalman filter-based bottom-up approach for household short-term load forecast
- (2019) Zhuang Zheng et al. APPLIED ENERGY
- Day ahead powerful probabilistic wind power forecast using combined intelligent structure and fuzzy clustering algorithm
- (2019) Lei Li et al. ENERGY
- National and global wind resource assessment under six wind turbine installation scenarios
- (2018) Christopher Jung et al. ENERGY CONVERSION AND MANAGEMENT
- Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM
- (2018) Hui Liu et al. ENERGY CONVERSION AND MANAGEMENT
- Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference station data
- (2018) Ravinesh C. Deo et al. RENEWABLE ENERGY
- A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data
- (2018) Amir Sharifian et al. RENEWABLE ENERGY
- A review and discussion of decomposition-based hybrid models for wind energy forecasting applications
- (2018) Zheng Qian et al. APPLIED ENERGY
- Short-term wind speed forecasting using a hybrid model
- (2017) Ping Jiang et al. ENERGY
- Non-parametric hybrid models for wind speed forecasting
- (2017) Qinkai Han et al. ENERGY CONVERSION AND MANAGEMENT
- 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
- One-day ahead wind speed/power prediction based on polynomial autoregressive model
- (2017) Oktay Karakuş et al. IET Renewable Power Generation
- Deep belief network based deterministic and probabilistic wind speed forecasting approach
- (2016) H.Z. Wang et al. APPLIED ENERGY
- Short-term wind speed forecasting using empirical mode decomposition and feature selection
- (2016) Chi Zhang 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
- Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function
- (2015) Z.R. Shu et al. APPLIED ENERGY
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