Nonlinear fuzzy forecasting system for wind speed interval forecasting based on self-adaption feature selecting and Bi-LSTM
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Nonlinear fuzzy forecasting system for wind speed interval forecasting based on self-adaption feature selecting and Bi-LSTM
Authors
Keywords
-
Journal
Signal Image and Video Processing
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2023-11-03
DOI
10.1007/s11760-023-02759-w
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Wind speed forecasting system based on gated recurrent units and convolutional spiking neural networks
- (2021) Danxiang Wei et al. APPLIED ENERGY
- A data-driven interval forecasting model for building energy prediction using attention-based LSTM and fuzzy information granulation
- (2021) Yue Li et al. Sustainable Cities and Society
- 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
- Short-term wind speed forecasting based on the Jaya-SVM model
- (2020) Mingshuai Liu et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- A combined model based on data preprocessing strategy and multi-objective optimization algorithm for short-term wind speed forecasting
- (2019) Xinsong Niu et al. APPLIED ENERGY
- Multi-step short-term wind speed forecasting approach based on multi-scale dominant ingredient chaotic analysis, improved hybrid GWO-SCA optimization and ELM
- (2019) Wenlong Fu et al. ENERGY CONVERSION AND MANAGEMENT
- Application of a new information priority accumulated grey model with time power to predict short-term wind turbine capacity
- (2019) Jie Xia et al. JOURNAL OF CLEANER PRODUCTION
- Wind power forecasting based on singular spectrum analysis and a new hybrid Laguerre neural network
- (2019) Cong Wang et al. APPLIED ENERGY
- A novel combined forecasting system for air pollutants concentration based on fuzzy theory and optimization of aggregation weight
- (2019) Hufang Yang et al. APPLIED SOFT COMPUTING
- Multi-step wind speed forecasting based on a hybrid decomposition technique and an improved back-propagation neural network
- (2018) Zongxi Qu et al. RENEWABLE ENERGY
- A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting
- (2017) Chu Zhang et al. ENERGY CONVERSION AND MANAGEMENT
- Direct interval forecasting of wind speed using radial basis function neural networks in a multi-objective optimization framework
- (2016) Chi Zhang et al. NEUROCOMPUTING
- Wind speed forecasting approach using secondary decomposition algorithm and Elman neural networks
- (2015) Hui Liu et al. APPLIED ENERGY
- Variational Mode Decomposition
- (2014) Konstantin Dragomiretskiy et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- A neural network-GARCH-based method for construction of Prediction Intervals
- (2012) Abbas Khosravi et al. ELECTRIC POWER SYSTEMS RESEARCH
- A case study on a hybrid wind speed forecasting method using BP neural network
- (2011) Zhen-hai Guo et al. KNOWLEDGE-BASED SYSTEMS
- Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals
- (2010) A Khosravi et al. IEEE TRANSACTIONS ON NEURAL NETWORKS
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started