An evolutionary robust solar radiation prediction model based on WT-CEEMDAN and IASO-optimized outlier robust extreme learning machine
出版年份 2022 全文链接
标题
An evolutionary robust solar radiation prediction model based on WT-CEEMDAN and IASO-optimized outlier robust extreme learning machine
作者
关键词
-
出版物
APPLIED ENERGY
Volume 322, Issue -, Pages 119518
出版商
Elsevier BV
发表日期
2022-06-28
DOI
10.1016/j.apenergy.2022.119518
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Evaluation of machine learning models for predicting daily global and diffuse solar radiation under different weather/pollution conditions
- (2022) Dongyu Jia et al. RENEWABLE ENERGY
- Short/medium term solar power forecasting of Chhattisgarh state of India using modified TLBO optimized ELM
- (2021) Raj Kumar Sahu et al. Engineering Science and Technology-An International Journal-JESTECH
- An improved atom search optimization with dynamic opposite learning and heterogeneous comprehensive learning
- (2021) Pu Sun et al. APPLIED SOFT COMPUTING
- An integrated framework of Bi-directional long-short term memory (BiLSTM) based on sine cosine algorithm for hourly solar radiation forecasting
- (2021) Tian Peng et al. ENERGY
- Weighted regularized extreme learning machine to model the discharge coefficient of side slots
- (2021) Farzad Hasani et al. FLOW MEASUREMENT AND INSTRUMENTATION
- Integrated framework of extreme learning machine (ELM) based on improved atom search optimization for short-term wind speed prediction
- (2021) Lei Hua et al. ENERGY CONVERSION AND MANAGEMENT
- Daily natural gas load forecasting based on the combination of long short term memory, local mean decomposition, and wavelet threshold denoising algorithm
- (2021) Shanbi Peng et al. Journal of Natural Gas Science and Engineering
- An enhanced sitting–sizing scheme for shunt capacitors in radial distribution systems using improved atom search optimization
- (2020) Rizk M. Rizk-Allah et al. NEURAL COMPUTING & APPLICATIONS
- Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks
- (2020) Bixuan Gao et al. RENEWABLE ENERGY
- Evaluation and development of empirical models for estimating daily and monthly mean daily diffuse horizontal solar radiation for different climatic regions of China
- (2019) Junliang Fan et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Comparison of BP, PSO-BP and statistical models for predicting daily global solar radiation in arid Northwest China
- (2019) Yixuan Zhang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Evaluation of temperature-based machine learning and empirical models for predicting daily global solar radiation
- (2019) Yu Feng et al. ENERGY CONVERSION AND MANAGEMENT
- Evaluation and development of temperature-based empirical models for estimating daily global solar radiation in humid regions
- (2018) Junliang Fan et al. ENERGY
- A novel atom search optimization for dispersion coefficient estimation in groundwater
- (2018) Weiguo Zhao et al. Future Generation Computer Systems-The International Journal of eScience
- A New Radiative Transfer Method for Solar Radiation in a Vertically Internally Inhomogeneous Medium
- (2018) Feng Zhang et al. JOURNAL OF THE ATMOSPHERIC SCIENCES
- Short-term photovoltaic solar power forecasting using a hybrid Wavelet-PSO-SVM model based on SCADA and Meteorological information
- (2018) Abinet Tesfaye Eseye et al. RENEWABLE ENERGY
- Assessment of SVM, empirical and ANN based solar radiation prediction models with most influencing input parameters
- (2018) R. Meenal et al. RENEWABLE ENERGY
- A new empirical model for forecasting the diffuse solar radiation over Sahara in the Algerian Big South
- (2018) Nadjem Bailek et al. RENEWABLE ENERGY
- Assessment of different combinations of meteorological parameters for predicting daily global solar radiation using artificial neural networks
- (2018) Y. El Mghouchi et al. BUILDING AND ENVIRONMENT
- Fast short-term global solar irradiance forecasting with wrapper mutual information
- (2018) Hassen Bouzgou et al. RENEWABLE ENERGY
- Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach
- (2017) Stéphanie Monjoly et al. ENERGY
- A novel probabilistic wind speed forecasting based on combination of the adaptive ensemble of on-line sequential ORELM (Outlier Robust Extreme Learning Machine) and TVMCF (time-varying mixture copula function)
- (2017) Xiangang Peng et al. ENERGY CONVERSION AND MANAGEMENT
- Composite quantile regression extreme learning machine with feature selection for short-term wind speed forecasting: A new approach
- (2017) Weiqin Zheng et al. ENERGY CONVERSION AND MANAGEMENT
- 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
- A comparison of the performance of some extreme learning machine empirical models for predicting daily horizontal diffuse solar radiation in a region of southern Iran
- (2017) Seyed Hossein Hosseini Nazhad et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Short term solar irradiance forecasting using a mixed wavelet neural network
- (2016) Vishal Sharma et al. RENEWABLE ENERGY
- Forecasting solar radiation using an optimized hybrid model by Cuckoo Search algorithm
- (2015) Jianzhou Wang et al. ENERGY
- Investigating the performance of support vector machine and artificial neural networks in predicting solar radiation on a tilted surface: Saudi Arabia case study
- (2015) Makbul A.M. Ramli et al. ENERGY CONVERSION AND MANAGEMENT
- Outlier-robust extreme learning machine for regression problems
- (2015) Kai Zhang et al. NEUROCOMPUTING
- A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran
- (2012) Elham Sadat Mostafavi et al. ENERGY
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