Comparison of the advanced machine learning methods for better prediction accuracy of solar radiation using only temperature data: A case study
暂无分享,去创建一个
Ozgur Kisi | Salim Heddam | Mojtaba Mehraein | Slavisa Trajkovic | Amin Mirbolouki | Kulwinder Singh Parmar | O. Kisi | S. Heddam | Slaviša Trajković | M. Mehraein | Amin Mirbolouki | Kulwinder Singh Parmar
[1] André St-Hilaire,et al. A guideline to select an estimation model of daily global solar radiation between geostatistical interpolation and stochastic simulation approaches , 2017 .
[2] Gunar E. Liepins,et al. Genetic algorithms: Foundations and applications , 1990 .
[3] Jianzhou Wang,et al. A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting , 2019, Appl. Soft Comput..
[4] Pedro Antonio Gutiérrez,et al. Evolutionary artificial neural networks for accurate solar radiation prediction , 2020, Energy.
[5] A. Gürel,et al. Assessment of machine learning, time series, response surface methodology and empirical models in prediction of global solar radiation , 2020 .
[6] Russell C. Eberhart,et al. A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.
[7] C. W. Tong,et al. A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation , 2015 .
[8] W. Russell Hamon. Estimating Potential Evapotranspiration , 1960 .
[9] Mohammad Reza Safaei,et al. Diurnal thermal evaluation of an evacuated tube solar collector (ETSC) charged with graphene nanoplatelets-methanol nano-suspension , 2019, Renewable Energy.
[10] James Kennedy,et al. Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.
[11] Zhang Chunxiao,et al. The research of new daily diffuse solar radiation models modified by air quality index (AQI) in the region with heavy fog and haze , 2017 .
[12] Guoqiang Sun,et al. Application of functional deep belief network for estimating daily global solar radiation: A case study in China , 2020 .
[13] Lei Liu,et al. Particle swarm optimization algorithm: an overview , 2017, Soft Computing.
[14] Ravinesh C. Deo,et al. Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network , 2020, Energies.
[15] Chengqi Cheng,et al. A long short-term memory approach to predicting air quality based on social media data , 2020 .
[16] O. Kisi,et al. Modeling monthly streamflow in mountainous basin by MARS, GMDH-NN and DENFIS using hydroclimatic data , 2020, Neural Computing and Applications.
[17] J. Rogelj,et al. Paris Agreement climate proposals need a boost to keep warming well below 2 °C , 2016, Nature.
[18] B. Babayigit,et al. Solar radiation prediction using multi-gene genetic programming approach , 2020, Theoretical and Applied Climatology.
[19] Moo-Yeon Lee,et al. A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models , 2020, International Journal of Energy Research.
[20] Chunlüe Zhou,et al. Temperature annual cycle variations and responses to surface solar radiation in China between 1960 and 2016 , 2020, International Journal of Climatology.
[21] Lotfi A. Zadeh,et al. Fuzzy Sets , 1996, Inf. Control..
[22] A. Marzo,et al. Daily global solar radiation estimation in desert areas using daily extreme temperatures and extraterrestrial radiation , 2017 .
[23] Laurel Saito,et al. ANFIS, SVM and ANN soft-computing techniques to estimate daily global solar radiation in a warm sub-humid environment , 2017 .
[24] M. Guermoui,et al. New temperature-based predicting model for global solar radiation using support vector regression , 2020 .
[25] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[26] Min Liu,et al. The importance of short lag-time in the runoff forecasting model based on long short-term memory , 2020 .
[27] Mohamed Abd Elaziz,et al. Performance analysis of Chaotic Multi-Verse Harris Hawks Optimization: A case study on solving engineering problems , 2020, Eng. Appl. Artif. Intell..
[28] A. Abdel‐Rehim,et al. Energy and exergy analysis for stationary solar collectors using nanofluids: A review , 2020, International Journal of Energy Research.
[29] M. B. Hayat,et al. Solar energy—A look into power generation, challenges, and a solar‐powered future , 2018, International Journal of Energy Research.
[30] Ü. Ağbulut,et al. Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms , 2021 .
[31] Kulwinder Singh Parmar,et al. Neuro-fuzzy-wavelet hybrid approach to estimate the future trends of river water quality , 2019, Neural Computing and Applications.
[32] Said Jadid Abdul Kadir,et al. Binary Optimization Using Hybrid Grey Wolf Optimization for Feature Selection , 2019, IEEE Access.
[33] G. Campbell,et al. On the relationship between incoming solar radiation and daily maximum and minimum temperature , 1984 .
[34] Shuai Luo,et al. Model selection for accurate daily global solar radiation prediction in China , 2019, Journal of Cleaner Production.
[35] Changjiang Zhang,et al. Tiny‐RainNet: a deep convolutional neural network with bi‐directional long short‐term memory model for short‐term rainfall prediction , 2020, Meteorological Applications.
[36] Ling Zou,et al. Prediction and comparison of solar radiation using improved empirical models and Adaptive Neuro-Fuzzy Inference Systems , 2017 .
[37] S. Salisu,et al. Solar radiation forecasting in nigeria based on hybrid PSO-ANFIS and WT-ANFIS approach , 2019, International Journal of Electrical and Computer Engineering (IJECE).
[38] Yonghang Tai,et al. Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks , 2020 .
[39] A. Kamsin,et al. Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure , 2016 .
[40] Heming Jia,et al. A Novel Hybrid Harris Hawks Optimization for Color Image Multilevel Thresholding Segmentation , 2019, IEEE Access.
[41] Sara Atef,et al. Assessment of stacked unidirectional and bidirectional long short-term memory networks for electricity load forecasting , 2020 .
[42] R. Deo,et al. Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea , 2020, Environmental Research Letters.
[43] L. Naderloo. Prediction of solar radiation on the horizon using neural network methods, ANFIS and RSM (case study: Sarpol-e-Zahab Township, Iran) , 2020, Journal of Earth System Science.
[44] Sinan Q. Salih,et al. Global solar radiation prediction over North Dakota using air temperature : Development of novel hybrid intelligence model , 2021 .
[45] Hilmi Cenk Bayrakçi,et al. Machine learning-based improvement of empiric models for an accurate estimating process of global solar radiation , 2020 .
[46] Ali Etem Gürel,et al. Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison , 2021, Renewable and Sustainable Energy Reviews.
[47] Zaher Mundher Yaseen,et al. The implementation of univariable scheme-based air temperature for solar radiation prediction: New development of dynamic evolving neural-fuzzy inference system model , 2019, Applied Energy.
[48] Özgür Kisi,et al. Solar Radiation Estimation in Mediterranean Climate by Weather Variables Using a Novel Bayesian Model Averaging and Machine Learning Methods , 2020, Neural Processing Letters.
[49] Xiaohui Yuan,et al. An improved long short-term memory network for streamflow forecasting in the upper Yangtze River , 2020, Stochastic Environmental Research and Risk Assessment.
[50] Yunpeng Wang,et al. Long short-term memory neural network for traffic speed prediction using remote microwave sensor data , 2015 .
[51] Vahid Nourani,et al. Estimation of daily global solar radiation using wavelet regression, ANN, GEP and empirical models: A comparative study of selected temperature-based approaches , 2016 .
[52] Lifeng Wu,et al. New combined models for estimating daily global solar radiation based on sunshine duration in humid regions: A case study in South China , 2018 .
[53] Zhi-jun Teng,et al. An improved hybrid grey wolf optimization algorithm , 2018, Soft Computing.
[54] Shu-hai Guo,et al. Response of shallow soil temperature to climate change on the Qinghai–Tibetan Plateau , 2020, International Journal of Climatology.
[55] Yanfeng Liu,et al. A review on global solar radiation prediction with machine learning models in a comprehensive perspective , 2021 .
[56] Yu Feng,et al. Evaluation of temperature-based machine learning and empirical models for predicting daily global solar radiation , 2019, Energy Conversion and Management.
[57] Jürgen Schmidhuber,et al. Framewise phoneme classification with bidirectional LSTM and other neural network architectures , 2005, Neural Networks.
[58] Sultan Noman Qasem,et al. Daily global solar radiation modeling using data-driven techniques and empirical equations in a semi-arid climate , 2019, Engineering Applications of Computational Fluid Mechanics.
[59] Iskander Tlili,et al. Potential of Solar Collectors for Clean Thermal Energy Production in Smart Cities using Nanofluids: Experimental Assessment and Efficiency Improvement , 2019, Applied Sciences.
[60] Ozgur Kisi,et al. Prediction of solar radiation in China using different adaptive neuro‐fuzzy methods and M5 model tree , 2017 .
[61] Ozgur Kisi,et al. Modelling solar radiation reached to the Earth using ANFIS, NN-ARX, and empirical models (Case studies: Zahedan and Bojnurd stations) , 2015 .
[62] Hossam Faris,et al. Harris hawks optimization: Algorithm and applications , 2019, Future Gener. Comput. Syst..
[63] Saad Mekhilef,et al. Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation , 2018 .
[64] Andrew Lewis,et al. Grey Wolf Optimizer , 2014, Adv. Eng. Softw..
[65] Sandeep Dhakal,et al. Evaluation of Temperature-Based Empirical Models and Machine Learning Techniques to Estimate Daily Global Solar Radiation at Biratnagar Airport, Nepal , 2020 .
[67] Shengjun Wu,et al. Assessing the transferability of support vector machine model for estimation of global solar radiation from air temperature , 2015 .
[68] Linzhu Sun,et al. Performance of building energy supply systems using renewable energy , 2020, International Journal of Energy Research.
[69] Xiang Li,et al. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation. , 2017, Environmental pollution.
[70] John Boland,et al. A Novel Hybrid Model for Solar Radiation Forecasting Using Support Vector Machine and Bee Colony Optimization Algorithm: Review and Case Study , 2021 .
[71] Aboul Ella Hassanien,et al. Binary grey wolf optimization approaches for feature selection , 2016, Neurocomputing.
[72] Ravinesh C. Deo,et al. Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms , 2019, Applied Energy.
[73] Eric Michielssen,et al. Genetic algorithm optimization applied to electromagnetics: a review , 1997 .
[74] R. Kroebel,et al. A novel time-effective model for daily distributed solar radiation estimates across variable terrain , 2018, International Journal of Energy and Environmental Engineering.
[75] O. Kisi,et al. Pan evaporation modeling by three different neuro-fuzzy intelligent systems using climatic inputs , 2019, Arabian Journal of Geosciences.
[76] Rasu Eeswaran,et al. Forecast of short-term daily reference evapotranspiration under limited meteorological variables using a hybrid bi-directional long short-term memory model (Bi-LSTM) , 2020 .
[77] Liu Yang,et al. Comparison of daily diffuse radiation models in regions of China without solar radiation measurement , 2020 .
[78] Babak Mohammadi,et al. Estimation of solar radiation using neighboring stations through hybrid support vector regression boosted by Krill Herd algorithm , 2020, Arabian Journal of Geosciences.
[79] Guglielmo Minervino,et al. New Public Institutional Forms and Social Innovation in Urban Governance: Insights from the “Mayor’s Office of New Urban Mechanics” (MONUM) in Boston , 2019, Sustainability.
[80] Shafiqur Rehman,et al. SOLAR RADIATION OVER SAUDI ARABIA AND COMPARISONS WITH EMPIRICAL MODELS , 1998 .
[81] Alexandre Bryan Heinemann,et al. Sensitivity of APSIM/ORYZA model due to estimation errors in solar radiation , 2012 .
[82] Lifeng Wu,et al. Hybrid support vector machines with heuristic algorithms for prediction of daily diffuse solar radiation in air-polluted regions , 2020 .
[83] Haoru Li,et al. Machine learning models to quantify and map daily global solar radiation and photovoltaic power , 2020 .
[84] Hermann Ney,et al. From Feedforward to Recurrent LSTM Neural Networks for Language Modeling , 2015, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[85] F. F. Putti,et al. INFLUENCE OF THE ESTIMATED GLOBAL SOLAR RADIATION ON THE REFERENCE EVAPOTRANSPIRATION OBTAINED THROUGH THE PENMAN-MONTEITH FAO 56 METHOD , 2021 .