Machine learning predictive models for optimal design of building‐integrated photovoltaic‐thermal collectors

[1]  Xinlong Feng,et al.  Multiquadric RBF-FD method for the convection-dominated diffusion problems base on Shishkin nodes , 2018 .

[2]  V. Velmurugan,et al.  Artificial neural network modeling of a photovoltaic-thermal evaporator of solar assisted heat pumps , 2015 .

[3]  Mike Duke,et al.  Estimation of photovoltaic conversion efficiency of a building integrated photovoltaic/thermal (BIPV/T) collector array using an artificial neural network , 2012 .

[4]  Song Xiang,et al.  Thin plate spline radial basis function for the free vibration analysis of laminated composite shells , 2011 .

[5]  Hossein Moayedi,et al.  Modelling and optimization of ultimate bearing capacity of strip footing near a slope by soft computing methods , 2018, Appl. Soft Comput..

[6]  Mohammad Behshad Shafii,et al.  Numerical simulation of a concentrating photovoltaic-thermal solar system combined with thermoelectric modules by coupling Finite Volume and Monte Carlo Ray-Tracing methods , 2018, Energy Conversion and Management.

[7]  Amin Shahsavar,et al.  Feasibility of a hybrid BIPV/T and thermal wheel system for exhaust air heat recovery: Energy and exergy assessment and multi-objective optimization , 2019 .

[8]  Jungho Im,et al.  Support vector machines in remote sensing: A review , 2011 .

[9]  P. Talebizadeh,et al.  Energy saving in buildings by using the exhaust and ventilation air for cooling of photovoltaic pane , 2011 .

[10]  Amin Shahsavar,et al.  Energy and Exergy Analysis of a Photovoltaic-Thermal Collector With Natural Air Flow , 2012 .

[11]  Youngdeok Hwang,et al.  Artificial neural network model for forecasting sub-hourly electricity usage in commercial buildings , 2016 .

[12]  Hasila Jarimi,et al.  Bi-fluid photovoltaic/thermal (PV/T) solar collector: Experimental validation of a 2-D theoretical model , 2016 .

[13]  Lars Kai Hansen,et al.  Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Christophe Menezo,et al.  Numerical studies on thermal and electrical performance of a fully wetted absorber PVT collector with PCM as a storage medium , 2017 .

[15]  Mehran Ameri,et al.  Experimental investigation and modeling of a direct-coupled PV/T air collector , 2010 .

[16]  Andreas K. Athienitis,et al.  Assessing active and passive effects of façade building integrated photovoltaics/thermal systems: Dynamic modelling and simulation , 2018 .

[17]  F. Soleymani,et al.  A multiquadric RBF–FD scheme for simulating the financial HHW equation utilizing exponential integrator , 2018, Calcolo.

[18]  Mohd Fauzi Othman,et al.  Comparison of different classification techniques using WEKA for breast cancer , 2007 .

[19]  Jalil Rashidinia,et al.  A stable method for the evaluation of Gaussian radial basis function solutions of interpolation and collocation problems , 2016, Comput. Math. Appl..

[20]  R. Schaback.  Multivariate Interpolation by Polynomials and Radial Basis Functions , 2005 .

[21]  Kamal Djidjeli,et al.  Thin-plate spline radial basis function scheme for advection-diffusion problems , 2002 .

[22]  Drew DeJarnette,et al.  Experimental evaluation of a prototype hybrid CPV/T system utilizing a nanoparticle fluid absorber at elevated temperatures , 2018, Applied Energy.

[23]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[24]  Soteris A. Kalogirou,et al.  Exergy analysis of a naturally ventilated Building Integrated Photovoltaic/Thermal (BIPV/T) system , 2017, Renewable Energy.

[25]  Timothy Nicholas Anderson,et al.  Performance of a Building Integrated Photovoltaic/Thermal Concentrator for Facade Applications , 2017 .

[26]  Mazyar Salmanzadeh,et al.  Performance assessment of an innovative exhaust air energy recovery system based on the PV/T-assisted thermal wheel , 2018, Energy.

[27]  Kamaruzzaman Sopian,et al.  Novel criteria for assessing PV/T solar energy production , 2019 .

[28]  Mohammad Passandideh-Fard,et al.  Effect of glass cover and working fluid on the performance of photovoltaic thermal (PVT) system: An experimental study , 2018, Solar Energy.

[29]  K. Touafek,et al.  Analysis of a Hybrid Solar Collector Photovoltaic Thermal (PVT) , 2015 .

[30]  Kamaruzzaman Sopian,et al.  Mathematical and neural network models for predicting the electrical performance of a PV/T system , 2019, International Journal of Energy Research.

[31]  M. Phil,et al.  Comparative Analysis of Classification Function Techniques for Heart Disease Prediction , 2013 .

[32]  Alibakhsh Kasaeian,et al.  Numerical investigation of the effects of a copper foam filled with phase change materials in a water-cooled photovoltaic/thermal system , 2018 .

[33]  Taskin Kavzoglu,et al.  A kernel functions analysis for support vector machines for land cover classification , 2009, Int. J. Appl. Earth Obs. Geoinformation.

[34]  M V Patil,et al.  Identification of Growth Rate of Plant based on leaf features using Digital Image Processing Techniques , 2013 .

[35]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[36]  Amin Shahsavar,et al.  Energy analysis and multi-objective optimization of a novel exhaust air heat recovery system consisting of an air-based building integrated photovoltaic/thermal system and a thermal wheel , 2018, Energy Conversion and Management.

[37]  Amin Shahsavar,et al.  Scenario-Based Multi-Objective Optimization of an Air-Based Building-Integrated Photovoltaic/Thermal System , 2018 .

[38]  Kaushik H. Raviya,et al.  Performance Evaluation of Different Data Mining Classification Algorithm Using WEKA , 2012 .

[39]  Wei Sun,et al.  Numerical simulation and experimental validation of tri-functional photovoltaic/thermal solar collector , 2015 .

[40]  A. Kabeel,et al.  Experimental investigation on Peltier based hybrid PV/T active solar still for enhancing the overall performance , 2018, Energy Conversion and Management.

[41]  Hongdong Li,et al.  Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[42]  Luis C. Dias,et al.  Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application , 2014 .

[43]  Miqdam T. Chaichan,et al.  Experimental and deep learning artificial neural network approach for evaluating grid‐connected photovoltaic systems , 2019, International Journal of Energy Research.

[44]  Mohammad Passandideh-Fard,et al.  Optimization and parametric analysis of a nanofluid based photovoltaic thermal system: 3D numerical model with experimental validation , 2018 .

[45]  T Poggio,et al.  Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks , 1990, Science.

[46]  Fathollah Pourfayaz,et al.  Evaluating the environmental parameters affecting the performance of photovoltaic thermal system using nanofluid , 2017 .

[47]  Mazyar Salmanzadeh,et al.  Energy and exergy analysis and multi-objective optimization of an air based building integrated photovoltaic/thermal (BIPV/T) system , 2017 .

[48]  Y. Tripanagnostopoulos,et al.  Air-cooled PV/T solar collectors with low cost performance improvements , 2007 .

[49]  N. Altman.  An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression , 1992 .

[50]  W. Beckman,et al.  Solar Engineering of Thermal Processes: Duffie/Solar Engineering 4e , 2013 .

[51]  Samir Kumar Bandyopadhyay,et al.  A tutorial review on Text Mining Algorithms , 2012 .

[52]  Wei Gao,et al.  The feasibility of genetic programming and ANFIS in prediction energetic performance of a building integrated photovoltaic thermal (BIPVT) system , 2019 .