Comparative study of modelling the thermal efficiency of a novel straight through evacuated tube collector with MLR, SVR, BP and RBF methods

Application of Artificial Neural Network in Solar Energy

“…Here, the thermal efficiency is defined as the ratio of the heat obtained by the heat transfer fluid to the incident solar flux on the tube [30], and is written as follows [22,[46][47][48]. Parameters of an all-glass straight through evacuated tube [11].…”

“…Sensitivity analysis refers to finding the sensitive factors that have a significant impact on the output of the models from many uncertain factors, and analyzing and calculating their impact and relative importance on the results. In short, sensitivity Accuracy of the models in performance prediction [11].…”

“…The dominant energy equations of the studied all-glass straight-through evacuated tube solar collector, as well as necessary heat and mass transfer and other related [11].…”

“…The traditional algorithms usually employed are very complex, including the solution of complicated different equations, which usually involves large resource and takes a great quantity of time to give exact solutions [8]. Moreover, traditional analysis methods are often based on simplified assumptions, as well as simplified models and solving nonlinear partial differential equations, which reduce the prediction accuracy [9][10][11]. ANN is a mathematical method that mimics the behavior of human brain.…”

“…(a) Relative importance of input variables based on solar radiation. (b) Relative importance (%) of the inlet variables on the thermal efficiency of the evacuated tube[11].…”