ORI GIN AL PA PER Potential of support vector regression for solar radiation prediction in Nigeria

Abstract In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine du-ration, monthly mean maximum and minimum temperature) taking from Iseyin meteoro-logical station in Nigeria was examined. The process, which simulates the solar radiation with support vector regression (SVR), was constructed. The inputs were monthly mean maximum temperature (Tmax), monthly mean minimum temperature (Tmin) and monthly mean sunshine duration (n). Polynomial and radial basis functions (RBF) are applied as the SVR kernel function to estimate solar radiation. According to the results, a greater im-provement in estimation accuracy can be achieved through the SVR with polynomial basis function compared to RBF. The SVR coefficient of determination R2 with the polynomial function was 0.7395 and with the radial basis function, the R2 was 0.5877