首页|Researcher at Chengdu University Has Published New Data on Machine Learning (A Machine Learning Approach to Estimating Solar Radiation Shading Rates in Mountainous Areas)
Researcher at Chengdu University Has Published New Data on Machine Learning (A Machine Learning Approach to Estimating Solar Radiation Shading Rates in Mountainous Areas)
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Investigators publish new report on artificial intelligence. According to news originating from Chengdu, People’s Republic of China, by NewsRx correspondents, research stated, “Quantification of shading effects from complex terrain on solar radiation is essential to obtain precise data on incident solar radiation in mountainous areas.” Financial supporters for this research include National Natural Science Foundation of China. The news editors obtained a quote from the research from Chengdu University: “In this study, a machine learning (ML) approach is proposed to rapidly estimate the shading effects of complex terrain on solar radiation. Based on two different ML algorithms, namely, Ordinary Least Squares (OLS) and Gradient Boosting Decision Tree (GBDT), this approach uses terrain-related factors as input variables to model and analyze direct and diffuse solar radiation shading rates. In a case study of western Sichuan, the annual direct and diffuse radiation shading rates were most correlated with the average terrain shading angle within the solar azimuth range, with Pearson correlation coefficients of 0.901 and 0.97. The GBDT-based models achieved higher accuracy in predicting direct and diffuse radiation shading rates, with R2 values of 0.982 and 0.989, respectively, surpassing the OLS-based models by 0.081 and 0.023.”
Chengdu UniversityChengduPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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