Title
Multiple Linear Regression Model of Environmental Variables, Predictors of Global Solar Radiation in the Area of East Lima, Peru
Date Issued
01 April 2022
Access level
open access
Resource Type
conference paper
Author(s)
Poma O.
Sumire D.A.
Rojas J.H.F.
Chipa S.M.R.
Publisher(s)
IOP Publishing Ltd.
Abstract
Multiple regression models are very relevant to predict values using predictor variables. The objective of this study was to predict the global solar radiation in the year 2019 in the area of East Lima, Peru. Three continuous quantitative predictor variables were analyzed: temperature, humidity, wind speed and the response variable was global solar radiation, resulting in a model with excellent significance p<0.001 that shows the prediction is effective. The multiple linear regression method was used, finding an average global radiation of 175 W/m2 and predictor variables with average temperature of 19.2 °C, humidity 23.9% and wind speed 1.77 m/s, with the highest temperature in summer recorded at 24.6°C, the highest humidity of 51.2% in autumn, the highest wind speed in summer at 2.63 m/s and the highest maximum global solar radiation in spring with 183 W/m2.
Volume
1006
Issue
1
Language
English
OCDE Knowledge area
Ingeniería ambiental y geológica Ingeniería de sistemas y comunicaciones
Scopus EID
2-s2.0-85127975196
ISSN of the container
17551307
Conference
IOP Conference Series: Earth and Environmental Science
Sources of information: Directorio de Producción Científica Scopus