Forecast generation model of municipal solid waste using multiple linear regression
Por:
Araiza-Aguilar, J. A., Rojas-Valencia, M. N., Aguilar-Vera, R. A.
Publicada:
1 ene 2019
Categoría:
Environmental science (miscellaneous)
Resumen:
The objective of this study was to develop a forecast model to determine
the rate of generation of municipal solid waste in the municipalities of
the Cuenca del Canon del Sumidero, Chiapas, Mexico. Multiple linear
regression was used with social and demographic explanatory variables.
The compiled database consisted of 9 variables with 118 specific data
per variable, which were analyzed using a multicollinearity test to
select the most important ones. Initially, different regression models
were generated, but only 2 of them were considered useful, because they
used few predictors that were statistically significant. The most
important variables to predict the rate of waste generation in the study
area were the population of each municipality, the migration and the
population density. Although other variables, such as daily per capita
income and average schooling are very important, they do not seem to
have an effect on the response variable in this study. The model with
the highest parsimony resulted in an adjusted coefficient of 0.975, an
average absolute percentage error of 7.70, an average absolute deviation
of 0.16 and an average root square error of 0.19, showing a high
influence on the phenomenon studied and a good predictive capacity. (c)
2020 GJESM. All rights reserved.
Filiaciones:
Araiza-Aguilar, J. A.:
Univ Sci & Arts Chiapas, Sch Environm Engn, North Beltway, Tuxtla Gutierrez, Chiapas, Mexico
Rojas-Valencia, M. N.:
Univ Nacl Autonoma Mexico, Inst Engn, Mexico City, DF, Mexico
Aguilar-Vera, R. A.:
Univ Nacl Autonoma Mexico, Inst Geog, Mexico City, DF, Mexico
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