Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model
Language English Country United States Media print-electronic
Document type Journal Article
PubMed
26774211
DOI
10.1016/j.wasman.2015.12.025
PII: S0956-053X(15)30258-0
Knihovny.cz E-resources
- Keywords
- Empirical test, Fuzzy logic, Prediction, Recycling behaviour,
- MeSH
- Fuzzy Logic * MeSH
- Humans MeSH
- Linear Models * MeSH
- Recycling * statistics & numerical data MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique.
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