Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The nature of statistical learning theory
The nature of statistical learning theory
An introduction to variable and feature selection
The Journal of Machine Learning Research
Application of fuzzy time series models for forecasting pollution concentrations
Expert Systems with Applications: An International Journal
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The study described in this paper, analyzed the urban and suburban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants concentrations) for each air pollutant in order to predict its medium-term concentration (in particular for the PM10). An information theoretic approach to feature selection has been applied in order to determine the best subset of features by means of a proper backward selection algorithm. The final aim of the research is the implementation of a prognostic tool able to reduce the risk for the air pollutants concentrations to be above the alarm thresholds fixed by the law. The implementation of this tool will be carried out using machine learning methods based on some of the most widespread statistical data driven techniques (Artificial Neural Networks, ANN, and Support Vector Machines, SVM).