Author/Authors :
Jimenez، L نويسنده 1 Chemical Engineering Department, ETSEQ, University Rovira i Virgili, Av. dels Països Catalans 26, 43007 Tarragona, Spain , , Mateo، J.M نويسنده Chemical Engineering Department, ETSEQ, University Rovira i Virgili, Av. dels Països Catalans 26, 43007 Tarragona, Spain , , Lopez-Arevalo، I نويسنده Information Technology Laboratory, Cinvestav Tamaulipas, Scientific and Technological Park TecnoTam, 87130 Victoria, Tamaulipas, Mexico , , Oms، M.T نويسنده TIRME S.A., Carretera de S?ller Km 8.2, 07120 Palma de Mallorca, Islas Baleares, Spain ,
Abstract :
This paper describes a study of operational parameters by using the multivariate data analysis
and neural networks for a municipal waste incinerator located in Majorca (Spain). The basis of the study also
includes the chemometric techniques: linear multivariate regression to develop a model with certain predictive
capabilities; linear principal component analysis, which allow the number of variables to be reduced from 17
to 4, thus fostering visualization in a low-dimension space; and linear discriminant analysis to categorize plant
data accordingto the month (probability ? 70%). Neural network predictive capability was good, with relative
errors around 6-8%. These techniques allow all the variables to be analysed simultaneously and focus on the
variables which have a significant impact. In this way, the interrelationships between sets of variables, causal
relations among input/output variables, seasonal motivated deviations as well as observation variations have
been identified.
