operational predictive model for a municipal waste incinerator: a spanish case study

نویسندگان

l. jimenez

j.m. mateo

i. lopez-arevalo

m.t. oms

چکیده

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.

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عنوان ژورنال:
international journal of environmental research

ناشر: university of tehran

ISSN 1735-6865

دوره 5

شماره 3 2011

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