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Using Pattern Classification and Recognition Techniques for Diagnostic and PredictionMORARIU, N., VLAD, S.
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pattern recognition, neural networks, multilayer, perceptron, diagnostication, prediction
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About this article
Date of Publication: 2007-04-02
Volume 7, Issue 1, Year 2007, On page(s): 63 - 67
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2007.01014
Web of Science Accession Number: 000259841200014
The paper presents some aspects regarding the joint use of classification and recognition techniques for the activity evolution diagnostication and prediction by means of a set of indexes. Starting from the indexes set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indexes set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The data set used in experiments describes the pollution due to CO2 emission from the consumption of fuels in Europe. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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