Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction

• Main Authors: MORARIU, N., VLAD, S.
• Format: Article
• Language: English
• Published: Stefan cel Mare University of Suceava 2007-04-01
• Series: Advances in Electrical and Computer Engineering
• Subjects: pattern recognition; neural networks; multilayer; perceptron; diagnostication; prediction
• Online Access: http://dx.doi.org/10.4316/AECE.2007.01014
• ISSN: 1582-7445; 1844-7600

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.