| Paper title: |
The Joint Use of Artificial Intelligence Technique for Diagnostication and Prediction |
| Published in: | Issue 1, (Vol. 1) / 2007 |
| Author(s): | Morariu Nicolae, Vlad Sorin |
| Abstract. | The paper presents some aspects regarding the joint use of artificial intelligence techniques for the activity evolution, diagnosis and prediction by means of a set of indexes. Starting from the indexes set a measure on the patterns set is defined, 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 toward positive evolution. For the diagnostication and prediction the following tools are used here: regressional models, pattern recognition and multilayer perceptron. The data set used in experiments describes the evolution of the Bucharest Stock Exchange (BSE). The paper presents: REFORME software written by the authors and the experiments carried out in order to analyze the activity of BSE. |
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| References: | 1. Abdi Herve, Les Reseaux de Neurones, Universite de Bourgogne,1993. 2. Nikola K. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, A Bradford Book, The MIT Press, Cambridge, Massachusetts, London, England, 1998 3. Menahem Friedman, Abraham Kandel Introduction to pattern recognition statistical, structural, neural and fuzzy logic approaches, World Scientific, 2000 4. Nicolae Morariu, “REFORME – A software product for pattern clasification and recognition by joint use of pattern recognition techniques and multi-layer perceptron”, “The Proceedings of the Central and East European Conference in Business Information Systems”, Cluj-Napoca, may 2004, Ed. Risoprint, ISBN 973-656- 648-X, pag.100-105. 5. Sorin Vlad, “Neural Networks Applications-Chaotic Time Series Prediction”, Distributed Processing, Suceava University Publishing House, Romania, 2005. 6. Şt.Gh.Pentiuc, Nicolae Morariu, ş.a., Intelligent System for Prognosis and Estimation of Economic Decisions at Districtual Level, Advances in Electrical and Computer Engineering, Faculty of Electrical Engineering “Stefan cel Mare” University of Suceava, vol.1(8), nb.1(15), 2001, pp. 44-47 7. Romul Vancea, Ştefan Holban, Dan Ciubotariu, Recunoaşterea Formelor Aplicaţii, Ed. Academiei R.S.R. 1989. |
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