Experience of Multi-Layer Neural Network Application for Empirical Regularities Identification
DOI:
https://doi.org/10.14529/ctcr190215Keywords:
neural network, prediction, control, comparison, enterprise, features, representation, recognition, contradictoryAbstract
In this article, the recognition method is applied to the comparison of industrial enterprises. At the same time, we had to consider the methods of taking into account non-formalized factors. The method can be used for objective ranking of enterprises. While researching the topic, a neural expert system was developed, and it was used by specialists of the regional government to predict the dynamics of industry.
In view of the complexity of relations, conflicting non-equality systems were arising. We were resolving them by means of committee method.
The effect of managing the situation by varying the values of factors by tracking them on a computer model, made it possible to adjust the model as a means of parallelizing the committee constructions. They act directly in multi-layer neural networks.
References
Mazurov Vl.D. Komitetnye resheniya zadach planirovaniya. V kn.: Metody approksimatsii nesobstvennykh zadach matematicheskogo programmirovaniya [Committee Problem Solving of Scheduling. In the Book “Methods of Approximation of the Improper Problems of Mathematical Programming”]. Sverdlovsk, TSC AS USSR, 1984, pp. 21–25.
Mazurov Vl.D. Metod komitetov v zadachakh optimizatsii i klassifikatsii [Method of Committees in Problems of Optimization and Classification]. Мoscow, Nauka Publ., 1990. 248 p.
Khachay M.Yu., Mazurov Vl. D., Rybin A.I. Committee Constructions for Solving Problems of Selection, Diagnostings, and Prediction. Proceedings of the Steklov Institute of Math., 2002, Suppl. 1, pp. 66–102.
Vasil'ev V.I. Raspoznayushchie sistemy. Spravochnik [Distinguishing Systems. Reference Book]. Kiev, Naukova dumka Publ., 1990. 305 p.
Ivakhnenko A.G. Nepreryvnost' i diskretnost'. Perebornye metody modelirovaniya i klasterizatsii. [Continuity and Discretization. Reboric Methods of Model Operation and Clustering]. Kiev, Naukova dumka Publ.,1990. 392 p.
Lapko A.V., Chentsov S.V., Krokhov S.I., Fel'dman L.A. Obuchayushchiesya sistemy obrabotki informatsii i prinyatiya resheniy [The Studying Data Reduction Systems and Decision Makings]. Novosibirsk, Nauka Publ., 1996. 270 p.
Mazurov Vl.D., Popkov V.V. et al. O primenenii obuchayushchikhsya algoritmov pri reshenii zadachi sravnitel'noy otsenki deyatel'nosti predpriyatiy [About Application of the Studying Algorithms at the Solution of a Problem of Comparative Assessment of Activity of the Enterprises]. Works IMM UB RAS, 1998, pp. 61–75.
