Volume 8, No. 1, 2013
- Ledeneva T.M., Kaplieva N.A.
«Influence of various types of transitivity on decomposition tree in problem of fuzzy classification»
This article is devoted to the influence of different types of transitivity generated by triangular norms on the structure of decomposition tree in the problem of fuzzy classification. Structural characteristics of decomposition tree are proposed.Keywords: similarity, difference, transitivity, decomposition tree.
Resources: title page of the article, elibrary.ru.
Bibliographic citationLedeneva T.M., Kaplieva N.A. Influence of various types of transitivity on decomposition tree in problem of fuzzy classification. Nechetkie sistemy i myagkie vychisleniya [Fuzzy Systems and Soft Computing], 2013, vol. 8, no. 1, pp. 5-25. (in Russian) - Filatova N.N., Khaneev D.M.
«Use of neurolike structures for automatic generation of hypotheses for classification rules»
The paper considers possibility of using neurolike network structures for automatic lasing hypotheses of classification rules. A hybrid algorithm for the solution of the problem is proposed. Algorithm includes in the classification rules only the most significant attributes. Fuzzy sets are used when describing the attribute spaces. Software that implements the algorithm is presented with results of its work on real experimental data.Keywords: classification, neural network structures, hybrid algorithms, fuzzy sets.
Resources: title page of the article, elibrary.ru.
Bibliographic citationFilatova N.N., Khaneev D.M. Use of neurolike structures for automatic generation of hypotheses for classification rules. Nechetkie sistemy i myagkie vychisleniya [Fuzzy Systems and Soft Computing], 2013, vol. 8, no. 1, pp. 27-44. (in Russian) - Ivanova E.I., Sorokin S.V.
«Artificial echo state network for predicting extraordinary situations in behavior of a rolling stock carriage equipment»
Article describes artificial echo state network for prediction extraordinary situations in behavior of a rolling stock carriage equipment of rail transport.Keywords: information system, rail transport, diagnostics, forecast, decision making, soft computing, artificial network, echo state network.
Resources: title page of the article, elibrary.ru.
Bibliographic citationIvanova E.I., Sorokin S.V. Artificial echo state network for predicting extraordinary situations in behavior of a rolling stock carriage equipment. Nechetkie sistemy i myagkie vychisleniya [Fuzzy Systems and Soft Computing], 2013, vol. 8, no. 1, pp. 45-57. (in Russian)