Fuzzy Systems
and Soft Computing

Volume 7, No. 2, 2012

Issue is devoted to problems of intelligent information systems development for diagnostics and troubleshooting of rolling equipment for rail transport.

• Ivanova E.I., Gordeev R.N., Mikhailov V.V., Severov A.V., Yazenin A.V.
  «Model of centralized intelligent information system for diagnosis and prediction of failure of rolling equipment on railways»
  
  In the article the model of information control system of a rolling stock carriage equipment of rail transport is presented. On different levels model of diagnostics subsystem, architecture of forecast complex and decision making, structure of processed data are described. The questions of data bases organization and optimization of informational system using methods of data mining and soft computing are considered.

  Keywords: information systems, rail transport, diagnostics, forecast, decision making, soft computing.

  Resources: title page of the article, elibrary.ru.

• Grishina E.N., Soldatenko I.S.
  «On the reduction of attributes space dimension in problems of railway wagon malfunctions forecasting»
  
  The paper describes the structure of the parameters defining the input data coming from sensors of rolling equipment on the railways. Various approaches for data mining which goal is to identify dependencies and redundancy are outlined.

  Keywords: information system, rail transport, optimization, data mining, correlation analysis, the method of decision tree.

  Resources: title page of the article, elibrary.ru.

• Soldatenko I.S., Grishina E.N.
  «Some approaches to the development of intelligent prediction models of railway wagon equipment malfunctions»
  
  The paper investigates main approaches for construction of prediction models based in information collected from sensors of the electronic railway carriage equipment. Regression models, neural networks, as well as models, built on the basis of decision-making trees are considered.

  Keywords: information system, railway transport, forecasting, data mining, neural networks, regression analysis, decision trees.

  Resources: title page of the article, elibrary.ru.

• Ivanova E.I., Sorokin S.V.
  «Database optimization and building of prediction models of railway wagon equipment malfunctions based on neural network technology and methods of evolutionary programming for the railways management system»
  
  In the article the combination of genetic algorithm and artificial network applying for preliminary data analysis and information system of railway transport management database optimization is presented. The example of work with real data from controller of railway car electric equipment management is described.

  Keywords: information systems, railway transport, diagnostics, forecast, soft computing, genetic algorithm, artificial network.

  Resources: title page of the article, elibrary.ru.

• Inshina I.V., Sorokin S.V.
  «Parameter estimation of fuzzy distributions in two-dimensional case»
  
  Based on the work of Wang Xizhao and Ha Minghu, we present a solution to the Maxmin mu/E parameters estimation problem of fuzzy distributions in two-dimensional case and show that this estimator is consistent, sufficient and is a maximum likehood estimator. Our method is based on geometrical approach, where minimal area enclosing ellipsis is constructed around the sample.

  Keywords: fuzzy distribution, parameter estimation, Maxmin estimator.

  Resources: title page of the article, elibrary.ru.

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