Volume 3, No. 4, 2008

Special Issue:

Problems and prospect of intelligent technologies of soft and quantum computing development

Dedicated editors of the issue:

  • Academician of Azerbaidzhan Academy of Sciences, Doctor of Technical Science, professor Aliev R.A.,
  • Doctor of Science, professor Ulyanov S.V.


  • Ryzhov A.P., Timirova A.N.
    On stability of fuzzy mathematical models in economics
    This paper analyzes properties of fuzzy models in economics. We investigate a question of dependence model work quality and initial data quality. Fuzzy model separating trade zones is considered. Initial data quality is estimated as a fuzziness degree of relations goods - property and goods - firm. It is proved that model response monotonicity doesn't survive fuzziness degree in general case. Sometimes there exists a relationship between the model answer and initial data quality. Such particular cases are investigated in detail. They are performed in highly artificial constraints. Also other operation application doesn't lead to fuzziness degree preservation. Thereby analyzing model doesn't guarantee that model work quality is a function of initial data quality and should be used carefully.

    Resources: elibrary.ru.

  • Lebedev A.A., Ryzhov A.P.
    Intelligent computing in information monitoring systems
    Information Monitoring Technology was developed for analysing complex systems or processes that do not have an appropriate mathematical model. Tools based on this technology (called information monitoring systems) can utilise all available information to provide estimates of the development of the monitored system/ process and find optimal strategies for controlling its behaviour. In this paper, we discuss the principal aspects of developing such systems and provide some theoretical results that guarantee their correctness and optimality. We also give several examples of developing and applying information monitoring systems for various application domains. We describe the main development stages as well as various ways of usage, and demonstrate some differences in the approaches caused by differences in the addressed problems' characteristics.

    Resources: elibrary.ru.

  • Ulyanov S.V., Litvintseva L.V., Sorokin S.V.
    Knowledgebase robustness of self-organizing intelligent regulators in unpredicted control situations
    Effectiveness of robust knowledgebase design technology is demonstrated with thermodynamic criteria using the Benchmark as unstable essentially nonlinear control object. Quantum control algorithm of knowledgebase self-organization is developed. In this algorithm additional quantum information (as hidden information in classical states superposition) and minimum entropy in intelligent control state are used. Application of quantum fuzzy inference and entropy minimum principle guarantee the achievement of required robustness level in unpredicted control situations.

    Resources: elibrary.ru.