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Genetic algorithms to reduce diagnostic information

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Abstract

A new genetic algorithm-based approach to the problem of reducing the diagnostic information acquired by testing discrete devices was proposed. Consideration was given to minimization and optimization of the diagnostic information for which the corresponding fitness functions and chromosome structures used in the genetic algorithms were suggested. Statistical data corroborating efficiency of the developed genetic algorithms for the problems under consideration were presented.

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References

  1. Barashko, A.S., Skobtsov, Yu.A, and Speranskii, D.V., Modelirovanie i testirovanie diskretnykh ustroistv (Modeling and Testing of Discrete Device), Kiev: Naukova Dumka, 1992.

    Google Scholar 

  2. Voznesenskii, S.S. and Razdobreev, A.Kh., Laboriousness of Malfunction Search as a Performance Criterion for Reduction of Volume of Diagnostic Information, Elektron. Modelir., 1980, no. 4, pp. 83–86.

  3. Malyshenko, Yu.V. and Razdobreev, A.Kh., A Method for Reduction of the Volume of Diagnostic Information for Seeking Malfunctions, Avtom. Telemekh., 1977, no. 4, pp. 160–164.

  4. Speranskii, D.V., On One Approach to Reduction of Volume of Diagnostic Information, Avtom. Telemekh., 1984, no. 3, pp. 151–160.

  5. Speranskii, D.V. and Shatokhina, N.K., Methods of Optimization of Diagnostic Information, in Teoreticheskie problemy kibernetiki (Theoretical Problems of Cybernetics), Saratov: Sarat. Univ., 1986, pp. 129–132.

    Google Scholar 

  6. Speranskii, D.V. and Shatokhina, N.K., Approximate Methods of Optimization of the Diagnosis of Depth of Discrete Devices, in Mnogoprotsessornye vychislitel’nye struktury (Multiprocessor Computing Structures), Taganrog: TRTI, 1985, vol. 7(XIV), pp. 70–72.

    Google Scholar 

  7. Chipulis, V.P., Methods of Minimization of Diagnosis Resolution and Diagnostic Information, Avtom. Telemekh., 1975, no. 3, pp. 133–141.

  8. Chipulis, V.P., Study of the Diagnostic Information at Checking and Search of Malfunctions of Discrete Devices, Avtom. Telemekh., 1975, no. 8, pp. 150–157.

  9. Chipulis, V.P., Search of Malfunctions of Discrete Devices: Preprocessing Methods and Forms of Diagnostic Information, Avtom. Telemekh., 1977, no. 4, pp. 165–175.

  10. Sharshunov, S.G., Features of Diagnosis of the State of Multioutput Objects by Malfunction Tables, Avtom. Telemekh., 1974, no. 12, pp. 161–168.

  11. Goldberg, D.E., Algorithms in Search, Optimization, and Machine Learning, New York: Addison-Wesley, 1989.

    MATH  Google Scholar 

  12. Speranskii, D.V., Speranskii, D.V., Samoilov, V.G., and Emel’yanova, O.V., Vvedenie v geneticheskie algoritmy (Introduction to Genetic Algorithms), Speranskii, D.V., Ed., Saratov: Sarat. Univ., 2006.

    Google Scholar 

  13. Blickle, T. and Thiele, L., A Comparison of Selection Schemes Used in Genetic Algorithms, in TIK-Report, Zurich: ETH, 1995, no. 11.

    Google Scholar 

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Original Russian Text © S.V. Mironov, D.V. Speranskii, 2008, published in Avtomatika i Telemekhanika, 2008, No. 7, pp. 146–156.

This work was supported by the Russian Foundation for Basic Research, projects nos. 05-08-18082, 05-08-49999.

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Mironov, S.V., Speranskii, D.V. Genetic algorithms to reduce diagnostic information. Autom Remote Control 69, 1231–1240 (2008). https://doi.org/10.1134/S000511790807014X

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  • DOI: https://doi.org/10.1134/S000511790807014X

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