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Comparative Study of Methods for Monitoring and Controlling a Regional Economic System

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E-business Technology and Strategy (CETS 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 113))

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Abstract

As a measure of the regional economic development, regional economic competitiveness in a regional economic system has been monitored and controlled by two different methods: classical integration control method and the fuzzy integration control method. In this paper, we discussed the relationship of these two methods, and then present a new method combing them together. Our experimental results confirm that this new method is effective in monitoring and controlling a regional economic system.

This research is supported by Liaoning Social Science funds (Project No. L07DJY067) and Ph.D. support funds (20066201). Supported by the Fundemental Research Funds for the Central Universities.

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References

  1. Zheng, S., Zheng, W., Jin, X.: An Application of System Identification Method in Regional Economic System. In: The 3rd IEEE International Conference on Wireless Communications, Networks and Mobile Computing, pp. 3870–3873 (2007)

    Google Scholar 

  2. Obeli, C., Urzua, J., et al.: An Expert System for Monitor Alarm Integration. Journal of Clinical Monitoring and Computing 15(1), 29–35 (1999)

    Article  Google Scholar 

  3. Wu, J., Karmin, D.: A Fuzzy-Expert System-Based Structure for Active Queue Management. In: Huang, D.-S., Zhang, X.-P., Huang, G.-B. (eds.) ICIC 2005. LNCS, vol. 3645, pp. 1013–1101. Springer, Heidelberg (2005)

    Google Scholar 

  4. Hadjimichael, M., Kuciauskas, A., et al.: A Meteorological Fuzzy Expert System Incorporating Subjective User Input. Knowledge and Information System 4(3), 350–369 (2002)

    Article  Google Scholar 

  5. Zheng, S., Zheng, W., Jin, X.: Fuzzy Integration Monitor Method in Regional Economic System and its Simulation. In: The 26th Chinese Control Conference, pp. 2–4 (2002)

    Google Scholar 

  6. Astrom, K.J., et al.: Automatic Tuning and Adaptation for PID Controllers-A Survey. Adaptive Systems in Control and Signal Proceeding, 371–376 (1992)

    Google Scholar 

  7. Takatsu, H., Kawano, T., Kitano, K.: Intelligent self-tuning PID Controller. In: International Symposium on Intelligent Tuning and Adaptive Control, pp. 451–457 (1991)

    Google Scholar 

  8. Nguyen, H.T., Prasad, N.R., Walker, C., et al.: A First Course of Fuzzy and Neural Control. CRC Press, USA (2003)

    MATH  Google Scholar 

  9. Zhu, Y., Meng, Z., Gan, S.: Calculation of weigntness by AHP. Journal of North Traffic University 10, 119–122 (1999)

    Google Scholar 

  10. Charmet, G., Cadalen, T., Sourdille, P., Bernard, M.: An Extension of the ‘Marker Regression’ Method to Interactive QTL. Molecular Breeding 4, 67–72 (1984)

    Article  Google Scholar 

  11. Arif, M., Ishihara, T., Inooka, H.: Iterative Learning Control Utilizing the Error Prediction Method. Journal of Intelligent and Robotic Systems 25(2), 95–108 (1999)

    Article  MATH  Google Scholar 

  12. Cedervall, M., Stoica, P.: System Identification from Noisy Measurements by Using Instrumental Variables and Subspace Fitting. Circuits, Systems, and Signal Processing 15(2), 275–290 (1996)

    Article  MATH  Google Scholar 

  13. Haubruge, S., Nguyen, V.H., Strodior, J.J.: Convergence Analysis and Applications of the Glowinski-Le Tallec Splitting Method for Finding a Zero of the Sum of Two Maximal Monotone Operators. Journal of Optimization Theory and Applications 97(3), 645–673 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  14. Subasil, A.: Application of Classical and Model-Based Spectral Methods to Describe the State of Alertness in EEG. Journal of Medical Systems 29(5), 473–486 (2005)

    Article  Google Scholar 

  15. Nyman, K.L.: Linear Inequalities for Rank 3 Geometric Lattices. Discrete Comput. Geom. 31(2), 229–242 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  16. Fan, G., Wang, X.: Index of General Adoption of Market Principle in China. Economic Science Press, Beijing (2001)

    Google Scholar 

  17. Tang, R., Tang, T.: Measurement on Efficiency of Province and Local Government in China. China Administration 6, 2857–2871 (2004)

    Google Scholar 

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Zheng, S., Zheng, W., Jin, X. (2010). Comparative Study of Methods for Monitoring and Controlling a Regional Economic System. In: Zaman, M., Liang, Y., Siddiqui, S.M., Wang, T., Liu, V., Lu, C. (eds) E-business Technology and Strategy. CETS 2010. Communications in Computer and Information Science, vol 113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16397-5_12

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  • DOI: https://doi.org/10.1007/978-3-642-16397-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16396-8

  • Online ISBN: 978-3-642-16397-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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