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Определение Параметров Управления Региональным Развитием На Основе Алгоритмов Нечеткой Логики

Author

Listed:
  • Низамутдинов М.М.
  • Орешников В.В.

Abstract

В статье рассматриваются вопросы разработки стратегии регионального развития на основе инструментария экономико-математического моделирования социально-экономических систем. Предварительный анализ подходов и программных решений в данной сфере показал, что в первую очередь требуют рассмотрения аспекты определения количественных характеристик целей развития и выработки регулирующего воздействия для их достижения. Разработан подход к формированию индикативного плана и параметров управления в рамках обоснования среднесрочных стратегий регионального развития, интегрирующий процедуры целеполагания и регулирования, отличающийся нечетким алгоритмом классификации ситуаций и корректировкой значений параметров управления в условиях взаимной адаптации интересов различных подсистем региона. Для использования методов нечеткой логики были разработаны критерии оценки ситуации, функции принадлежности и база нечетких правил. Кроме того, сформирован комплекс правил корректировки управляющих параметров. Предложенный подход позволяет связать модель функционирования экономических агентов и модель определения целей регионального развития в единую систему управления с обратными связями, а также обеспечить наиболее эффективное использования ресурсов при формировании среднесрочной стратегии регионального развития.

Suggested Citation

  • Низамутдинов М.М. & Орешников В.В., 2016. "Определение Параметров Управления Региональным Развитием На Основе Алгоритмов Нечеткой Логики," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 52(2), pages 30-39, апрель.
  • Handle: RePEc:scn:cememm:v:52:y:2016:i:2:p:30-39
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    References listed on IDEAS

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    1. Sherman Robinson, 2006. "Macro Models and Multipliers: Leontief, Stone, Keynes, and CGE Models," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Alain Janvry & Ravi Kanbur (ed.), Poverty, Inequality and Development, chapter 0, pages 205-232, Springer.
    2. Gianni Amisano & John Geweke, 2017. "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 912-925, December.
    3. Gary Fromm & Lawrence R. Klein & George R. Schink, 1972. "Short- and Long-Term Simulations with the Brookings Model," NBER Chapters, in: Econometric Models of Cyclical Behavior, Volumes 1 and 2, pages 201-310, National Bureau of Economic Research, Inc.
    4. Andriantiatsaholiniaina, Luc A. & Kouikoglou, Vassilis S. & Phillis, Yannis A., 2004. "Evaluating strategies for sustainable development: fuzzy logic reasoning and sensitivity analysis," Ecological Economics, Elsevier, vol. 48(2), pages 149-172, February.
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