Илғор иқтисодиёт ва педагогик технологиялар Том 2 № 6 (2025) · с. 319-324
IDENTIFYING THE ENDOGENEITY OF REGIONAL ECONOMIC GROWTH USING A NEURO-FUZZY APPROACH: METHODS AND MODELS
Mirzayev, Shokhrukh, Мирзаев, Шохрух, Mirzayev, Shoxrux
Аннотация
This study evaluates the endogenous drivers of economic growth in Kashkadarya region using statistical data from 2010–2025 through neuro-fuzzy (ANFIS) and multilayer perceptron (MLP) models. Household income, traditional and digital infrastructure were selected as key indicators. The ANFIS model achieved high accuracy (R² = 0.977; RMSE = 0.40; MAPE = 7.8%), effectively capturing nonlinear economic relationships. A 3D surface plot highlighted the strong synergy between digital infrastructure and income. In comparison, the MLP model yielded slightly lower accuracy. The results suggest that investing in digital infrastructure and applying endogenous modeling approaches are crucial for strategic planning
ANFISMLPregional economic growthdigital infrastructurefuzzy logicnonlinear modelingANFISMLPрегиональный экономический ростцифровая инфраструктура
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