IDENTIFYING THE ENDOGENEITY OF REGIONAL ECONOMIC GROWTH USING A NEURO-FUZZY APPROACH: METHODS AND MODELS

Mirzayev , Shokhrukh, Мирзаев , Шохрух, Mirzayev , Shoxrux

Илғор иқтисодиёт ва педагогик технологиялар · 2025-yil

Annotatsiya

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

Maqola ma’lumotlari
MualliflarMirzayev , Shokhrukh, Мирзаев , Шохрух, Mirzayev , Shoxrux
JurnalИлғор иқтисодиёт ва педагогик технологиялар
Nashr sanasi2025-12-03
Jild2
Son6
Betlar319-324
TilO‘zbek
DOI10.60078/3060-4842-2025-vol2-iss6-pp319-324

Kalit so‘zlar

ANFIS, MLP, regional economic growth, digital infrastructure, fuzzy logic, nonlinear modeling, ANFIS, MLP, региональный экономический рост, цифровая инфраструктура, доходы населения, нечеткая логика, ANFIS, MLP, mintaqaviy iqtisodiy o‘sish, raqamli infratuzilma, aholi daromadlari, fuzzy mantiq

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