Predicting human development index using neural network regression: Insights and recommendations

Abstract

This study focuses on forecasting the Human Development Index (HDI) by applying neural network regression analysis. The HDI, an indicator used by the United Nations to assess advancement, covers a range of aspects including electricity usage, life expectancy, at birth income per person years of education on average gender equality issues, jobless rates, income distribution fairness, inflation levels, and overall human progress. Through the use of network regression techniques, this research seeks to delve into how these factors interrelate and improve accuracy in predicting data points. These findings indicate that the neural network regression model effectively predicts the HDI values with precision.