Analysis of Iranian Society and it`s Threshold of Tolerance, Modeling Social Resilience Using Artificial Neural Networks
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
In this applied study, analysis of Iranian society and its threshold of tolerance has been done in a descriptive-analytical method. The society were professors of universities and the sampling size were 133. Data collection was done in archive and field methods. The reliability of the questionnaire was 89%. A multilayer perceptron artificial neural network was created to predict and model the human development index of the 38 target countries. Four input parameters were life expectancy at birth, expected years of schooling, mean years of schooling, and gross national income per capita". The response parameter was the human development index. The 4000 structures were developed, trained, validated, and tested by changing the variables of activation function, training function, and the number of neural neurons in the hidden layer. The optimal neural network in terms of network performance measures was the network with mean absolute percentage error (MAPE = 0.01156), Normalized Root Mean Square Error (NRMSE = 0.00124), and R squared (R2=0.99620). The optimal network had ten neurons in the hidden layer, a tansig activation function, and an RP training function. The artificial neural network model had a high accuracy in predicting the human development index. Based on the results of sensitivity analysis, the most influential factors were mean years of schooling, "life expectancy at birth, expected years of schooling, and gross national income per capita, with the relative importance of 33.63%, 24.43%, 23.83%, and 18.11%, respectively.
Keywords:
Language:
Persian
Published:
Journal of Strategic Management Studies, Volume:14 Issue: 57, 2025
Pages:
207 to 232
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