Heydari Torkamani, M; Shahbazi, Y and Belali Oskoyi, A (2024) Explaining resilience model of historical bazaars using artificial neural network. Smart and Sustainable Built Environment, 13(6), pp. 1538-1559. ISSN 2046-6099
Abstract
Purpose: Historical bazaars, a huge treasure of Iranian culture, art and economy, are places for social capital development. Un-supervised management in past decades has led to the demolition and change of historical bazaars and negligence of its different aspects. The present research aims to investigate the resilience of historical bazaars preserving their identity and different developments. Design/methodology/approach: The artificial neural network (ANN) has been applied to investigate the resilience of historical bazaars. This model consists of three main networks for evaluating the resilience of historical networks in terms of adaptability, variability and reactivity. Findings: The ANN proposed to evaluate the resilience of historic bazaars based on the mentioned factors is efficient. By calculating mean squared error (MSE), the model accuracy for evaluating adaptability, variability and reactivity were obtained at 7.62e-25, 2.91e-24 and 1.51e-24. The correlation coefficient was obtained at a significance level of 99%. This indicates the considerable effectiveness of the artificial intelligence model in modeling and predicting the qualitative properties of historical bazaars resilience. Originality/value: This paper clarifies indexes and components of resilience in terms of adaptability, variability and reactivity. Then, the ANN model is obtained with the least error and very high accuracy that predict the resilience of historical bazaars.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | adaptability; artificial neural network; historical bazaar; reactivity; resilience; variability |
| Index terms: | bazaar, effectiveness, identity, modelling, variability, artificial intelligence, negligence, accuracy, social capital, artificial neural network, model accuracy, methodology, adaptability |
| Subjects: | sociology, statistical analysis, performance management, professional development, modelling and simulation, artificial intelligence, liability law, research methods, analytical methods, construction type, user focus |
| Topics: | Legal Issues, Quality Management, Engineering Principles, Design Practice, Digital Applications, Construction Technology, Research Practice, Information Management |
| Descriptive scope: | 3 PCT |
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