Modeling of social vulnerability in Hesarak neighborhood of Karaj city by ANFIS method and tree regression

Social vulnerability is the creation of structural relationships between groups and forces of society against various pressures of nature and decisions and the capacity of society to respond and react to environmental hazards. Attracting immigrants with different geographical origins is one of the most important factors affecting the diversity of social structure and intensifying the sense of place in the city of Karaj. Research shows that in some areas of Karaj, such as Hesarak neighborhood (districts 5 and 6), due to the physical structure, especially the economic, social, cultural and marginal characteristics of residents, the opportunity for social harm is higher compared to other parts of the city. Due to the importance of this issue, the present study seeks to provide a model for social vulnerability indicators of this neighborhood to determine the pattern of these indicators and the impact of each of them on the satisfaction or dissatisfaction of residents of the neighborhood. The research method was analytical-exploratory in nature and the total population of households in the 5th and 6th districts of Karaj and the sample size were calculated using the Cochran's formula of 350 people.The research data were collected randomly from the study area through a query technique and using artificial neural network and infusion inference system to intelligent modeling (rule base) and tree regression model to estimate the factors affecting vulnerability. paid. The proposed model in this research is significant from several dimensions; The first result is the presentation of a methodology in this field that has been done with special architecture and the use of computational intelligence and environmental assessment knowledge base, and the second result is the creation of a knowledge base based on a set of criteria that can be intelligently Pay attention to the environmental conditions to assess the situation of the region as well as similar cases.