Provide an integrated model of fuzzy TOPSIS and neural networks

Abstract: Identifying the most important challenges and opportunities for advancing the process of resilient urban reconstruction before crises such as floods or earthquakes can have a significant impact on the performance of the city in the event of a crisis. Given the importance of the above topic, in the present dissertation, an attempt was made to first identify and evaluate the most important opportunities for physical development for the resilient reconstruction of cities. For this purpose, in the review of specialized texts, the concepts of resilience and its relationship with urban design were explained, and after explaining the theoretical framework of the research, to identify and evaluate the factors and process affecting resilience of urban reconstruction after floods or earthquakes. Also, opportunities for physical development after a possible flood or earthquake were studied in a case study in the city of Greater Tehran. Then, the most important physical, social, economic and psychological aspects for the reconstruction of cities after floods or earthquakes were evaluated and the sub-criteria of each of the identified factors, using multi-criteria decision methods of fuzzy TOPSIS and network Neutrally evaluated and ranked according to all the above, in the present study, first in the review of specialized texts, the concepts of resilience and its relationship with urban design in the field of resilient urban design will be explained and then the resilient reconstruction approach from the perspective Urban design will be examined. To this end, while stating the theoretical framework and the relationship between natural crises and urban development, efforts will be made to identify and evaluate the opportunities for physical development after the accident with an analytical model taken from global experiences and lessons learned from it. . To achieve this goal, first the most important aspects of post-crisis urban reconstruction, including physical, social, economic and psychological aspects will be evaluated and then the sub-criteria of each of the identified factors will be evaluated and ranked.

Keywords:

_Combined method of fuzzy TOPSIS and neural network , Natural crises , urban resilience