Tourism Risk Prediction Model Developed Using Fuzzy Approach
Subject Areas : Urban Management Studies
امیر رضا خادم
1
(
مسئول مکاتبات
)
حامد صارمی
2
(
ندارد
)
Keywords: Tourism, Tourist, Fuzzy Logic, risk metropolitan,
Abstract :
Introduction and Aim: Prediction is based on the principles of sustainable development and achieving balance in complex and dynamic environments and Tourism is the second most lucrative industry in the world after oil. In this regard, the approach of using fuzzy - neural model to predict the risk tourism in complex and dynamic environments. To this end, first determine the number of process parameters affecting tourism in the Tehran metropolitan population was identified and then classified as input variables in 10 categories have been considered. Methods: The present study is the combination of documentation methods, analytical and mathematical. In this study, using statistical and research resources in ten of the 29 indicators of the structural, social, financial, health, psychological, cultural, safety, legal, political and terrorism extracted and studied in Tehran Metropolis . After classification, each of the variables using the membership functions of the linguistic variables are converted into qualitative and quantitative variables Results: Each fuzzy variable is entered into the system as a fuzzy neural network. After that, each variable is output as fuzzy inference system. After creating 10-phase network, the network output results as a major factor affecting risk is characterized by a certain weight. Finally, the main risk is calculated by weighting each of the statements concerning the risks Conclusion: Finally, Tehran, as a case study, has been calculated with 50% (average) risk of human-induced tourism.
