A fuzzy inference system for predicting relief goods demand in the different scenarios of occurrence earthquake

Earthquake is one of the natural disasters that, depending on the scale, location, preventive measures, etc, can have financial and human effects to a large extent. Natural disasters have an uncertain nature. In other words, regarding the statistics related to such events, it is not possible to comment with high accuracy, which reveals the need to predict and estimate the dimensions of the possible effects of natural disasters. It should be noted that predicting the demand for relief goods and estimating the number of injured and displaced people as a result of these disasters can increase the efficiency of rescue operations and reduce the duration of this process, resulting in more services and reducing casualties costs. According to the mentioned cases and the necessity of conducting effective research from different aspects and in different fields, especially in the field of predicting and management of relief and disasters, this research was carried out. For this purpose, factors such as population ratios such as population density, texture erosion in different areas, earthquake time, and earthquake intensity based on the Richter scale, taking into consideration the opinions of experts in the field of geology and relief rescue, were used as inputs to the fuzzy inference system and the output of this system is determined by items such as the demand for biological, food, pharmaceutical goods, as well as the number of displaced and injured people.