Predicting the arrival time of firefighters at the scene of the incident using the fuzzy linear regression method(case study: Mashhad Fire Department)

Fire departments are important and vital service centers in urban areas that play an important role in ensuring the safety of people, assets and the environment. Obviously, the prompt response of firefighters, necessitating the effective allocation of fire departments, significantly decreases human and financial losses caused by incidents. Numerous factors influence timely service, which cannot be comprehensively analyzed by traditional methods due to the large volume of data. On the other hand, ignoring these factors can result in inaccurate results and decisions; hence, regression analysis tools that work with large data sets can be helpful in achieving the right results and decisions. Therefore, this research, for the first time, has developed a model using the fuzzy linear regression method in order to predict the arrival time of firefighters at the scene of the incident and allocated the most appropriate fire departments to the incident point based on data from the Mashhad Fire Department. The obtained results showed that the fuzzy linear regression method outperforms the regression models such as multiple linear,, ridge, support vector machine, and regression tree in terms of the coefficient of determination, mean square error, and mean square error of prediction metrics.