The invention discloses a subway ventilation
system and method based on
big data analysis, relates to the technical field of ventilation management and control, and is used for dynamically adjusting the
operation time of ventilation equipment so as to achieve the purposes of guaranteeing the comfort of passengers and saving energy. Comprising the steps of collecting
station characteristics, the distance between stations and the
duration time of a ventilation effect required by determining an optimal strategy for starting the ventilation equipment; according to the
station characteristics, the stations are classified by using a clustering
algorithm, and the importance of the stations is determined; the importance of the stations, the distance between the stations and the duration of the ventilation effect are comprehensively considered, a
linear regression model is established, and the optimal strategy for starting ventilation equipment is predicted; the real-time temperature and the real-time
relative humidity in the compartment are obtained, the
comfort index is calculated through the Roseburg formula, and the
comfort index serves as the real-time environment; and the real-time environment in the compartment and the importance of the
station serve as input variables, and the
running time of ventilation equipment is adjusted through a
fuzzy logic control method.