Study on the relationship between house rent and people congestion by time in Tokyo based on mobile phone GPS data

Many previous studies showed that house rent is affected by residential property characteristics, house surrounding environment, facilities, and so on. However, there are few researches on finding the relationship between house rent and people’s activities. Thus, we used hourly location-based big data collected by mobile phone GPS data to monitor people’s activities all over the city. Multiple residential property characteristics and environments helped to verify if there is a relationship between house rent and people congestion in Tokyo. We find that people congestion has relationship with house rent and make more accurate prediction. We also employed linear and regularization regression and artificial neural network as algorithm and find artificial neural network might be the best calculation method.