Public bicycle renting forecasting method based on multi-source data fusion
A public bicycle, multi-source data technology, applied in the field of urban intelligent public transportation system
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[0092] specific implementation
[0093] The present invention will be further described below in conjunction with drawings and embodiments.
[0094] Such as figure 1 As shown, a public bicycle rental prediction method based on multi-source data fusion includes the following steps:
[0095] Step (1) Data collection and processing:
[0096] Read the user's car rental records stored in the public bicycle system (PBS), calculate the remaining number of public bicycles at each station at each time period, and establish a vector N date =[n 1 ,n 2 ,...,n j ,...,n M ], M is the total number of time periods; obtain historical weather conditions, temperature and holidays from the Internet, and establish an environmental attribute vector S={S 1 ,S 2 ,...,S i ,...,S L}, S i =[d,w,t], L is the number of samples in the data sample set; M, L, i and j are all positive integers, where j≤M, i≤L;
[0097] The user car rental record includes rental time, rental site, rental car stake,...
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