Public bike usage amount prediction method based on various factors

A technology of public bicycles and forecasting methods, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as unrecognizable weather, public site impact, etc., and achieve good control effects

Active Publication Date: 2017-09-08
ZHEJIANG UNIV CITY COLLEGE
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

However, since the ARIMA model can only consider the relationship between the time series

Method used

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  • Public bike usage amount prediction method based on various factors
  • Public bike usage amount prediction method based on various factors
  • Public bike usage amount prediction method based on various factors

Examples

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Embodiment Construction

[0027] The present invention will be further described below in conjunction with the examples. The description of the following examples is provided only to aid the understanding of the present invention. It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, some improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

[0028] One, overall thought of the present invention:

[0029] We mainly consider the following three aspects: how to adjust the forecast results in combination with weather factors; how to judge special situations in combination with site factors; and how to optimize the model in combination with time factors.

[0030] Two, this multi-factor based public bicycle usage forecasting method of the present invention, such as figure 1 As shown, the steps are as follo...

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Abstract

The invention relates to a public bike usage amount prediction method based on various factors. The method comprises the steps of establishing a training data set; carrying out cleaning and statistics on all data according to original data set information; determining a rainfall influencing coefficient; carrying out linear fitting according to rainfall and the bike rent and return number and adjusting the data set; searching nearby stations; calculating the nearest station through utilization of a K nearest neighbor (KNN) algorithm and determining the influencing coefficient of surrounding stations on the station; carrying out preliminary forecasting on setting parameters; inputting the setting parameters into the data set and establishing an autoregressive integrated moving average (ARIMA), thereby obtaining a preliminary forecasting result; adjusting the forecasting result and outputting a final result; and adjusting the result according to the rainfall coefficient and the station influencing coefficient and outputting the result. The method has the beneficial effect that according to a public bike system, the bikes of the stations can be regulated and controlled well through combination of real-time monitoring and prediction methods.

Description

technical field [0001] The invention relates to a method for predicting the amount of use of public bicycles, in particular to a method for predicting the amount of use of public bicycles based on multiple factors. Background technique [0002] In recent years, with the popularity of public bicycles, people are used to this green way of travel. However, the public bicycle system has been facing a problem. At different times, users have different needs for bicycles at bicycle stations. It often happens that there is no car to borrow when you need to use the car, or there is no car pile to return the car when you need to return it. return. Real-time monitoring of the status of bicycle stations cannot effectively solve this problem, because it takes a certain amount of time to regulate the number of bicycles, and during this period it may not be able to meet user needs. [0003] The ARIMA (autoregressive integral moving average) model is based on the autocorrelation analysis ...

Claims

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Application Information

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IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 郑增威陈思浓孙霖陈丹
Owner ZHEJIANG UNIV CITY COLLEGE
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