Trajectory preprocessing method for taxi data set

A data set and taxi technology, which is applied in electrical digital data processing, special data processing applications, database models, etc., can solve problems such as large amount of data, affecting the accuracy of calculation, and decreasing calculation speed.

Inactive Publication Date: 2017-07-21
HOHAI UNIV
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AI Technical Summary

Problems solved by technology

In some areas of the trajectory data, the distribution of points is very dense and the characteristics are similar. If it is not processed, it will first lead to a large amount of data and a decrease in calculation speed. Secondly, it will also affect the accuracy of calculation.

Method used

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  • Trajectory preprocessing method for taxi data set

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Embodiment Construction

[0031] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.

[0032] The taxi data set of the UCI machine learning library is the taxi location record data, and the data collection interval is 1 minute, including a total of 12,255 vehicles' positioning data for 6 consecutive days. The acquired raw text data mainly includes main information such as record keywords, vehicle number, date and time, longitude, latitude, direction, and instantaneous speed. This system studies a trajectory preprocessing method based on the taxi data set.

[0033] In order to facilitate the work of trajectory analysis and calculation, and preprocess the trajectory data, this system is based on the taxi data set of the UCI machine learning library, uses Eclipse development tools, and uses Java EE technology to design and implement a Web with trajectory data preprocessing. application.

[0034] A trajectory preprocessing system b...

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Abstract

The invention discloses a trajectory preprocessing method for a taxi data set. The method comprises the steps of firstly obtaining trajectory data, wherein each sampling trajectory point comprises longitude, latitude and timestamp information; secondly analyzing the trajectory data, performing abstract storage in entity objects, numbering trajectories, and adding trajectory point IDs; thirdly searching for missing values of the trajectories, and supplementing the missing values by utilizing a linear interpolation method or a mean value method; fourthly clustering the trajectory points, detecting abnormal points, and accurately analyzing and processing the abnormal points; fifthly detecting a data redundancy region, extracting redundant data and performing trajectory compression; sixthly searching for the trajectory points at the corners in the trajectories, generating a corner point set, combining and adjusting the corner point set, and performing trajectory cutting according to the corner point set; and finally updating and outputting the trajectory information. According to the method, the missing values can be processed; the abnormal points can be detected and processed; and complex and overlapped trajectories can be cut.

Description

technical field [0001] The invention belongs to the technical field of data preprocessing, in particular to a method for trajectory preprocessing based on a taxi data set in a UCI machine learning library. Background technique [0002] With the rapid development of location acquisition technologies such as sensor networks, satellites, and wireless communications, various moving objects generate large-scale trajectory data. Trajectory data usually includes trajectory sequence and trajectory points, among which: trajectory point is the atomic data of the recorded trajectory, which is composed of longitude, latitude and time stamp; trajectory sequence is composed of several containing trajectory points. The data in real life is complicated and messy, and there are often missing and entry errors in the collected data. It is also a normal phenomenon to have missing values ​​in the trajectory data. If it is not processed, it will greatly interfere with the calculation results. Th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/215G06F16/285
Inventor 叶枫吴胜艳邹由超
Owner HOHAI UNIV
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