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Bus passenger flow volume prediction method and system based on SPGAPSO-SVM algorithm

A prediction method and passenger flow technology, which is applied in the field of bus passenger flow prediction based on the SPGAPSO-SVM algorithm, can solve the problems of long time consumption of fitness and achieve good scalability, fast operation speed, and improved operation speed and efficiency Effect

Inactive Publication Date: 2020-02-07
INNER MONGOLIA UNIV OF TECH
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Problems solved by technology

[0007] The present invention provides a bus passenger flow prediction method and system based on the SPGAPSO-SVM algorithm to solve the problem in the above-mentioned background technology that the calculation fitness of the existing prediction model consumes too long time in the prior art

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  • Bus passenger flow volume prediction method and system based on SPGAPSO-SVM algorithm
  • Bus passenger flow volume prediction method and system based on SPGAPSO-SVM algorithm
  • Bus passenger flow volume prediction method and system based on SPGAPSO-SVM algorithm

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[0055] This embodiment: as figure 1 As shown, the bus passenger flow prediction method based on the SPGAPSO-SVM algorithm includes: constructing populations, segmenting and parallelizing S102 through the elastic distributed data set S101 of the fast general computing engine platform based on large-scale data processing, and Output the optimal system parameters S103.

[0056] Due to the use of elastic distributed data sets based on a fast general computing engine platform based on large-scale data processing for population construction, segmentation and parallel processing, and the output of optimal system parameters, due to the relevant research results in the field of bus passenger flow forecasting On the basis of in-depth analysis and research, the GAPSO-SVM algorithm based on GA and PSO was adopted in the parameter optimization stage of the traditional SVM prediction model, which solved the problem of low prediction accuracy of the traditional SVM prediction model; for the ...

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Abstract

The invention belongs to the technical field of bus passenger flow volume prediction, in particular to a bus passenger flow prediction method and system based on an SPGAPSO-SVM algorithm. The method comprises the steps that population construction, segmentation and parallelization processing are carried out through an elastic distributed data set of a rapid universal computing engine platform based on large-scale data processing; optimal system parameters are output. According to the method, the problem that in the prior art, the time consumed for calculating the fitness of an existing prediction model is too long is solved, and the method has the beneficial technical effects of being high in prediction accuracy, high in operation speed and good in expandability.

Description

technical field [0001] The invention belongs to the technical field of bus passenger flow forecasting, in particular to a bus passenger flow forecast method and system based on the SPGAPSO-SVM algorithm. Background technique [0002] Accurately predicting urban bus passenger flow is of great significance for scientifically making urban bus operation scheduling decisions and improving bus operation efficiency. In modern transportation systems, urban buses play an important role. Compared with other travel modes, public transport It has the characteristics of large passenger capacity, small sewage discharge, and low cost. In order to ensure the efficient and orderly operation of urban public transport, not only a good public transport operation management plan is required, but also effective operation scheduling is also essential. Accurate bus passenger flow forecast can provide effective decision support for urban bus operation scheduling; [0003] At present, scholars at ho...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/26G06N3/00G06N3/12G06N20/10
CPCG06N3/006G06N3/126G06Q10/04G06Q50/26G06N20/10
Inventor 李雷孝林浩邓丹王慧周成栋冯永祥
Owner INNER MONGOLIA UNIV OF TECH
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