Method and device for predicting scenic spot passenger flow volume based on random forest algorithm

A technology of random forest algorithm and passenger flow, which is applied in the field of predicting passenger flow in scenic spots based on random forest algorithm, can solve problems such as difficulty in ensuring timeliness, unsatisfactory accuracy rate, difficulty in improving timeliness and accuracy of prediction models, etc., to ensure timeliness performance, improve accuracy, and reduce overhead

Pending Publication Date: 2020-05-19
上饶市中科院云计算中心大数据研究院
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AI Technical Summary

Problems solved by technology

First, due to the continuous increase of historical data, the time for model training is also increasing, making it difficult to guarantee the timeliness of prediction; second, the accuracy of prediction is related to features and prediction models, and the accuracy rate is not ideal due to features and training models
At present, there are many methods for predicting passenger flow in scenic spots, which provide some help for scenic spot management decision-making, but the timeliness and accuracy of the prediction model have been difficult to improve

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  • Method and device for predicting scenic spot passenger flow volume based on random forest algorithm
  • Method and device for predicting scenic spot passenger flow volume based on random forest algorithm
  • Method and device for predicting scenic spot passenger flow volume based on random forest algorithm

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[0039] The present invention will be described in detail below in conjunction with the implementations shown in the drawings, but it should be noted that these implementations are not limitations of the present invention, and those of ordinary skill in the art based on the functions, methods, or structural changes made by these implementations Equivalent transformations or substitutions all fall within the protection scope of the present invention.

[0040] The Random Forest (RF) algorithm is a classification and regression algorithm that integrates multiple decision trees (DecisionTree) through the idea of ​​Ensemble Learning. RF first uses the decision tree as the base classifier, then uses the Bagging (Bootstrap Aggregating) method to generate training data sets that are different from each other, and uses a strategy of random subspace division (Random Subspace Method) to construct each decision tree, and then from Some attributes are randomly selected from all attributes, ...

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Abstract

The embodiment of the invention discloses a method and a device for predicting scenic spot passenger flow volume based on a random forest algorithm, and the method comprises the steps: establishing arandom forest algorithm model with optimized parameters, debugging model parameters according to goodness of fit and an average standard error, and searching an optimal random forest algorithm model based on a grid search algorithm; and inputting the feature data set into the optimal random forest algorithm model to obtain the predicted future daily passenger flow volume of the scenic spot. According to the method and the device provided by the embodiment of the invention, the accuracy of the prediction model can be effectively improved, the timeliness of prediction is ensured, and managementof cities and scenic spots is facilitated.

Description

technical field [0001] This application relates to the technical field of artificial intelligence, in particular to a method and device for predicting passenger flow in scenic spots based on random forest algorithm. Background technique [0002] With the rapid development of my country's tourism industry, outbound tourism has become the norm of life, and the passenger flow of many scenic spots in my country changes significantly with the seasons, showing a typical seasonality. Whenever the passenger flow peaks, there will be congestion and chaos in different situations in the city and various tourist attractions, and even group frictions will occur, endangering the personal and property safety of tourists and causing great troubles to the management of the city and scenic spots. Therefore, there is an urgent need for a method that can predict the future passenger flow of tourist attractions. Scenic spot managers can take effective preventive measures in advance according to ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06K9/62G06Q50/14
CPCG06Q10/04G06Q50/14G06F18/214G06F18/241
Inventor 皮慧婷洪学海杨勇陈鑫
Owner 上饶市中科院云计算中心大数据研究院
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