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Demand prediction method and system for shared equipment

A technology of shared equipment and forecasting methods, applied in the field of data processing, can solve problems such as loss of corporate profits, inconvenient use of users, and failure to find a car, achieving real-time forecasting, improved accuracy, and guaranteed accuracy

Inactive Publication Date: 2017-08-11
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, people have many problems in the process of using shared bicycles, one of which is the difficulty of riding a bicycle. Many users cannot find a car around when they need to rent a car. Idle cars, on the one hand, this brings great inconvenience to users, on the other hand, it also brings a lot of profit loss to enterprises

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  • Demand prediction method and system for shared equipment
  • Demand prediction method and system for shared equipment

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Embodiment Construction

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0031] The core of the present invention is to provide a method and system for forecasting the demand of shared equipment, which is used to predict the demand of shared equipment in an area in advance, thereby improving the utilization rate of shared equipment.

[0032] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention will be further described in detail below in conjunc...

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Abstract

The invention discloses a demand prediction method and system for shared equipment. The method comprises: acquiring positioning data of a target area within a predetermined time period; inputting the positioning data to a preprocessing layer of a pre-established neural network model, and processing the positioning data according to a preprocessing rule to obtain sample data corresponding to the target area; inputting the sample data to a hidden layer of the neural network model to carry out sample training; and after a prediction instruction is acquired, receiving current positioning data and inputting the current positioning data to the trained neural network model to obtain a prediction result. According to the method, the neural network model is established using a neural network algorithm, a large amount of sample data is trained by deep learning, and after the current positioning data is input, a prediction result of demand corresponding to the target area can be obtained, so that real-time prediction is realized. In addition, after the positioning data is acquired, the positioning data is preprocessed, so that the accuracy of the prediction result can be improved.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a demand forecasting method and system for shared equipment. Background technique [0002] In order to facilitate people's life, many shared devices have emerged, such as shared bicycles or shared cars. Bike sharing refers to the cooperation between enterprises and the government to provide bicycle sharing services in campuses, subway stations, bus stations, residential areas, commercial areas, public service areas, etc. A few days ago, various types of shared bicycles quickly became popular all over the country, and even extended overseas. [0003] However, people have many problems in the process of using shared bicycles, one of which is the difficulty of riding a bicycle. Many users cannot find a car around when they need to rent a car. Idle cars, on the one hand, have brought great inconvenience to users, and on the other hand, have also brought great loss of profit...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q30/02G06N3/04G06N3/08
CPCG06N3/08G06Q10/04G06Q30/0202G06N3/045
Inventor 张雁峰黄运保范西岸
Owner GUANGDONG UNIV OF TECH
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