Methods and devices for building place crowding degree forecasting model and forecasting place crowding degree

A technology for predicting models and establishing methods, applied in the field of information processing, can solve problems such as waste of medical resources, inability to better serve patients with serious diseases and difficult miscellaneous diseases, delaying time for medical treatment, etc., to improve travel efficiency and reduce invalid waiting the effect of time

Active Publication Date: 2016-12-07
BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

And for some patients who are common diseases but acute diseases, such as acute gastroenteritis, etc., the long waiting time is even more unbearable.
[0004] At the same time, the outpatient and emergency departments of major tertiary hospitals are unable to better serve patients with serious diseases and difficult miscellaneous diseases due to the need to diagnose a large number of patients with common diseases such as drunkenness and colds.
High-quality and scarce medical resources are wasted in large quantities, causing people who really need to delay precious time for medical treatment

Method used

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  • Methods and devices for building place crowding degree forecasting model and forecasting place crowding degree
  • Methods and devices for building place crowding degree forecasting model and forecasting place crowding degree
  • Methods and devices for building place crowding degree forecasting model and forecasting place crowding degree

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Embodiment 1

[0031] figure 1 It is a flow chart of a method for establishing a place congestion prediction model provided by Embodiment 1 of the present invention. The method of this embodiment can be executed by a device for establishing a place congestion prediction model, and the device can be implemented by means of hardware and / or software , and generally can be integrated in the server used to realize the function of establishing the prediction model of the degree of congestion in the place. The method of this embodiment specifically includes:

[0032] 110. From the target place positioning data corresponding to the target place, acquire the target user positioning data corresponding to the floating personnel.

[0033] In this embodiment, the target place specifically refers to a public place where user experience is closely related to the number of people (or crowding) in the place. For example, places such as hospitals, shopping malls, playgrounds, stations, banks or stadiums.

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Embodiment 2

[0055] figure 2 It is a flow chart of a method for establishing a place congestion prediction model provided by Embodiment 2 of the present invention. This embodiment is optimized on the basis of the above-mentioned embodiments. In this embodiment, in the target place positioning data corresponding to the target place, the specific optimization of obtaining the target user positioning data corresponding to the floating personnel is as follows: the target place The positioning data is classified according to the user identification, and user positioning data corresponding to different users are obtained; the user positioning data corresponding to each user is divided into user interval positioning data under different time units; according to the user interval positioning data, Determining the stay time of each user in the target place under different time units; identifying floating personnel among the users according to the stay time, and acquiring target user positioning da...

Embodiment 3

[0089] image 3 It is a flow chart of a method for establishing a place congestion prediction model provided by Embodiment 3 of the present invention. This embodiment is optimized on the basis of the above embodiments. In this embodiment, according to the user interval positioning data, it is determined that the stay time of each user in the target place in different time units is specifically optimized as follows: The interval positioning data of the target user under the target time unit is used as the current processing positioning data; according to the departure confidence decay rule and each positioning time point in the current processing positioning data, the time when the departure confidence decays to the set decay value is obtained According to the mark time point, reversely deduce the departure time point when the target user leaves the target place; according to the positioning time point, obtain the arrival time of the target user corresponding to the departure t...

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Abstract

The embodiment of the invention discloses methods and devices for building a place crowding degree forecasting model and forecasting the place crowding degree. The method for building the place crowding degree forecasting model comprises the following steps: acquiring target user positioning data corresponding to floating people from target place positioning data corresponding to a target place; and training a standard time forecasting model according to a staying time parameter determined by the target user positioning data, and generating a crowding degree forecasting model corresponding to the target place. By means of the technical scheme disclosed by the invention, modeling of the crowding degree of a place is realized by screening useful data in mass positioning data, so that the built crowding degree forecasting model can be used for forecasting the amount of flowing people, entering the target place at different forecasting time points, within different staying time ranges, and a user can pre-judge the crowding degree of the place based on a forecasting result; and therefore, the travel efficiency of the user can be improved, and the invalid waiting time of the user in the target place is shortened.

Description

technical field [0001] The embodiments of the present invention relate to information processing technology, and in particular, to a method and device for establishing a place congestion degree prediction model, and a place congestion degree prediction method and device. Background technique [0002] With the popularity of smart terminal devices such as smartphones and tablets and high-speed wireless networks such as 4G in recent years, mobile applications have exploded. There are currently more than 1 billion 4G users in the world, and the total number of 3G and 4G users in the country is nearly 800 million. The mobile broadband at your fingertips has made people accustomed to using various services such as social networking, catering and entertainment provided by mobile applications. With the maturity and popularization of GPS positioning technology and cellular positioning technology, LBS (Location-Based Service, location-based service) has been used in various mobile app...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/26
CPCG06Q10/04G06Q50/26
Inventor 巢汉青曹原夏粉张军平张道强祁全昌
Owner BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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