Model training, state prediction method and device, electronic equipment and storage medium

A training method and predictor technology, applied in the field of deep learning, can solve the problem of low accuracy of car-hailing status, and achieve the effect of ensuring stickiness, improving car-hailing experience, and high practical value

Active Publication Date: 2021-05-28
BEIJING DIDI INFINITY TECH & DEV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of this, the purpose of this application is to provide a model training, state prediction method and device, electronic equipment and storage media to improve the problem of low accuracy of the car-hailing state predicted based on the existing prediction technology

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Model training, state prediction method and device, electronic equipment and storage medium
  • Model training, state prediction method and device, electronic equipment and storage medium
  • Model training, state prediction method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0108] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is only a part of the embodiments of the present application, but not all the embodiments. The components of the embodiments of the application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the application. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary ski...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The model training, state prediction method and device, electronic equipment, and storage medium provided by this application relate to the technical field of deep learning. In this application, a plurality of historical order information is obtained first. Secondly, the corresponding status identification information is obtained based on each historical order information, wherein the status identification information is used to characterize the status of the car booking based on the corresponding historical order information. Then, based on the historical order information and state identification information, the preset neural network model is trained to obtain the corresponding state prediction model, wherein the state prediction model is used to process the target user's car-hailing identification information to obtain The car-hailing status prediction information when the target order information is used for car-hailing, and the target order information is formed based on the car-hailing identification information. Through the above method, the problem of low accuracy of the car-hailing status predicted based on the existing prediction technology can be improved.

Description

technical field [0001] The present application relates to the technical field of deep learning, in particular, to a method and device for model training, state prediction, electronic equipment, and storage media. Background technique [0002] In order to improve the user's car-hailing experience, in the prior art, the car-hailing platform generally predicts the car-hailing status that may occur after the user places an order before the user places an order, and displays the predicted car-hailing status to the user. However, the inventors found that in the existing car-hailing state prediction technology, there is a problem of low accuracy. Contents of the invention [0003] In view of this, the purpose of this application is to provide a model training, state prediction method and device, electronic equipment and storage media, so as to improve the problem of low accuracy of the car-hailing state predicted based on the existing prediction technology. [0004] In order to ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q30/06G06K9/62G06N3/04G06N3/08
CPCG06Q10/04G06Q30/0635G06N3/08G06N3/045G06F18/24
Inventor 邱悦邓京东肜博辉
Owner BEIJING DIDI INFINITY TECH & DEV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap