A method for predicting the length of time a user waits during a VR generation process
By dynamically updating the adjustment factor for waiting time in the VR generation system and combining it with historical data from the operating load range, the prediction of user waiting time was optimized, the impact of operating load changes on accuracy was resolved, and more stable and efficient prediction was achieved.
CN121284302BActive Publication Date: 2026-06-23HANGZHOU BINGBINGQIZHANG NETWORK TECHNOLOGY CO LTD
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Patent Information
- Application Number
- CN202511831984.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-08
- Publication Date
- 2026-06-23
- Estimated Expiration
- 2045-12-08
AI Technical Summary
Technical Problem
In the current VR generation process, the accuracy of predicting user waiting time is affected by changes in the operating load, making it difficult to adjust effectively.
Method used
By determining the operating load variation data of the VR generation system, the adjustment factor for the waiting time is dynamically updated, and the generation data and duration data are updated within different operating load ranges to optimize the adjustment factor for the prediction duration.
Benefits of technology
It improves the accuracy of user waiting time prediction, avoids instability and excessive latency caused by frequent updates, and ensures the reliability and timeliness of adjustment factors.
✦ Generated by Eureka AI based on patent content.
Abstract
The application provides a method for predicting user waiting time in a VR generation process, and belongs to the technical field of data processing. The method specifically comprises the following steps: performing update processing on generation data and corresponding generation time data in an update load interval; and based on the update processing result of the generation data in the update load interval, determining whether the update processing of the generation data needs to be performed in a running load interval other than the update load interval based on the variation of the adjustment factor of the predicted time in different running load intervals when the update processing of the adjustment factor of the predicted time can be performed, so that the accuracy of the prediction result of the user waiting time is improved.
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