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CN-122020524-A - Teaching computer virtual system based on data fusion

CN122020524ACN 122020524 ACN122020524 ACN 122020524ACN-122020524-A

Abstract

The invention relates to the technical field of data processing, in particular to a computer virtual system for teaching based on data fusion, which comprises a data processing module, a scene generation module, an interaction module, a weight adjustment module, a correlation adjustment module and a gradient adjustment module, wherein the data processing module is used for acquiring multi-source teaching data and preprocessing the multi-source teaching data to obtain multi-source teaching characteristics, the scene generation module is used for fusing the multi-source teaching characteristics to obtain characteristic fusion results and combining teaching scene requirements to construct a virtual teaching scene, the interaction module is used for applying the virtual teaching scene to a computer to enable teachers and students to conduct interactive teaching, the weight adjustment module is used for determining minimum adaptation amount of multi-source teaching core characteristic weight according to the matching deviation ratio of the characteristic fusion results and the teaching scene, the correlation adjustment module is used for determining multi-source characteristic missing complementary correlation adaptation value according to the missing ratio of the multi-source teaching data, and the gradient adjustment module is used for determining fluctuation smooth gradient calibration degree of the multi-source teaching data according to the noise data occupation ratio of the multi-source teaching data. The virtual teaching scene construction method improves the construction effectiveness of the virtual teaching scene.

Inventors

  • ZHAO JIE

Assignees

  • 深圳市东方贤德科技有限公司

Dates

Publication Date
20260512
Application Date
20260119

Claims (10)

  1. 1. A data fusion-based computer virtual system for teaching, comprising: the data processing module comprises a data acquisition unit for acquiring multi-source teaching data and a preprocessing unit for preprocessing the multi-source teaching data to obtain multi-source teaching characteristics; The scene generation module comprises a fusion unit for fusing the multisource teaching features through a fusion algorithm to obtain a feature fusion result and a scene construction unit for constructing a virtual teaching scene according to the feature fusion result and teaching scene requirements; the interaction module is connected with the scene generation module and used for applying the virtual teaching scene to a computer so as to enable a user to conduct interactive teaching; The weight adjusting module is connected with the scene generating module and used for determining the minimum adaptive quantity of the multi-source teaching core feature weight according to the matching deviation rate of the feature fusion result and the teaching scene; the association adjustment module is respectively connected with the data processing module and the weight adjustment module and is used for determining a multisource characteristic missing complementary association adaptation value according to the missing rate of multisource teaching data; And the gradient adjustment module is respectively connected with the data processing module and the association adjustment module and is used for determining the fluctuation smooth gradient calibration degree of the multi-source teaching data according to the noise data duty ratio of the multi-source teaching data.
  2. 2. The computer virtual system for teaching based on data fusion according to claim 1, wherein the weight adjustment module determines that the construction effectiveness of the virtual teaching scene is not satisfactory in response to the matching deviation rate of the feature fusion result and the teaching scene being greater than a preset first deviation rate.
  3. 3. The teaching computer virtual system based on data fusion according to claim 2, wherein the weight adjustment module is used for initially determining that the acquisition integrity of the multi-source teaching data is not satisfactory in response to the matching deviation rate of the feature fusion result and the teaching scene being greater than the preset first deviation rate and less than the preset second deviation rate, and determining whether the acquisition integrity of the multi-source teaching data is satisfactory according to the deletion rate of the multi-source teaching data.
  4. 4. The data fusion-based computer virtual system for teaching according to claim 3, wherein the weight adjustment module increases a minimum adaptation amount of the multi-source teaching core feature weight in response to a match deviation ratio of the feature fusion result and the teaching scene being greater than or equal to the preset second deviation ratio; The increment of the minimum adaptive quantity of the multi-source teaching core feature weight is determined by the difference value between the matching deviation rate of the feature fusion result and the teaching scene and the preset second deviation rate.
  5. 5. The data fusion-based computer virtual system for teaching of claim 4, wherein the association adjustment module determines that the acquisition integrity of the multi-source teaching data is unsatisfactory in response to the deletion rate of the multi-source teaching data being greater than a preset first deletion rate.
  6. 6. The data fusion-based teaching computer virtual system of claim 5, wherein the association adjustment module increases a multi-source feature missing complementary association adaptation value in response to the multi-source teaching data missing rate being greater than the preset first missing rate and less than a preset second missing rate.
  7. 7. The teaching computer virtual system based on data fusion according to claim 6, wherein the association adjustment module is configured to initially determine that the acquired anti-interference performance of the multi-source teaching data does not meet the requirements in response to the deletion rate of the multi-source teaching data being greater than or equal to the preset second deletion rate, and determine whether the acquired anti-interference performance of the multi-source teaching data meets the requirements according to the noise data duty ratio of the multi-source teaching data.
  8. 8. The data fusion-based computer virtual system for teaching of claim 7, wherein the magnitude of the increase in the multisource feature missing complementary correlation adaptation value is determined by a difference between a missing rate of multisource teaching data and a preset first missing rate.
  9. 9. The data fusion-based computer virtual system for teaching of claim 8, wherein the gradient adjustment module determines that acquisition interference resistance of the multi-source teaching data is not satisfactory and increases fluctuation smooth gradient calibration of the multi-source teaching data in response to a noise data duty ratio of the multi-source teaching data being greater than a preset duty ratio.
  10. 10. The data fusion-based teaching computer virtual system of claim 9, wherein the magnitude of the increase in the multi-source teaching data fluctuation smooth gradient calibration is determined by a difference between a noise data duty cycle of the multi-source teaching data and a preset duty cycle.

Description

Teaching computer virtual system based on data fusion Technical Field The invention relates to the technical field of data processing, in particular to a computer virtual system for teaching based on data fusion. Background In the prior art, the suitability of the virtual teaching scene of the computer and the robustness of data fusion have obvious defects, the data fusion is mostly shallow splicing, quantization deviation judgment and dynamic adjustment closed loops are lacked, the core feature weight distribution depends on experience, and the problem that dominant features are diluted easily occurs, so that fusion results are disjointed with teaching targets. Meanwhile, the system does not design exclusive fusion logic aiming at scenes such as virtual training, virtual experiments and the like, lacks a data quality fault tolerance mechanism, and is easy to distort fusion results. In addition, the method does not consider the parameter differential configuration of different teaching scenes, does not adapt to the low-delay requirement required by virtual interaction, and is difficult to meet the actual requirements of accurate and personalized virtual teaching in education digital transformation. The Chinese patent publication No. CN119849971A discloses an interactive teaching system integrating multi-mode perception, which comprises a data acquisition module, a data storage module and an access control module, wherein the data acquisition module is used for collecting a multi-source original teaching data set and performing preliminary processing on the multi-source original teaching data set to acquire an original teaching data set, the original teaching data set covers student basic information data, learning process data and learning result data, the student basic information data comprises student name data, student gender data, student grade class data, student age data and student contact mode data, the learning process data comprises student class participation data and post-class learning duration data, the learning result data comprises student homework result data and examination result data, the data processing module is used for performing deep analysis on the original teaching data set to determine student learning state reference values and classifying students, the data storage module is used for storing the original teaching data set and the student learning state reference values, and the access control module is used for analyzing access data and establishing user rights. Therefore, the interactive teaching system integrating multi-mode perception has the problems that the system only realizes multi-source data acquisition, preliminary analysis and encryption storage, lacks a computer virtual scene adaptation mechanism, is not designed to dynamically adjust a closed loop, is easily influenced by data quality fluctuation, cannot interact with interactive feedback of virtual teaching, and causes insufficient construction effectiveness of a virtual teaching scene. Disclosure of Invention Therefore, the invention provides a computer virtual system for teaching based on data fusion, which is used for solving the problems that in the prior art, as only multi-source data acquisition, preliminary analysis and encryption storage are realized, a computer virtual scene adaptation mechanism is lacked, a dynamic regulation closed loop is not designed, a fusion result is easily influenced by data quality fluctuation and cannot be linked with interactive feedback of virtual teaching, so that the construction effectiveness of a virtual teaching scene is insufficient. In order to achieve the above object, the present invention provides a computer virtual system for teaching based on data fusion, including: the data processing module comprises a data acquisition unit for acquiring multi-source teaching data and a preprocessing unit for preprocessing the multi-source teaching data to obtain multi-source teaching characteristics; The scene generation module comprises a fusion unit for fusing the multisource teaching features through a fusion algorithm to obtain a feature fusion result and a scene construction unit for constructing a virtual teaching scene according to the feature fusion result and teaching scene requirements; the interaction module is connected with the scene generation module and used for applying the virtual teaching scene to a computer so as to enable a user to conduct interactive teaching; The weight adjusting module is connected with the scene generating module and used for determining the minimum adaptive quantity of the multi-source teaching core feature weight according to the matching deviation rate of the feature fusion result and the teaching scene; the association adjustment module is respectively connected with the data processing module and the weight adjustment module and is used for determining a multisource characteristic missing complementary association adaptation value