Evaluation index determination method and system

A technology for evaluating indicators and determining methods. It is applied in neural learning methods, neural architectures, and biological neural network models. It can solve the problems of complex evaluation model construction and poor reuse of new data.

Pending Publication Date: 2020-04-03
BEIJING NORMAL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] Therefore, the present invention provides a method for determining evaluation indicators, which overcomes the defects of complex evaluation model construction and poor reuse of new data in the prior art

Method used

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  • Evaluation index determination method and system
  • Evaluation index determination method and system
  • Evaluation index determination method and system

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Experimental program
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Effect test

Embodiment 1

[0024] Embodiments of the present invention provide a method for determining an evaluation index, which is applicable to application scenarios where evaluation of target objects is required. like figure 1 As shown, the determination method of the evaluation index includes:

[0025] Step S1: Obtain the sample size of the object to be evaluated, the preset evaluation index data and the target evaluation variables.

[0026] In the embodiment of the present invention, the subjects to be evaluated can be students, teachers, schools, etc. In practical applications, the number of samples, preset evaluation index data and target evaluation variables can be reasonably selected according to the specific conditions of the evaluated objects. For example, when the objects to be evaluated are students, the optional sample size is the number of all students in a school or all students in an online learning course, and the default evaluation indicators are basic statistical indicators in the...

Embodiment 2

[0076] An embodiment of the present invention provides a system for determining evaluation indicators, such as Figure 4 As shown, the system includes:

[0077] The data acquisition module 1 of the object to be evaluated is used to obtain the sample size of the object to be evaluated, preset evaluation index data and target evaluation variables. This module executes the method described in step S1 in Embodiment 1, which will not be repeated here.

[0078] The data operation function library construction module 2 is used to build a data operation function library for performing data processing on the preset evaluation index data; this module executes the method described in step S2 in Embodiment 1, which will not be repeated here .

[0079] The hierarchical model building module 3 is used to construct a hierarchical model with a preset depth, and determine the hierarchical node where the preset evaluation index data is located; this module executes the method described in ste...

Embodiment 3

[0086] An embodiment of the present invention provides a terminal, such as Figure 5As shown, it includes: at least one processor 401 , such as a CPU (Central Processing Unit, central processing unit), at least one communication interface 403 , memory 404 , and at least one communication bus 402 . Wherein, the communication bus 402 is used to realize connection and communication between these components. Wherein, the communication interface 403 may include a display screen (Display) and a keyboard (Keyboard), and the optional communication interface 403 may also include a standard wired interface and a wireless interface. The memory 404 may be a high-speed RAM memory (Ramdom Access Memory, volatile random access memory), or a non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory 404 may also be at least one storage device located away from the aforementioned processor 401 . The processor 401 may execute the method for determining...

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PUM

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Abstract

The invention discloses an evaluation index determination method and system. The method comprises the steps: obtaining the sample number of a to-be-evaluated object, preset evaluation index data and atarget evaluation variable; constructing a data operation function library for performing data processing on the preset evaluation index data; constructing a hierarchical model of a preset depth, anddetermining a hierarchical node where the preset evaluation index data is located; obtaining an operation function of each preset evaluation index data and a preset weight of each preset evaluation index data; training evaluation index data and corresponding weights in the hierarchical model by using a neural network to obtain trained evaluation indexes and corresponding weights; according to thetrained evaluation index and the corresponding weight, determining the evaluation index of the to-be-evaluated object, the corresponding weight and the value of the target evaluation variable. According to the evaluation index determination method and system provided by the invention, the hierarchical model construction speed and the model accuracy can be improved, and the new application data can be quickly multiplexed.

Description

technical field [0001] The invention relates to the field of model building, in particular to a method and system for determining an evaluation index. Background technique [0002] The hierarchical model refers to the use of a "directed tree" data structure to represent various entities and the relationship between entities. Each node in the tree represents a record type, and the tree structure represents the relationship between entity types. In the field of education, researchers and decision makers often use hierarchical dimension models to construct multi-layer index dimension structures, and calculate the corresponding weights of each node to obtain the values ​​of the root node and each branch node through layer-by-layer calculations, so as to complete the evaluation of students and teachers. The evaluation and analysis model construction of subjects such as schools and schools. [0003] However, the existing relevant tools cannot quickly and conveniently help model d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N3/04
CPCG06N3/082G06N3/045
Inventor 陈丽郑勤华孙洪涛徐鹏飞王怀波杜君磊
Owner BEIJING NORMAL UNIVERSITY
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