Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Mixture Gaussian probability density weighting based grading model and system

A mixed Gaussian and model technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as depression, loss of scoring information, and improvement of scoring

Inactive Publication Date: 2015-04-01
伍度志 +5
View PDF4 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

On the one hand, different experts have different levels of recognition for players, resulting in different scoring points. Therefore, it is reasonable to rate players differently. If the level of players is evaluated by removing the highest and lowest scores, it is obvious that It will lose the scoring information, so it is not advisable; on the other hand, because the existing scoring method adopts the method of taking the average value, the weight of each expert is equal, so it cannot effectively solve the problem of a small number of experts deliberately lowering or increasing the scoring

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
  • Mixture Gaussian probability density weighting based grading model and system
  • Mixture Gaussian probability density weighting based grading model and system
  • Mixture Gaussian probability density weighting based grading model and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The present invention will be described in detail below in conjunction with examples.

[0028] Example description: In a large-scale competition, a total of 10 judges rate the competition level of all contestants. The scores of the two contestants A and B are respectively:

[0029] S A =(70, 72, 85, 87, 86, 90, 94, 91, 89, 90)

[0030] S B =(78,84,87,88,87,86,89,85,86,87)

[0031] (1) Data distribution fitting

[0032] The two sets of data were fitted separately using a mixture of Gaussian distributions. In this patent, the EM algorithm is used to estimate the parameters in the mixed Gaussian distribution. Assuming that the mixed Gaussian distribution is composed of two Gaussian distributions, the score data is first normalized to the (-1, 1) interval. Calculate the parameters of players A and B as:

[0033] alpha A =(0.8197, 0.1803) α B =(0.8306, 0.1694)

[0034] mu A =(10,10.2) μ B =(9.8,10.1)

[0035] σ A =(11,13) σ B =(10,13)

[0036] (2) Interval div...

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 invention discloses a mixture Gaussian probability density weighting based grading model and system. According to the mixture Gaussian probability density weighting based grading system, a distribution function can be fit through mixture Gaussian distribution according to the dispersion degree of grading by experts and the weight can be reasonably arranged according to the probability density of the function. Compared with the prior art, the mixture Gaussian probability density weighting based grading system has the advantages of 1 being capable of fitting an actual distribution function well and guaranteeing the validity of a fitting result in theory; 2 fairly reflecting the level of an evaluation level due to the fact that the grading weight of the experts can be automatically adjusted according to fitting distribution; 3 not damaging the grading data information of the experts due to a grading system. After grading data is obtained, parameter values of the mixture Gaussian distribution can be obtained through an EM algorithm, then weight is given for every subdata through the probability density function, the final score of a player is a weight sum of scores of the experts, and finally a grading model program is embedded to ARM board hardware to achieve interactive operation. The mixture Gaussian probability density weighting based scoring model is widely applied to a game with many judges.

Description

technical field [0001] The invention relates to a scoring model and system based on Gaussian mixture distribution probability density, which is mainly used in various evaluation systems and expert scoring systems. technical background [0002] Scoring is an incentive measure adopted by various fields and all walks of life in order to carry forward the advanced and select the best among the best. In order to avoid the influence of personal factors on the real level of the contestants, a number of judges are arranged to score the contestants in various evaluation activities. The two currently popular expert scoring methods are: ① directly sum the scores of all experts and take the average; ② first remove the highest and lowest scores in the expert scores, and then sum and average, also known as "removing the two ends" Scoring method. [0003] Although the above two methods are widely accepted and applied in most fields, obvious disadvantages can still be found. On the one h...

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 Applications(China)
IPC IPC(8): G06F19/00
Inventor 伍度志方海洋宗福兴赵静汪辉李小蓉
Owner 伍度志
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com