CN110189020A - A kind of colleges and universities' Intelligent campus construction level evaluation method - Google Patents
A kind of colleges and universities' Intelligent campus construction level evaluation method Download PDFInfo
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Abstract
The present invention, which provides one kind, can be included the following steps using machine automatic Evaluation, the high colleges and universities' Intelligent campus construction level evaluation method of accuracy, be determined index set and evaluate collection；Determine index set weight；Establish fuzzy relation matrix；Calculation Estimation vector.The analytic hierarchy process (AHP) that the present invention chooses can be by qualitative analysis and quantitative analysis effectively as a result, strong decision support can be provided for more rules decision problem.The combination of analytic hierarchy process (AHP) and Field Using Fuzzy Comprehensive Assessment reduces all kinds of complicated deductions, calculates, good to understand, is easy-to-use.This method can obtain the evaluation result of each level.It can be used for across comparison and the vertical analysis in similar campus.
Description
Technical field
The present invention relates to data processing fields, and in particular to a kind of colleges and universities' Intelligent campus construction level evaluation method.
Background technique
In the prior art colleges and universities' Intelligent campus construction level evaluation the disadvantage is that: by composite index/comprehensive score meter
It calculates technique study and index system establishment research to separate, the two emphasizes particularly on different fields；According to composite index/comprehensive score, wisdom is determined
The research of the descriptive grade of Campus Construction level is less；According to composite index/comprehensive score as a result, across comparison apply compared with
More, vertical analysis is using less；Index score, index weights are both needed to artificial determination, heavy workload, labor intensive.
Summary of the invention
To solve the above-mentioned problems, the present invention provides a kind of colleges and universities' Intelligent campus construction level evaluation method, including following
Step,
Determine index set and evaluate collection；
Determine index set weight；
Establish fuzzy relation matrix；
Calculation Estimation vector；
The determining index set and evaluate collection step include carrying out recognition of face to staff using human face recognition model,
The calculating of the human face recognition model loss function is as follows:
Wherein, N indicates the number of all samples pair,
yiIndicate sample label,Model prediction is indicated as a result, Np indicates the number of positive sample pair, Fi1Indicate positive sample pair
The feature of first picture, Fi2Positive sample is indicated to the feature of second of picture, λ indicates penalty coefficient, and value is in the present invention
0.01, w indicates the parameter in deep learning model.
Further, the index set includes,
Leading organ's data, responsibility data, construction plan data, management system data, financial support data, O&M
Service data, information security data, server data, data center's data, cable network data, wireless network data, campus
Network data, multi-media classroom data, wisdom classroom data, security monitoring data, teaching resources library data, Network Course number of passes
According to, experiment and real training data, tool software data, high property experiment with computing centre data, Library Digital Resources Construction data, number
Data, IT application in management platform data, teaching information platform data, transformation of scientific findings data, all-purpose card system are built according to library
It unites data, other service platform construction data, staff's training data, a variety of in resource and application data or one
Kind.
Further, the determining index set weight includes, using expert estimation, Evaluation Method, from colleges and universities' security system, base
Infrastructure, resource construction, application system are collected and determine each index weights, to true by the subjective weighting method of multiple evaluation experts
Fixed weight has carried out normalized, obtains weight vectors:
W=(w1,w2..., wn),
Wherein n is index number in assessment indicator system, wnFor each index weights,
The fuzzy relation matrix step of establishing includes establishing fuzzy matrix,
Wherein n is index number, and m is opinion rating number, rnmIt indicates when to n-th of index evaluation, is assessed as m grade
Expert's number/evaluation total number of persons ratio；
The Calculation Estimation vector step includes,
Evaluation model is established,
B=wR=(B1,B2,…,Bm)
Wherein, Bj(j=1m) indicate comprehensive all evaluation experts in the evaluation result of m grade；
The Calculation Estimation vector step includes greatest member B in evaluation vectorj(j=1m) as commenting
Surely develop the comprehensive score of grade.
The invention has the advantages that
The analytic hierarchy process (AHP) that the present invention chooses can be by qualitative analysis and quantitative analysis effectively as a result, can ask for more rules decision
Topic provides strong decision support.The combination of analytic hierarchy process (AHP) and Field Using Fuzzy Comprehensive Assessment reduces all kinds of complicated deductions, meter
It calculates, it is good to understand, is easy-to-use.This method can obtain the evaluation result of each level.It can be used for across comparison and the longitudinal direction point in similar campus
Analysis.
Detailed description of the invention
Fig. 1 is one embodiment of the invention flow chart.
Fig. 2 is one embodiment of the invention composite index/score determination process schematic diagram.
Specific embodiment
As various informationization technologies are in the depth of the application of China university, significant progress is obtained, is believed as education
The key of breathization, Intelligent campus theory be also with mobile Internet, Internet of Things, artificial intelligence development and be suggested and obtain
Certain development, as teaching quality, Scientific Research Service is horizontal, educates the Promoting Approach and target of Governance Ability.
Colleges and universities' Intelligent campus construction level is studied, colleges and universities is not only assisted in and completes more to standardize when informatization planning,
And self information work present situation and level can be measured.Colleges and universities' Intelligent campus construction level evaluation number is evaluation colleges and universities letter
The statistical indicator of the comprehensive condition of breathization construction level.
Colleges and universities' Intelligent campus construction level evaluation number, the main foundation including assessment indicator system, evaluation model are established
Two parts.The present invention is to be provided evaluation colleges and universities' Intelligent campus based on colleges and universities' Intelligent campus development reality and business demand and built
If horizontal method, this method provide scientific and reasonable appraisement system simultaneously, standard is provided for Intelligent campus construction, is required,
Data foundation is provided for the description of Intelligent campus construction level data.
The present invention provides invention and provides a kind of colleges and universities' Intelligent campus construction level evaluation method as shown in Figure 1, including following
Step,
Determine index set and evaluate collection；
Determine index set weight；
Establish fuzzy relation matrix；
Calculation Estimation vector.
Determine that index set and evaluate collection include 3 important steps:
Gather information, colleges and universities' Intelligent campus construction plan, content, existing technical research data collection work；
Analysis of data, according to building index system hierarchical structure principle, every grade of index is set up multiple specific respectively simultaneously
Sub- index.In numerous indexs, the index of close relation is classified as one kind, composing indexes group forms different indicator layers, favorably
In the image study object of full apparent.
Index system is established, checks that method, analytic hierarchy process (AHP) construct index colleges and universities Intelligent campus according to system analysis method, document
Construction level assessment indicator system.
Colleges and universities' Intelligent campus construction level assessment indicator system determines
According to the scientific and reasonable principle of building index system, hierarchical structure principle, change principle, scalability principle in right amount,
From colleges and universities' security system, infrastructure, resource construction, application system, other etc. in terms of 5, select following 29 indexs (can see
" the evaluation detailed rules and regulations/requirement " for the Intelligent campus level of IT application that judges), build up index system:
1. security system
Organization leadership: leading organ, responsibility；
Policy support: construction plan, management system, fund (funds) are supported；
Technological service: O&M service, information security；
2. infrastructure
Building environment: server, data center；
Network: cable network, wireless network, campus network；
Terminal construction: multi-media classroom, wisdom classroom, security monitoring；
3. resource construction
Teaching resource: teaching resources library, network courses, experiment and real training；
Scientific Research Resource: tool software, high-performance calculation experimental center；
Other resources: Library Digital Resources Construction, database establishment；
4. application system
Management application: IT application in management platform；
Teaching application: teaching information platform；
Industrial application: transformation of scientific findings；
It is served by: card system, other service platform constructions；
5. other
Informatization training: staff's training, resource and application.
The foundation of colleges and universities' Intelligent campus construction level evaluation number model, i.e. index calculating process
Index set weight step determining in implementation process of the present invention is illustrated below.
About weight determination method there are many, due to the constraint of Intelligent campus construction situation, using expert estimation, assessment
Method, from colleges and universities' security system, infrastructure, resource construction, application system, other etc. in terms of 5, collect, determine each index power
Weight, i.e., carry out tax power to layer index each in index system with subjective assessment.
Establish weight vectors
The weight determined to the subjective weighting method by multiple evaluation experts has carried out normalized.Obtain weight to
Amount:
W=(w1,w2..., wn),
Wherein n is index number in assessment indicator system, wnFor each index weights.
Establish fuzzy relation matrix
Wherein n is index number, and m is opinion rating number, rnmIt indicates when to n-th of index evaluation, is assessed as m grade
Expert's number/evaluation total number of persons ratio.
Calculation Estimation vector
Establish evaluation model:
B=wR=(B1,B2,…,Bm)
Wherein, Bj(j=1m) indicate comprehensive all evaluation experts in the evaluation result of m grade.
Calculation Estimation vector, evaluation score of the Intelligent campus construction level obtained in each grade.
It determines and develops grade comprehensive score
According to maximum membership degree principle, greatest member B in evaluation vectorj(j=1m) as evaluating development
The comprehensive score of grade, and can further make explanations to rating.
The present invention will be further explained with reference to the examples below:
Firstly, collecting the initial data for measuring the index system of certain colleges and universities' Intelligent campus construction level, and determine wisdom school
The evaluate collection of garden construction level.Each index is divided into m grades, which is to be responsible for judgement by expert to obtain, to each index
The marking expert of each grade keeps a record.
Evaluate collection is denoted as: V=(v1,v2,...,vm), m is evaluation set number, and under normal circumstances, m takes 3,5,7, not only
Meet the quality requirement of fuzzy overall evaluation, the grade commented ownership can also be made to have a intermediate grade.
Secondly, establishing index set weight, weight vectors are obtained by subjective weighting method:
W=(w1,w2..., wn)
Here, subjective weighting method uses analytic hierarchy process (AHP) (AHP), in " same level seeks Dan Quanchong " step, using minimum two
Multiplication is asked
Minimum value.Wherein, b is evaluation expert's number, is minimized, local derviation is sought to ω in both sides, makes it equal to 0.
Vector ω is found out, and obtains weight vectors after being standardized: W=(w1,w2..., wn), wherein each vector element
For each index weights.
Then, fuzzy relation matrix is established:
According to the initial data that each expert of collection gives a mark to each index, calculate to evaluate the mould of Intelligent campus construction level
Paste relational matrix:
Wherein n is index number, and m is opinion rating number, rij(i=1 ... n, j=1 ... m) are indicated to i-th of index evaluation
When, expert's number/evaluation total number of persons ratio of j grade is assessed as (it is assumed that colleges and universities' Intelligent campus construction level is m etc.
Grade).
Later, Calculation Estimation vector:
According to Comprehensive Fuzzy Evaluation principle, applicating evaluating vector calculation formula, weight vectors are multiplied by fuzzy relation matrix:
Wherein, Bj(j=1,2 ... ..., m) indicates score of the school in jth grade.
The evaluation result of each level can be obtained according to this formula.
Finally, the index score calculated evaluation model does final evaluation according to evaluation criterion.According to maximum membership degree original
Manage greatest member B in evaluation vectorjAs the comprehensive score for evaluating development grade, and last reality is done to " score " and is solved
It releases.With the same area same type, colleges and universities are compared, and obtain colleges and universities' Intelligent campus construction level objectively evaluates result.
It determines index set and evaluate collection step includes carrying out recognition of face to staff using human face recognition model.
In recognition of face link, a kind of novel modelling and loss function calculation method are introduced.In deep learning
When model training, the feature that the present invention extracts the different photos of the same person mentions the photo of different people to positive sample is considered as
The feature taken is to being considered as negative sample.In research before, only consider positive negative sample prediction result and label as close as,
And positive and negative sample characteristics are had ignored to similarity relationship itself.In the present invention, the present invention uses for reference the thought of SVM classifier, base
In positive and negative sample classification interval principle as big as possible, the optimal hyperlane of positive and negative sample classification is found, improves model to just
The distinction of negative sample improves the accuracy rate of recognizer.
The present invention distinguishes the feature of extraction feature pair in the middle layer of deep learning, and the present invention is denoted as fea1 and fea2, calculates
Method requires the fea1 and fea2 of positive sample as close as possible, and the fea1 and fea2 of negative sample become estranged as far as possible.In loss function
The middle present invention measures the similitude of feature with Euclidean distance.Also, the present invention joined regular terms in loss function, to prevent
Only model over-fitting, improves the generalization ability of model, further improves the accuracy rate of recognizer.The calculating of loss function
It is as follows:
Wherein, N indicates the number of all samples pair,
yiIndicate sample label,Model prediction is indicated as a result, Np indicates the number of positive sample pair, Fi1Indicate positive sample pair
The feature of first picture, Fi2Positive sample is indicated to the feature of second of picture, λ indicates penalty coefficient, and value is in the present invention
0.01, w indicates the parameter in deep learning model.
Claims (3)
1. a kind of colleges and universities' Intelligent campus construction level evaluation method, which is characterized in that include the following steps,
Determine index set and evaluate collection；
Determine index set weight；
Establish fuzzy relation matrix；
Calculation Estimation vector；
The determining index set and evaluate collection step include carrying out recognition of face to staff using human face recognition model,
The calculating of the human face recognition model loss function is as follows:
Wherein, N indicates the number of all samples pair,
yiIndicate sample label,Model prediction is indicated as a result, Np indicates the number of positive sample pair, Fi1Indicate positive sample to first
The feature of picture, Fi2Positive sample is indicated to the feature of second of picture, λ indicates penalty coefficient, and value is 0.01 in the present invention,
W indicates the parameter in deep learning model.
2. a kind of colleges and universities' Intelligent campus construction level evaluation method as described in claim 1, which is characterized in that the index set
Including,
Leading organ's data, responsibility data, construction plan data, management system data, financial support data, O&M service
Data, information security data, server data, data center's data, cable network data, wireless network data, campus network
Data, multi-media classroom data, wisdom classroom data, security monitoring data, teaching resources library data, network courses data are real
It tests and real training data, tool software data, high property experiment with computing centre data, Library Digital Resources Construction data, database
Build data, IT application in management platform data, teaching information platform data, transformation of scientific findings data, card system number
According to, other service platform construction data, staff's training data is a variety of or a kind of in resource and application data.
3. a kind of colleges and universities' Intelligent campus construction level evaluation method as described in claim 1, which is characterized in that
The determining index set weight includes, using expert estimation, Evaluation Method, building from colleges and universities' security system, infrastructure, resource
If, application system, collect and determine each index weights, the weight determined to the subjective weighting method by multiple evaluation experts carries out
Normalized obtains weight vectors:
W=(w1,w2..., wn),
Wherein n is index number in assessment indicator system, wnFor each index weights,
The fuzzy relation matrix step of establishing includes establishing fuzzy matrix,
Wherein n is index number, and m is opinion rating number, rnmIt indicates when to n-th of index evaluation, is assessed as the expert of m grade
Number/evaluation total number of persons ratio；
The Calculation Estimation vector step includes,
Evaluation model is established,
B=wR=(B1,B2,…,Bm)
Wherein, Bj, j=1m, evaluation result of the comprehensive all evaluation experts of expression in m grade；
The Calculation Estimation vector step includes greatest member B in evaluation vectorj, j=1m, as evaluating development
The comprehensive score of grade.
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Cited By (3)
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| CN111968431A (en) * | 2020-09-15 | 2020-11-20 | 石家庄小雨淞教育科技有限公司 | Remote education and teaching system |
| CN113034058A (en) * | 2021-05-10 | 2021-06-25 | 南京百伦斯智能科技有限公司 | Teaching evaluation method and system based on education data mining and analysis |
| CN116109456A (en) * | 2023-04-03 | 2023-05-12 | 成都大学 | Comprehensive evaluation method and system for intelligent education, electronic equipment and storage medium |
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Application publication date: 20190830 |