The Construction of Comprehensive Evaluation System of Cloud Model for Postgraduates' Innovative Ability in China

2016 International Conference on Wireless Communication and Network Engineering (WCNE 2016) ISBN: 978-1-60595-403-5

The Construction of Comprehensive Evaluation System of Cloud Model

for Postgraduates' Innovative Ability in China

Qing-hua WANG

1

, Lan-fang CHENG

2

and Feng-qin ZHANG

2 1_{Beijing University of Technology, Institute of Laser Engineering}

2_{Beijing University of Technology, Institute of Economics and Management, Beijing (100124)}

Keywords: Cloud model, Fuzzy analytic hierarchy process (AHP), Innovation ability, Evaluation index.

Abstract. The innovation ability of Graduate student is one of the important factors affecting the quality of higher education in our country. At first, this paper puts forward evaluation factors of Postgraduates' innovation and Evaluation Index System, and uses the fuzzy analytic hierarchy process (AHP) to determine the index weight, considering the evaluation of graduate student innovation ability has the characteristics features of fuzziness and randomness ,summarizes the evaluation process of graduate students' innovation ability based on cloud model, to enrich and perfect the evaluation system of graduate student innovation ability. Conclusion shows that the cloud model for graduate student innovation ability evaluation and fuzzy analytic hierarchy process (AHP) can be well objective description, has good comprehensive and scientific.

Introduction

In today's world of the comprehensive national strength competition is essentially the competition of innovative talents and national innovation ability, and the construction of innovative countries have raised the national development strategy. With the rapid development of higher education in our country, the recruitment of students scale steady expansion and to develop education levels have made great progress. Graduate student is higher education to cultivate high-level objects, higher education assumes the responsibility of cultivating high-quality talents, especially the cultivation of graduate students innovative quality is very important. The existing graduate student's innovation ability needs scientific evaluation, and evaluation is the selection of evaluation index system and problem determination.

Graduate student innovation ability evaluation in our country has drawn the attention of many scholars, also produced many valuable research results about evaluation system and evaluation index, but previous studies also lack of fully considering the ability to innovate the concept of connotation and denotation of features, because every evaluation is the main subjective understanding of the involved, so the evaluation results has a certain randomness, vary from person to person. Not only such, level of innovation ability is a fuzzy concept, only the degree of discretion is relatively objective characterization and description, not arbitrarily as "high" or "low" and other qualitative conclusions. Therefore, the author thinks that the graduate student innovation ability concept itself exists certain randomness and fuzziness, only fully embodies the characteristics of the evaluation method is more scientific and objective. Based on the above consideration, this paper proposes a graduate student innovation ability evaluation system based on cloud model, in order to give a more scientific and reasonable graduate student innovation ability evaluation method, to enrich graduate student innovation ability evaluation system.

Introduction to Cloud Model

The Basic Concept of Cloud and Its Numerical Characteristics

Definition 1: A T is associated with theory of domain U = {X} language value. The fuzzy setAU_,

membership, membership in the distribution of domain known as the membership cloud, referred to as the cloud. That is:

 

A

A

[image:2.595.181.403.102.254.2]

 :U [0,1],xU,x_A

 

x

Figure 1. Digital characteristics of cloud model, meaning here.

From figure 1 shows, the desired function to represent the qualitative concept most likely points or the center of the theory of domain values. Entropy is a measure of uncertainty and ambiguity, is determined by the randomness and fuzziness of the concept of the common. Hyper entropy is entropy, namely entropy uncertainty of measurement of cloud droplets, primarily on the degree of discrete cloud and random metric.

Cloud Arithmetic and Its Two Comparisons

[image:2.595.88.507.438.678.2]

Cloud as a mathematical object, also has its operation as well as the comparison between the two, first is arithmetic, it is the most basic and commonly used in the application. Define its arithmetic rules as shown in Table 1.

Table 1. Normal cloud four algorithms.

operator _{Ex En He}

+

2 1

Ex Ex 2

2 2

1 En

En  He₁2He₂2

—

2

1 Ex

Ex  2

2 2

1 En

En  He₁2He₂2

 Ex1Ex2

2 2 2 2 2 1 2 1 2

1 |

x |

Ex En Ex En Ex

E  ₂

2 2 2 2 1

2 1 2

1 |

|

Ex He Ex He Ex

Ex 

 Ex1Ex2

2 2 2 2 2 1 2 1 2 1 _|

|

Ex En Ex En Ex Ex

 ₂

2 2 2 2 1 2 1 2 1 _|

|

Ex He Ex

He Ex Ex



Graduate Student Innovation Ability Evaluation Index and Method of Determining Weight

The Graduate Student Innovation Ability Evaluation Index System

[image:3.595.65.534.82.404.2]

Table 2. Graduate student innovation ability evaluation index system.

The evaluation index Index significance

Innovation motivation will Innovation motivation will is the important factors influencing the graduate student innovation ability.

Creative thinking ability

Creative thinking is the basic core ability and innovation ability. Innovative thinking embodied in don't blindly follow and trust, the spirit of challenging

authority, not superstition authority theory

Knowledge innovation ability

Knowledge innovation ability is the graduate student learning innovation knowledge, the ability to engage in knowledge accumulation.

Innovation practice ability

To graduate, real and concrete practical ability, can make its acutely aware of problems and phenomena, and through practice to think and to try to solve the problem, summarize and found the regularity of innovation, thus improve their

innovation ability.

Organization and coordination ability

Organization and coordination ability is to point to in the process of innovation practice according to the desire to complete the task of resource allocation, incentives and coordinates activities of innovation at the same time, mutual

confluence, to achieve organizational goals.

Innovation status

Innovation ability strong and the weak must eventually use through a variety of research results to reflect, no results output definitely cannot be called a high level

of graduate student training of innovation ability.

Graduate Student Innovation Ability Evaluation Index Weight Determining Method

In the process of graduate student innovation ability evaluation, each the influence degree of the influence factors on the final evaluation result is not the same, in order to objectively reflect the actual situation of graduate student innovation ability, must be to distinguish between the importance of each influence factor, in order to obtain the weight of each influence factor, and ultimately innovation ability evaluation result is given. Graduate student innovation ability evaluation system itself is a complicated multi-factor and multi-index evaluation process, not simply to distinguish with good and bad, ability to innovate the choice of the main factors affecting the weight determination method through the actual evaluation process and the composition of innovation ability evaluation index to select.

Table 3. Fuzzy membership degree evaluation standard.

scale Containing righteousness instructions

0.9

When compared with the two factors, the former xi _is

more important than the latter xj

If a factor relative to another factor has the scale

value (for example, 3) above, then, on the other

hand, the second factor value is relative to the first

scale for its reciprocal (e.g., a third) 0.7

The former xi _{is significantly more important than the}

latter xj

0.5 Two factors are equally important 0.3

The former xi _{is less important than the latter} xj

0.1

The former xi _{is less important than the latter} xj

0.2, 0.4,

0.6, 0.8 0.2, 0.4, 0.6, 0.8 is the median of two adjacent judgments; if the influence factor xi and

j x

importance compared to the scale ofr_ij, then xi _and xj _{the importance of}

[image:3.595.85.514.572.800.2]

Fuzzy analytic hierarchy process (AHP) is mainly based on the importance of innovation ability between influence factors are compared, and two fuzzy membership degree to use as shown in Table 3 evaluation scale to describe the relative importance between the two factors affecting coefficient, thus building up meet the consistency of fuzzy complementary judgment matrix. And the matrix inverse symmetry position values are.

If the accord with sum consistency fuzzy judgment matrix, can be further calculated on innovation ability evaluation index weight vector, expressed as W 



w₁,w₂,w₃,w₄,w₅,w₆



T

Graduate Student Innovation Ability Evaluation Method Based on Cloud Model

In order to more clearly illustrate the evaluation process, then, we present graduate student innovation ability based on cloud model of comprehensive evaluation modeling process:

Step 1: cloud data acquisition: suppose to n the graduate student's innovation ability evaluation, in the process of evaluation, selection of the evaluation of six factors in Table 1, namely, innovation motivation will

 

X1 , thinking ability

 

X2 , innovation knowledge ability

 

X3 , practical ability

 

X4 , organization coordinated ability

 

X5 , the condition of innovation

 

X6 as its innovation

ability evaluation index system. In order to make evaluation result more scientific and reasonable, to the ideas of integrated various, therefore, on the n in the process of graduate student innovation ability evaluation, using a questionnaire, advance design contains six evaluation factors of questionnaire survey, to involve to evaluate the influence factors of the innovation ability of graduate students and a questionnaire m, 0 to rate, ultimate recovery of valid questionnaires for k, and the valid questionnaires data selection and processing, thus to each for evaluation objects, get the corresponding cloud data, as symbols of C_i 



C_i1,Ci₂,Ci₃,Ci₄,Ci₅,Ci₆



Step 2: determine the index weight. On the importance of the six factors affecting graduate student innovation ability are compared, and two to use the comparison in Table 1 membership degree to express the importance of various factors, and compares the two complementary judgment matrix, consistency check, until satisfied consistency of complementary judgment matrix, the use of complementary judgement matrix, the weight export, determine the characterization of six major factors affecting the innovative ability of weights.

Step 3: weighted comprehensive evaluation. For a graduate student innovation ability influence factors of the evaluation results of the weighted, obtains each graduate student innovation ability of comprehensive evaluation result: Y_i w₁Ci₁w₂Ci₂ w₆Ci₆



i1,2,3,...n



Step 4: sorting. Each in the study, on the basis of the evaluation results



YEx_i,YEn_i,YHe_i



In turn calculation between two graduate student innovation ability evaluation result



YExi,YEni,YHei



closeness degree, fuzzy and random degree, thus get the cloud model of matrix,

fuzzy closeness degree matrix and random degree matrix.

Mark n order matrix respectively as follows:

12 1 21 2 1 2 0 0 0 n n n n DEx DEx DEx DEx AEx DEx DEx       _{ }     12 1 21 2 1 2 0 0 0 n n n n DEn DEn DEn DEn BEn DEn DEn       _{ }     12 1 21 2 1 2 0 0 0 n n n n DHe DHe DHe DHe CHe DHe DHe       _{ }    

For each stay evaluation objects, and other objects close to the degree of the evaluation results of n - 1 counterpoint to a row of the matrix, you need to further synthetical average all the evaluation results, so get the evaluation results of type according to the mean:

[image:4.595.93.521.625.695.2]

Its first i respectively a is the average close to the degree of evaluation object and other objects, fuzzy degree and average fuzzy degree. At this time, for each stay evaluation objects are cloud model with three characteristics under the meaning of the evaluation results.

To get a final value, should be three degree would be further integrated, considering the cloud is degree are indicator, its value shows that the stronger the innovation ability, the greater the degree and fuzzy and random as small as possible, so will be the first i graduate comprehensive evaluation value is defined as the final







i i







i



i



i MaxDEn DEn Max DHe DHe

DEx

Z_i     



i1,2,3,...n



Obviously, the greater the Zi numerical, which indicates that the graduate student's innovation ability. So it is to end up with a highly comprehensive evaluation value.

For every graduate Z₁,Z₂,Z₃Z_n to sort the innovation ability of comprehensive evaluation, gets the final comprehensive evaluation. If the descending (or ascending) is at the top (or behind) the object of relatively strong (weak).

Conclusion

With qualitative description of the objective things in the randomness of the fuzziness and results for characteristics of cloud model method, relative to the current mature other conventional evaluation methods, is used in a variety of comprehensive evaluation problem more objectively. Especially using cloud distribution characteristics of three important digital to depict the graduate student's innovation ability from different angles is more comprehensive, and thus further integrating it into another value is more simple, easy to work for other similar evaluation provides important methodology guidance, comprehensive evaluation method system.

Acknowledgements

This paper is supported by Beijing Research Base of Social Science Fund Project (15JDJGC016) and 2016 RiXin Fund Project (011000514116007) and BJUT Social Science Fund Project (011000514315507).

References

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