Microsoft Word - cet-01.docx CHEMICAL ENGINEERING TRANSACTIONS VOL. 46, 2015 A publication of The Italian Association of Chemical Engineering Online at www.aidic.it/cet Guest Editors: Peiyu Ren, Yancang Li, Huiping Song Copyright © 2015, AIDIC Servizi S.r.l., ISBN 978-88-95608-37-2; ISSN 2283-9216 Archives Management Evaluation of Colleges and Universities based on Fuzzy Mathematics Zhiying Sang Weifang University of Science and Technology, Shandong, Shouguang, China. 121585032@qq.com In colleges and universities, it is inevitable to evaluate archives management which is the focus of daily operation. This paper first confirms the indicators of the archives management evaluation index system for colleges and universities and then utilizes AHP to confirm their weights and fuzzy mathematical method to establish the evaluation model. The model gives results of the evaluation as 5 levels: very high, high, medium, low and very low. Expert judging method is utilized to judge al l secondary indexes and level judging vectors are then acquired. Finally the evaluation level is confirmed based on maximum principle . 1. Introduction Archives management is a very complicated job, especially in colleges where talents are cultivated. Archi ves management, in general, is divided into five parts: documents, educational archives, student records, scientific research records, and honors and awards. Currently, without unified management, archives management in colleges is relatively disordered. Therefore, archives management evaluation is an urgent job. 2. Establishing an Archives Management Evaluation Indicator System for Colleges and Universities An archives management evaluation indicator system for colleges and universities is established based on a large amount of related readings and telephone interviews to several colleges in Shandong Province. It is scientific, reasonable and feasible. The system contains three primary factors: technical indicator A (infrastructure A1; archives collection A2; archives management A3; archives query A4; archives statistics A5; archives security A6), human indicator B (number of staff B1; quality of staff B2; professional ability B3; staff turnover B4) and environmental indicator C (archives locationC1; priority given by leadership C2; investment by the school C3; attention from teachers C4). 3. Analytic Hierarchy Process Method and Fuzzy Mathematics Method 3.1 Analytic hierarchy process method Analytic hierarchy process method is an issue processing method to combine, systematize and layering qualitative and quantitative analyses of practical issues, which is abbreviated as AHP. AHP method divides the practical issues into several layers and compares the indicators layer to layer and further analyses, solves and predicates the issues. The process has 4 steps: 1. Based on archives management evaluation indicator system for colleges and universities, analyze the relationships between all factors and establishes the hierarchical chart of the system; 2. Compare the primary and secondary factors of archives management of colleges and universities and construct a comparative matrix of primary indicators. In comparison 1-9 scale values are normally adopted. Table 1 shows the values. DOI: 10.3303/CET1546202 Please cite this article as: Sang Z.Y., 2015, Archives management evaluation of colleges and universities based on fuzzy mathematics, Chemical Engineering Transactions, 46, 1207-1212 DOI:10.3303/CET1546202 1207 Table 1: 1-9 scale values of analytic hierarchy process method Scale aij 1 2 3 4 5 6 7 8 9 Comparison of I and j Same Slightly stronger Strong Obviously strong Absolutely strong 3. Utilize geometric method to calculate relative weight vectors of primary and secondary factors of archives management of colleges and universities. The calculation has three steps which are: (1) Calculate the product of every line of factors in the comparative matrix, acquire vector  ; (2) Conduct n-order extraction calculation to vector  to acquire vector  ; (3) Conduct normalization processing to vector  to acquire index weight vector  . 4. Conduct consistency check to the comparative matrix and maintain it within specified error range due to the existence of subjective factors. The checkout procedure has three steps which are: (1) Calculate coincident indicators of the comparative matrix max 1    n CI n  . 1 max 1 1      n ij jn j i i a r n r  is the maximum eigenvalue of the comparative matrix; (2) Confirm random coincident indicators according to the value of n . Specific values are shown in Table 2; Table 2: Random coincident indicators of the comparative matrix n 1 2 3 4 5 6 7 8 9 10 11 12 RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.54 (3) Calculate consistency ratio of the comparative matrix  CI CR RI , when 0.10CR , the matrix passes the consistency check. 3.2 Fuzzy mathematics method Fuzzy mathematics method is commonly used in fuzzy decision issue. It is a key to make reasonable and comprehensive evaluation to a practical problem that is affected by various index factors. This method mainly adopts the membership degree theory of fuzzy mathematics. Based on confirming the evaluation factor sets and judgement sets of archives management of colleges and universities, it constructs a judgment matrix of the secondary factors and finally confirms the evaluation level of archives management. 1. Confirm the evaluation factor sets  1 2, , , nP p p p of archives management of colleges and universities. The evaluation object has n factors; 2. Confirm the judgment sets  1 2 5, , ,V v v v of archives management of colleges and universities. All secondary factors are divided into 5 levels; 3. Confirm the fuzzy evaluation matrix 5 ( )   ij n R r of archives management of colleges and universities, the process has two steps: (1) Generate an evaluation ( ) i f p for each factor i p ( 1, 2, ,i n ), acquire a fuzzy reflection map f ( P to V ): 1 2 : ( ), ( ) ( , , , ) ( )    i i i i im f P F P p f p r r r F V (2) Induce fuzzy relation ( )  f R F P V from fuzzy reflection map f : ( , ) ( )( )  f i i i i ij R p v f p v r , 1, 2, ,i n ; 1, 2, ,j m , Then finally fuzzy judgment matrix ( )   ij n m R r is acquired. 4. According to the weight vectors of each level of factors of archives management of colleges and universities, the comprehensive judgment vectors  Tw R are calculated by matrix multiplication. 1208 4. Building an Archives Management Evaluation Model for Colleges and Universities 4.1 Adopt layer comparison method to confirm the weights of each factor of archives management of colleges and universities. 1. Construct the layer structure map of archives management of colleges and universities (Figure 1). Figure 1: Layer structure map 2. Adopt expert judgment method to construct a comparative matrix of primary factors and secondary factors of archives management of colleges and universities. 10 experts are invited to score the importance level of each level of factors of archives management of colleges and universities. After averaging the scores, the impact levels of each factor and the comparative matrix are confirmed: P, A, B, C, D, and E. 3. Calculate the weight vectors of each level of factors of archives management of colleges and universities. Results acquired are: P  , A  , B  , C  , D  , 4. Conduct consistency check, make sure that 0.10CR . 4.2. Building an archives management evaluation model for colleges and universities based on fuzzy mathematics method 1. Put all of 14 secondary factors into the factor sets  1 2 14, , ,P p p p of archives management of colleges and universities; 2. Construct the evaluation sets  1 2 5, , ,V v v v of archives management of colleges and universities, dividing its performance into 5 levels: very high, high, medium, low and very low. Specific levels are shown in table 3: Table 3: Level evaluation sets of secondary factors of archives management of colleges and universities Secondary factors Evaluation levels infrastructureA1 Very good Good Medium Low Very low archives collection A2 Very good Good Average Low Very low archives management A3 Very good Good Average Low Very low archives queryA4 Very good Good Average Low Very low archives statistics A5 Very good Good Average Low Very low archives security A6 Very good Good Average Low Very low number of staffB1 Very good Good Average Low Very low quality of staff B 2 Very good Good Average Low Very low professional ability B 3 Very good Good Average Low Very low staff turnover B 4 Very good Good Average Low Very low archives locationC1 Very good Good Average Low Very low priority given by leadership C2 Very good Good Average Low Very low investment by the school C 3 Very good High Average Low Very low attention from teachersC 4 Very good Good Average Low Very low 1209 3. Confirm the fuzzy evaluation matrix ( )   ij n m R r of archives management of colleges and universities and then use expert judgment method to conduct level evaluation to secondary factors y of archives management of colleges and universities. 10 experts are invited to do so: ( ) ( ) ( ) 11 12 15 ( ) ( ) ( ) 41 42 45            A A A A A A A r r r r r r R ,  10 ij number of experts who give level of j r ， B R , C R , D R , E R are acquired in line with this formula. 4. According to the weights of each secondary factor of archives management of colleges and universities, the fuzzy evaluation matrix of 3 primary factors are acquired as:   T T T T T T P A A B B C C D D E E R R R R R R     , Lastly the level evaluation vectors of archives management of colleges and universities are calculated according to the weights of the primary indexes:  T P P w R , Based on the maximum principle, the level that corresponds to the maximum vector w is the evaluation level of archives management of colleges and universities. 5. Model Calculation and Application 5.1. By means of expert interview (10 experts) and questionnaire investigation, the comparative matrix of archives management of colleges and universities is confirmed. Specific results are listed in table 4-7: Table 4: Comparative matrix and inspection results of archives management of colleges and universities Objective level Evaluation of archives management of colleges and universities P Maximum eigenvalue Consistency ratio Primary factors technical indicator A human indicator B environmental indicator C Weight technical indicator A 1 7 9 0.7928 3.0217 0.0209 human indicator B 1/7 1 2 0.1312 environmental indicator C 1/9 1/2 1 0.0760 Table 5: Comparative matrix and inspection results of technical indicator A Primary factors technical indicator A Maximum eigenvalu e Consistenc y ratio Secondary factors Infrastructur e A1 archives collectio n A2 archives managemen t A3 archive s queryA4 archives statistic s A5 archive s security A6 weight infrastructureA 1 1 3 2 7 4 1/4 0.2155 6.4324 0.0686 archives collection A2 1/3 1 2 5 3 1/7 0.1227 archives management A3 1/2 1/2 1 6 2 1/3 0.1156 archives queryA4 1/7 1/5 1/6 1 1/3 1/9 0.0274 archives statistics A5 1/4 1/3 1/2 3 1 1/5 0.0625 Primary factors technical indicator A archives security A6 4 7 3 9 5 1 0.0456 3 1210 Table 6: Comparative matrix and inspection results of technical indicator B Primary factors human indicator B Maximum eigenvalue Consistency ratio Secondary factors number of staffB1 quality of staff B 2 professional ability B 3 staff turnover B 4 weight number of staffB1 1 1/3 1/6 5 0.1179 4.1851 0.0693 quality of staff B 2 3 1 1/3 7 0.2642 professional ability B 3 6 3 1 9 0.5794 staff turnover B 4 1/5 1/7 1/9 1 0.0385 Table 7: Comparative matrix and inspection results of technical indicator C Primary factors environmental indicator C Maximum eigenvalue Consist ency ratio Secondary factors archives locationC1 priority given by leadership C2 investment by the school C3 attention from teachers C4 weight archives locationC1 1 1/8 1/6 1/3 0.0485 4.1037 0.0388 priority given by leadership C2 8 1 3 6 0.5815 investment by the school C3 6 1/3 1 3 0.2627 attention from teachers C4 3 1/6 1/3 1 0.1073 5.2. Invite 10 experts to conduct level judgment to the secondary factors of archives management of one college. Results are shown in table 8: Table 8: Level judgment results of secondary factors of archives management of one college Secondary factors Level judgment results infrastructureA1 3 5 1 1 0 archives collection A2 1 3 5 1 0 archives management A3 2 4 4 0 0 archives queryA4 5 3 2 0 0 archives statistics A5 0 2 5 2 1 archives security A6 0 1 7 1 1 number of staffB1 0 2 6 2 0 quality of staff B 2 1 2 4 2 1 professional ability B3 4 5 1 0 0 staff turnover B 4 2 4 3 1 0 archives locationC1 4 3 3 0 0 priority given by leadership C2 1 2 4 3 0 investment by the school C 3 0 2 6 1 1 attention from teachers C 4 1 3 5 1 0 5.3. The evaluation vector of archives management level of this college is calculated as:  0.1318 0.2378 0.2239 0.0669 0.0140w , According to the maximum principle, the evaluation level of archives management of this college is: high. 6. Conclusions Evaluation research of archives management of colleges and universities are relatively few and that there are still many problems in archives management for colleges. Problems to be solved include: lack of unified management mechanism, low facility updating, low level of human resource and lack of funds. Evaluation of 1211 archives management is able to urge colleges and universities to pay more attentions to it by increasing funds, updating facility, speeding up digitalization process and enhancing level of human resource. These mentioned above are of far-reaching significance for archives management of colleges and universities. References Bu H.B., Bu S.Z., 2012, Two-Layer Fuzzy Comprehensive RSA-ANP-DSS Evaluation Model of Emergency Management Capacity about Enterprise Value Network [J]. 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