Construction mechanism of whitenization weight function and its application in grey clustering evaluation
|
摘要
The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clustering rule relies on the construction of the whitenization weight function, while the existing construction method of the linear function lacks the construction mechanism analysis and validity explanation. A normative construction principle is put forward by analyzing the construction mechanism of the function. Through proving the normative principle of the function,the basic modal function(BMF) is proposed and characterized by different function forms. Then, a new type of the whitenization weight function and its grey clustering evaluation model algorithm are given by studying the mechanism and nature of the construction of different forms of the function. Finally, the comparative study for self-innovation capability of defense science and technology industry(DSTI) is taken as an example. The results show that the different construction ways of the function have an effect on the clustering result. The proposed construction mechanism can better explain the index clustering rules and evaluation effectiveness,which will perfect the theoretical system of grey clustering evaluation and be applied to practice effectively.
The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clustering rule relies on the construction of the whitenization weight function, while the existing construction method of the linear function lacks the construction mechanism analysis and validity explanation. A normative construction principle is put forward by analyzing the construction mechanism of the function. Through proving the normative principle of the function,the basic modal function(BMF) is proposed and characterized by different function forms. Then, a new type of the whitenization weight function and its grey clustering evaluation model algorithm are given by studying the mechanism and nature of the construction of different forms of the function. Finally, the comparative study for self-innovation capability of defense science and technology industry(DSTI) is taken as an example. The results show that the different construction ways of the function have an effect on the clustering result. The proposed construction mechanism can better explain the index clustering rules and evaluation effectiveness,which will perfect the theoretical system of grey clustering evaluation and be applied to practice effectively.
The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clustering rule relies on the construction of the whitenization weight function, while the existing construction method of the linear function lacks the construction mechanism analysis and validity explanation. A normative construction principle is put forward by analyzing the construction mechanism of the function. Through proving the normative principle of the function,the basic modal function(BMF) is proposed and characterized by different function forms. Then, a new type of the whitenization weight function and its grey clustering evaluation model algorithm are given by studying the mechanism and nature of the construction of different forms of the function. Finally, the comparative study for self-innovation capability of defense science and technology industry(DSTI) is taken as an example. The results show that the different construction ways of the function have an effect on the clustering result. The proposed construction mechanism can better explain the index clustering rules and evaluation effectiveness,which will perfect the theoretical system of grey clustering evaluation and be applied to practice effectively.
引文
[1]LIU W,WU C,CHANG X,et al.Evaluating remanufacturing industry of China using an improved grey fixed weight clustering method-a case of Jiangsu province.Journal of Cleaner Production,2016,142(4):2006-2020.
[2]GUO J,ZHAO X,HUANG Y.Grey clustering evaluation of urban low-carbon transport development based on triangular whitenization weight function.Grey Systems:Theory and Application,2015,5(3):278-289.
[3]XIN J H.Evaluation of auto parts remanufacturing by grey cluster model.Grey Systems:Theory and Application,2016,6(3):296-308.
[4]HAN T,LUO S,ZHU H,et al.A novel trust evaluation model based on grey clustering theory for routing networks.Journal of Computers,2013,8(11):2743-2749.
[5]MA F,HE J,MA J P,et al.Evaluation of urban green transportation planning based on central point triangle whiten weight function and entropy-AHP.Transportation Research Procedia,2017,25:3638-3648.
[6]DENG J L.Grey prediction and decision making.Wuhan:Huazhong University of Science and Technology Press,1986.(in Chinese)
[7]LIU S F.On grey clustering evaluation model with fixed weight:new methods of grey system.Beijing:Agricultural Press,1993.(in Chinese)
[8]LIU S F,ZHU Y D,LI B J.Study on triangular model and indexes in synthetic evaluation of regional economy.Transactions of the Chinese Society of Agricultural Engineering,1993,9(2):8-13.(in Chinese)
[9]DANG Y G,LIU S F,LIU B,et al.Research on grey comprehensive clustering method with no significant difference in clustering coefficient.Chinese Management Science,2005,13(4):69-73.(in Chinese)
[10]LIU S F,XIE N M.New grey evaluation method based on reformative triangular whitenization weight function.Journal of Systems Engineering,2011,26(2):244-250.(in Chinese)
[11]LIU S F,FANG Z G,YANG Y J.Two stages decision model with grey synthetic measure and a betterment of triangular whitenization weight function.Control and Decision,2014,29(7):1232-1238.(in Chinese)
[12]XIAO X P,XIAO W.Grey optimal clustering theory model and its application.Operations Research and Management,1997,6(1):21-26.(in Chinese)
[13]MI C M,LIU S F,DANG Y G,et al.Study on grey entropy weight clustering decision-making.Systems Engineering and Electronics,2006,28(12):1823-1825.(in Chinese)
[14]DONG Y Z,DANG Y G.Grey clustering method based on maximizing deviations.Systems Engineering-Theory&Practice,2009,29(9):141-146.(in Chinese)
[15]WANG Z X,DANG Y G,LIU S F.Variable weight grey clustering based on classification of whitenization weight function.Statistics&Information Forum,2011,26(6):23-27.(in Chinese)
[16]MENG W,LIU S F,ZENG B,et al.Standard triangular whitenization weight function and its application in grey clustering evaluation.Journal of Grey System,2012,24(1):39-48.
[17]LI L J,WANG X.Research of grey evaluation model based on CCTWF and its application:taking the evaluation of the hydraulic projects management modernization as an example.Hebei Journal of Industrial Science&Technology,2015,32(4):295-301.(in Chinese)
[18]LIU S F,YANG Y J,FANG Z G,et al.Grey cluster evaluation models based on mixed triangular whitenization weight functions.Grey Systems:Theory and Application,2015,5(3):410-418.
[19]PANG B,LI Y X,TONG L.Application of grey clustering method and fuzzy comprehensive assessment method to assess eutrophication level of water quality.Environmental Science&Technology,2011,34(11):185-188.(in Chinese)
[20]LI L,WANG R,LI X.Grey fuzzy comprehensive evaluation of regional financial innovation ability based on two types weights.Grey Systems:Theory and Application,2016,6(2):187-202.
[21]YAO T,CHENG W R,GAO H.The natural disaster damage assessment of Sichuan province based on grey fixed weight cluster.Grey System:Theory and Application,2016,6(2):415-425.
[22]ZHANG G B,LI X C,QI F Y,et al.Grey cluster estimating model of soil organic matter content based on hyperspectral data.Proc.of the IEEE International Conference on Grey Systems and Intelligent Services,2014:335-339.
[23]LI P,GAO H Y,SUN H.Seismic performance evaluation of rural houses based on combined grey-AHP and grey clustering.World Earthquake Engineering,2014,30(3):164-168.
[24]JIANG H X.Evaluation of auto parts remanufacturing by grey cluster model.Grey System:Theory and Application,2016,6(3):309-321.
[25]WU Y N,WANG Z.The post-evaluation of green residential building in Ningxia.IOP Conference Series:Earth and Environmental Science,2017:012004.
[26]SU B T,XIE N M.Research on safety evaluation of civil aircraft based on the grey clustering model.Grey System:Theory and Application,2018,8(1):110-120.
[27]LIN Y,CHEN M,LIU S F.Theory of grey systems:capturing uncertainties of grey information.Kybernetes,2004,33(2):196-218.
[28]LIU S F,LIN Y.Grey systems:theory and applications.Berlin:Springer-Verlag,2011.
[29]LIU S F,FORREST J,YANG J Y.A brief introduction to grey systems theory.Grey Systems:Theory and Application,2012,2(2):89-104.
[30]LIU S F.Explanation of terms of grey clustering evaluation models.Grey System:Theory and Application,2017,7(1):123-128.
[2]GUO J,ZHAO X,HUANG Y.Grey clustering evaluation of urban low-carbon transport development based on triangular whitenization weight function.Grey Systems:Theory and Application,2015,5(3):278-289.
[3]XIN J H.Evaluation of auto parts remanufacturing by grey cluster model.Grey Systems:Theory and Application,2016,6(3):296-308.
[4]HAN T,LUO S,ZHU H,et al.A novel trust evaluation model based on grey clustering theory for routing networks.Journal of Computers,2013,8(11):2743-2749.
[5]MA F,HE J,MA J P,et al.Evaluation of urban green transportation planning based on central point triangle whiten weight function and entropy-AHP.Transportation Research Procedia,2017,25:3638-3648.
[6]DENG J L.Grey prediction and decision making.Wuhan:Huazhong University of Science and Technology Press,1986.(in Chinese)
[7]LIU S F.On grey clustering evaluation model with fixed weight:new methods of grey system.Beijing:Agricultural Press,1993.(in Chinese)
[8]LIU S F,ZHU Y D,LI B J.Study on triangular model and indexes in synthetic evaluation of regional economy.Transactions of the Chinese Society of Agricultural Engineering,1993,9(2):8-13.(in Chinese)
[9]DANG Y G,LIU S F,LIU B,et al.Research on grey comprehensive clustering method with no significant difference in clustering coefficient.Chinese Management Science,2005,13(4):69-73.(in Chinese)
[10]LIU S F,XIE N M.New grey evaluation method based on reformative triangular whitenization weight function.Journal of Systems Engineering,2011,26(2):244-250.(in Chinese)
[11]LIU S F,FANG Z G,YANG Y J.Two stages decision model with grey synthetic measure and a betterment of triangular whitenization weight function.Control and Decision,2014,29(7):1232-1238.(in Chinese)
[12]XIAO X P,XIAO W.Grey optimal clustering theory model and its application.Operations Research and Management,1997,6(1):21-26.(in Chinese)
[13]MI C M,LIU S F,DANG Y G,et al.Study on grey entropy weight clustering decision-making.Systems Engineering and Electronics,2006,28(12):1823-1825.(in Chinese)
[14]DONG Y Z,DANG Y G.Grey clustering method based on maximizing deviations.Systems Engineering-Theory&Practice,2009,29(9):141-146.(in Chinese)
[15]WANG Z X,DANG Y G,LIU S F.Variable weight grey clustering based on classification of whitenization weight function.Statistics&Information Forum,2011,26(6):23-27.(in Chinese)
[16]MENG W,LIU S F,ZENG B,et al.Standard triangular whitenization weight function and its application in grey clustering evaluation.Journal of Grey System,2012,24(1):39-48.
[17]LI L J,WANG X.Research of grey evaluation model based on CCTWF and its application:taking the evaluation of the hydraulic projects management modernization as an example.Hebei Journal of Industrial Science&Technology,2015,32(4):295-301.(in Chinese)
[18]LIU S F,YANG Y J,FANG Z G,et al.Grey cluster evaluation models based on mixed triangular whitenization weight functions.Grey Systems:Theory and Application,2015,5(3):410-418.
[19]PANG B,LI Y X,TONG L.Application of grey clustering method and fuzzy comprehensive assessment method to assess eutrophication level of water quality.Environmental Science&Technology,2011,34(11):185-188.(in Chinese)
[20]LI L,WANG R,LI X.Grey fuzzy comprehensive evaluation of regional financial innovation ability based on two types weights.Grey Systems:Theory and Application,2016,6(2):187-202.
[21]YAO T,CHENG W R,GAO H.The natural disaster damage assessment of Sichuan province based on grey fixed weight cluster.Grey System:Theory and Application,2016,6(2):415-425.
[22]ZHANG G B,LI X C,QI F Y,et al.Grey cluster estimating model of soil organic matter content based on hyperspectral data.Proc.of the IEEE International Conference on Grey Systems and Intelligent Services,2014:335-339.
[23]LI P,GAO H Y,SUN H.Seismic performance evaluation of rural houses based on combined grey-AHP and grey clustering.World Earthquake Engineering,2014,30(3):164-168.
[24]JIANG H X.Evaluation of auto parts remanufacturing by grey cluster model.Grey System:Theory and Application,2016,6(3):309-321.
[25]WU Y N,WANG Z.The post-evaluation of green residential building in Ningxia.IOP Conference Series:Earth and Environmental Science,2017:012004.
[26]SU B T,XIE N M.Research on safety evaluation of civil aircraft based on the grey clustering model.Grey System:Theory and Application,2018,8(1):110-120.
[27]LIN Y,CHEN M,LIU S F.Theory of grey systems:capturing uncertainties of grey information.Kybernetes,2004,33(2):196-218.
[28]LIU S F,LIN Y.Grey systems:theory and applications.Berlin:Springer-Verlag,2011.
[29]LIU S F,FORREST J,YANG J Y.A brief introduction to grey systems theory.Grey Systems:Theory and Application,2012,2(2):89-104.
[30]LIU S F.Explanation of terms of grey clustering evaluation models.Grey System:Theory and Application,2017,7(1):123-128.