Evaluation of the application of BIM technology based on PCA - Q Clustering Algorithm and Choquet Integral

Transcription

1 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal Evaluaton of the applcaton of BIM technology based on PCA - Q Clusterng Algorthm and Choquet Integral We Xaozhao, Hong Wenxa, Yang Fan, Jang Zhenyao Qngdao Unversty of Technology, Qngdao, Shandong , Chna a @qq.com, b @qq.com Keywords: PCA-Q Clusterng; Choquet ntegral ; BIM Technology. Abstract: For the development of the constructon ndustry, the constructon of data era s approachng, BIM (buldng nformaton model) wth the actual needs of the constructon ndustry has been wdely used as a buldng nformaton clan system software, dfferent software for the practcal applcaton of dfferent maturty, through the expert scorng method for the applcaton of BIM technology maturty ndex mark, establsh the evaluaton ndex system, usng PCA - Q clusterng algorthm for the evaluaton ndex system of classfcaton, comprehensve evaluaton n combnaton wth the Choquet ntegral on the classfcaton of evaluaton ndex system, to acheve a reasonable assessment of the applcaton of BIM technology maturty ndex. To lay a foundaton for the future development of BIM Technology n varous felds of constructon, at the same tme provdes drecton for the comprehensve applcaton of BIM technology. 0 Preface Snce Chna entered the twenty-frst Century, the rapd development of economc constructon, wth the ncreasng progress of economy, the constructon ndustry chan has been a huge nfluence, buldng the applcaton of nformaton technology has also been a good development, BIM technology s a cuttng-edge technology of global constructon of nformaton technology n our country, the promoton of the development of.bim technology has attracted much attenton and has been appled n the actual constructon proect wth hs famly thought, but the BIM techncal nformaton structure s huge, there s no guarantee that all software can be appled to practcal engneerng, the applcaton of BIM technology maturty evaluaton s conducve to the development of BIM technology and mprovement, can make more practcal applcaton of BIM technology drect, strengthen the promoton of BIM technology, ndrectly provdes the drecton for the development of BIM technology. 1 Overvew of applcaton of BIM Technology 47

2 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal Under the trend of global economc socety, ndustralzaton, ndustralzaton, the ncreasngly close relatonshp between the nformaton and nformaton factors become economc and socal development s one of the mportant factors.bim technology archtecture exhbton ndustry, nformaton technology, as the core wll become ncreasngly comprehensve development to adapt to the needs of the actual engneerng, the engneerng proect n BIM Technology of collaboratve management more convenent and effcency, the management of.bim technology wll be closely ntegrated proect specfc techncal level and management level, the combnaton of tools and technques to proect whole lfe cycle management, reasonable and effectve control of engneerng proect n the varous stages of the operaton, to ensure smooth operaton of each proect. 2 Classfcaton of PCA applcaton maturty evaluaton ndex based on Q - BIM clusterng algorthm By the experts on the BIM technology applcaton maturty evaluaton ndex system for scorng, each ndex s composed of 10 factors, the table s as follows: 1: From table 1 shows, each level ndcator s vewed as a 10 dmensonal vector, a total of dmensonal vector consstng of hgh-dmensonal data sets, n order to ensure the ratonalty of the data classfcaton, prncpal component analyss method and Q type clusterng combnaton method, the screened reasonable data group to the overall response number accordng to the characterstcs. The method through the PCA of ndcators for dmensonalty reducton, low dmensonal embeddng data expressed as data manfold lnear smoothng functon combnaton, Q type clusterng algorthm was then used to reduce the dmenson of the data set, cluster analyss was conducted, and the ndex system of reasonable classfcaton. 1)Standardzed processng of raw data [2-5] When the prncpal component analyss s carred out, the dmenson of the ndex s often dfferent, so the nfluence of the dmenson should be elmnated before the prncpal component s calculated [6-8].Standardzaton of raw data transform are as follows: x * x x 1,2,..., n; 1,2,..., p s (1) Among: x, n x s ( x x ) n 1 1 n n

3 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal Table 1 BIM applcaton maturty evaluaton ndex score ndex Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 Factor 8 Factor 9 Factor 10 Data completeness and avalablty Data mutual Conflct detecton capablty nformaton content Support professonal Spatal localzaton ablty Hardware capablty Tmelness of nformaton transmsson Access control Change management and Applcaton lfe cycle Busness nformaton flow Basc equpment Human resource management Product based, servce orented Contract system Regulaton Reserve forces )Computng covarance matrx s p p,among 49

4 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal n 1 s, 12,,, p (2) ( x x )( x x ) k k n 1 k1 3)Fnd the egenvalues of the covarance matrx Characterstc vectors after orthogonal varaton a Covarance matrx m Characterstc value of a feature vector m 0,Just before m Varance values correspondng to the prncpal components., Correspondng unt feature vector a Prncpal component F On the coeffcent of the orgnal varable,the orgnal varableno. Prncpal component score F by: F a X (3) Varance (nformaton) contrbuton rate of prncpal component s used to reflect the sze of nformaton, by: m / 1 (4) 4)Select prncpal component Fnally to select a few man components,that s F1, F2,, F n m Is determned by the varance m (nformaton) cumulatve contrbuton rate G m To determne. m Gm ( ) / k p 1 k1 (5) When the prncpal component s worth the cumulatve contrbuton rate of more than 85%, t can be found that the performance of the ntal varables can be reflected by the nformaton. 5)Calculate prncpal component load 50

5 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal Prncpal component loadng s a reflecton of the prncpal component scores F wth Intal varable X The close degree,intal varable X( 12,,, p) In each man score F( 12,,, m) Load n l( 1,, 2, m; 1,, 2, p) : l( Z, X ) a ( 1,2, L, m; 1,2, L, p) (6) 6)Prncpal component score Calculate sample n m Score on a prncpal component: F a X a X a X 1,, 2, m (7) p p Solvng model: Usng Matlab programmng, the 8 man components, the cumulatve contrbuton rate reached 91.22%, can be clearly seen as the man component of the flter has a strong representatve and reasonable. Table 2 prncpal component analyss Prncpal component category Characterstc value Indvdual contrbuton rate Cumulatve contrbuton rate Data completeness and avalablty Conflct detecton capablty nformaton content Hardware capablty Tmelness of nformaton transmsson Change management system Busness nformaton flow Product based servce

6 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal By usng the Q clusterng algorthm to classfy the prncpal components, the specfc steps are as follows: 1)set up ={ w, w, w,... w },Calculate the dstance between 8 sample ponts matrx D ( d ) , p 1 n n 2 2 d( x, y) [ xk yk ] k1 ; d,record as a 2) The preparaton of 8 knds of data, each class contans only one sample pont, all knds of platform heght s 0; 3)The nearest two class s a new class, and the dstance between the two classes s the heght of the platform; 4)Calculate the dstance between the new class and other types of values, f the class number s equal to 1, the transfer step (5), not equal to 1 when the return to the step (3); 5)Determnes the number and class of classes. Table 3 results of cluster analyss prncpal component Data abundance and relablty Conflct detecton capablty nformaton content Hardware capablty Real-tme nformaton transmsson Change management operaton flow Products and servces category Evaluaton of prncpal component ndex by Choquet fuzzy ntegral Combned wth BIM technology applcaton maturty ndex, ndex factors, the man factor as a fuzzy aggregaton operator, usng Choquet fuzzy ntegral,its defnton s as follows:set a fnte sety=y 1, y2, y3,... y n 1, y n,the functon s defned as the Y (x) dscrete functon, and the functon value sy x ), y( x ), y( x )... y( x ), y( x ),The assumpton functon y (x) s monotone ( n 1 n ncreasng,that s y x ) y( x ) y( x )... y( x ) y( x ),Then defne [11] Y (x) n the X on the fuzzy ( n 1 n measure of the Choquet fuzzy ntegral: n ( x) d ( A ) 1 y( x ) y( x 1 X,ntegral form: ( x 0 ) 0 y, A x x,..., x (10), 1 n 52

7 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal Choquet s an extenson of weghted average operator. The above fuzzy ntegral can be used to sort the domnant elements n order to get the fnal BIM technology applcaton maturty sort, and the applcaton effect of BIM technology to complete the comprehensve evaluaton. Sort results are shown n table 4: Table 4 man component ndex sort results prncpal component category sort Data abundance and relablty 1 3 Conflct detecton capablty 2 2 nformaton content 2 4 Hardware capablty 1 6 Real-tme nformaton transmsson 1 1 Change management 2 5 operaton flow 2 7 Products and servces Concluson Ths paper ntroduces the concept of BIM technology applcaton, reference to the Unted States on the applcaton of BIM technology maturty standards [12],In accordance wth the prncple of scentfc ratonalty gradng on the applcaton of BIM Technology Maturty, and gves the applcaton of BIM Technology mature degree ndex system, accordng to the expert's score, usng PCA-Q type clusterng algorthms for data processng, classfcaton, combnaton of Choquet fuzzy ntegral derved the prncpal component (ndcators) sort, drect reflect the maturty of the applcaton of BIM Technology gap, for the future development of the technology and applcaton of Bm and provde convenence. References 53

8 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal [1] He Guanpe. What's that thng called BIM.[M],Beng:Chna Buldng Industry Press, 2012: [2] Cao Fuyuan. Research on clusterng algorthm for categorcal data[d].tayuan:shanx Unversty,2010. [3] Wang Ll. Spectral clusterng algorthm[d].zhengzhou:henan Unversty,2012. [4]Zhou Ln, Xu Sen, Png X Jan, Zhang Tao. Integrated clusterng algorthm based on spectral clusterng[j]. Journal of automaton,2012,08: [5]Xu Xaol. Research on mage segmentaton algorthm based on clusterng analyss[d].harbn Engneerng Unversty,2012. [6]Dng Shfe, Ja Honge, the hstory of Zhongzh.Adaptve clusterng algorthm for large data Nystr spectrum based on M samplng [J]. Journal of software,2014,09: [7]Zhang Yapng. Spectral clusterng algorthm and ts applcaton[d].north Central Unversty,2014. [8]Ln L, pan nsurance. The wnd farm cluster partton method splt herarchy clusterng algorthm based on sem supervsed spectral[j]. Electrc power automaton equpment,2015,02:8-14. [9]L Yong, Changsheng tube. Informaton management mode and strategy of engneerng proect based on BIM Technology[J]. Journal of Engneerng Management,2012,04: [10]Wu Shuangyue. Research on nformaton classfcaton and codng system of archtecture based on BIM[D].Beng Jaotong Unversty,2015. [11]Huang Je, L Bcheng, Zhao Yongun. Target threat assessment method based on fuzzy ntegral Choquet [J],2012,13(1) [12]Sun Chengshuang, Jang Fan, Man Qngpeng. A revew of the applcaton of BIM technology n the constructon ndustry[j].journal of Engneerng Management,2014,03: Author ntroducton We Xaozhao (1991-), male, graduate student. Research drecton: Cvl Engneerng and engneerng cost management. Work unt: Qngdao Technologcal Unversty. 54

9 IETI Transactons on Busness and Management Scences, 2016, Volume 1, Issue 1, An Internatonal Open Access Journal Hong Wenxa (1964-), female, master's degree. Ttle: Qngdao Technologcal Unversty, Professor, master's tutor. Research drecton: Cvl Engneerng and engneerng cost management. Work unt: Qngdao Technologcal Unversty. Jang Zhenyao (1992-), female, master's degree graduate student. Research drecton: cvl engneerng constructon cost management. Work unt: Qngdao Technologcal Unversty. Contrbutor contact: We Xaozhao Tel: Contrbutor malbox: Malng address: Qngdao Economc Development Zone No. 2 Changang Rver (old campus of Qngdao Technologcal Unversty) 55