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An Assembly Coastal Building Technique in Port Engineering 被引量:1
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作者 陈育民 刘汉龙 +1 位作者 陈泽 高玉峰 《China Ocean Engineering》 SCIE EI 2009年第2期379-386,共8页
The assembly coastal building technique initiated at home and abroad,is for a novel vertical standing harbor structure.Its main concept is the assembling components which can be combined and locked together to form a ... The assembly coastal building technique initiated at home and abroad,is for a novel vertical standing harbor structure.Its main concept is the assembling components which can be combined and locked together to form a large caisson.Its application and future are discussed for a building.After many years of application and tests,the technique has a high stability,a wide range of application,low workload and fast construction speed.It can be widely applied in future for harbor engineering projects. 展开更多
关键词 Assembly techniques frame structure open-ended caisson port engineering
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Principal Model Analysis Based on Bagging PLS and PCA and Its Application in Financial Statement Fraud
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作者 Xiao LIANG Qiwei XIE +2 位作者 Chunyan LUO Liang TANG Yi SUN 《Journal of Systems Science and Information》 CSCD 2024年第2期212-228,共17页
Motivated by the Bagging Partial Least Squares(Bagging PLS)and Principal Component Analysis(PCA)algorithms,a novel approach known as Principal Model Analysis(PMA)method is introduced in this paper.In the proposed PMA ... Motivated by the Bagging Partial Least Squares(Bagging PLS)and Principal Component Analysis(PCA)algorithms,a novel approach known as Principal Model Analysis(PMA)method is introduced in this paper.In the proposed PMA algorithm,the PCA and the Bagging PLS are combined.In this method,multiple PLS models are trained on sub-training sets,derived from the training set using the random sampling with replacement approach.The regression coefficients of all the sub-PLS models are fused in a joint regression coefficient matrix.The final projection direction is then estimated by performing the PCA on the joint regression coefficient matrix.Subsequently,the proposed PMA method is compared with other traditional dimension reduction methods,such as PLS,Bagging PLS,Linear discriminant analysis(LDA)and PLS-LDA.Experimental results on six public datasets demonstrate that our proposed method consistently outperforms other approaches in terms of classification performance and exhibits greater stability.Additionally,it is employed in the application of financial statement fraud identification.PMA and other five algorithms are utilized to financial statement fraud which concerned by the academic community,and the results indicate that the classification of PMA surpassed that of the other methods. 展开更多
关键词 principal model analysis partial least squares principal component analysis dimension reduction ensemble learning financial statement fraud detection
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