A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a n...A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.展开更多
原子吸收光谱法测定 EMD 中 Co、Ni、Cu、Pb(见9900133) 2010 数理科学与基础理论Y98-61168-1 9901345判决(含5篇文章)=Decision[会,英]//1997 AnnualMeeting of the North American Fuzzy Information Pro-cessing Society.—1～26(HG...原子吸收光谱法测定 EMD 中 Co、Ni、Cu、Pb(见9900133) 2010 数理科学与基础理论Y98-61168-1 9901345判决(含5篇文章)=Decision[会,英]//1997 AnnualMeeting of the North American Fuzzy Information Pro-cessing Society.—1～26(HG)本部分汇编5篇论文。介绍了采用软计算技术的基于构成媒介物的判决支持系统,模糊认识映射对决策中数据提取和合成的应用,模糊逻辑模型,联机决策支持模糊系统。展开更多
基金Project(9140A18010210KG01) supported by the Departmental Pre-Research Fund of China
文摘A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.
文摘原子吸收光谱法测定 EMD 中 Co、Ni、Cu、Pb(见9900133) 2010 数理科学与基础理论Y98-61168-1 9901345判决(含5篇文章)=Decision[会,英]//1997 AnnualMeeting of the North American Fuzzy Information Pro-cessing Society.—1～26(HG)本部分汇编5篇论文。介绍了采用软计算技术的基于构成媒介物的判决支持系统,模糊认识映射对决策中数据提取和合成的应用,模糊逻辑模型,联机决策支持模糊系统。
