Due to the correlation and diversity of robotic kinematic dexterity indexes, the principal component analysis （PCA） and kernel principal component analysis （KPCA） based on linear dimension reduction and nonlinear ...Due to the correlation and diversity of robotic kinematic dexterity indexes, the principal component analysis （PCA） and kernel principal component analysis （KPCA） based on linear dimension reduction and nonlinear dimension reduction principle could be respectively introduced into comprehensive kinematic dexterity performance evaluation of space 3R robot of different tasks. By comparing different dimension reduction effects, the KPCA method could deal more effectively with the nonlinear relationship among different single kinematic dexterity indexes, and its calculation result is more reasonable for containing more comprehensive information. KPCA＇ s calculation provides scientific basis for optimum order of robotic tasks, and furthermore a new optimization method for robotic task selection is proposed based on various performance indexes.展开更多
An objective evaluation scheme for automotive technical and comprehensive performance could provide critical and instructive insights for academic research,engineering practice,and commercial marketing of vehicles.In ...An objective evaluation scheme for automotive technical and comprehensive performance could provide critical and instructive insights for academic research,engineering practice,and commercial marketing of vehicles.In this paper,the technical performance index A=S∕T_(1)⋅T_(2)(m∕(s^(2)⋅L))and comprehensive performance index F=M⋅S∕T_(1)⋅T_(2),(kN⋅L^(−1),where M is the vehicle mass)are formulated by incorporating the vehicle 0–100 km⋅h^(−1) acceleration duration T_(1),100–0 km⋅h^(−1) braking duration T_(2),and fuel economy S(mileage per liter fuel at constant speed)to assess the vehicle’s longitudinal dynamic performance.A and F offer a clear physical implication of a vehicle’s acceleration capability and traction efficiency acquired per unit of fuel consumption,respectively.These indexes are used for wide case studies of popular market sedans and SUVs of joint ventures(JVs)and domestic brands in China over the last 17 years.The findings prove that this approach could be effectively and reliably utilized for the objective evaluation and analysis of the technical and comprehensive performance of automotive models.展开更多
The decision-making units(DMUs)in the modern service industries may produce desirable outputs and undesirable outputs.For the decision makers,some outputs may be more desired than others although all of them are desir...The decision-making units(DMUs)in the modern service industries may produce desirable outputs and undesirable outputs.For the decision makers,some outputs may be more desired than others although all of them are desirable.Considering these characteristics,this work combines the data envelopment analysis(DEA)and the multiple attributes decision-making(MADM)method,to make a reasonable and comprehensive performance evaluation for DMUs.Specifically,three DEA-based models are modified to obtain more reasonable efficiency scores for DMUs.The MADM method is used to determine the weights of outputs based on the preference ratings within the outputs.The efficiency scores are then multiplied by the aggregated outputs quantities to obtain the comprehensive performance scores for evaluation.The effectiveness of the proposed models is demonstrated by extensive numerical experiments.展开更多
基金Supported by the National Natural Science Foundation of China(No.51075005)the Beijing City Science and Technology Project(No.Z131100005313009)
文摘Due to the correlation and diversity of robotic kinematic dexterity indexes, the principal component analysis （PCA） and kernel principal component analysis （KPCA） based on linear dimension reduction and nonlinear dimension reduction principle could be respectively introduced into comprehensive kinematic dexterity performance evaluation of space 3R robot of different tasks. By comparing different dimension reduction effects, the KPCA method could deal more effectively with the nonlinear relationship among different single kinematic dexterity indexes, and its calculation result is more reasonable for containing more comprehensive information. KPCA＇ s calculation provides scientific basis for optimum order of robotic tasks, and furthermore a new optimization method for robotic task selection is proposed based on various performance indexes.
基金The National Natural Science Foundation of China(Project Name:Transmission mechanics and performance optimization of confined granular media self-adaptive differentialNo.51475475)工+1 种基金the Changsha Natural Science Foundation of China(Project Name:Structure principle and performance prediction of the intelligent tireNo.kq2014130)have provided funding for this research.
文摘An objective evaluation scheme for automotive technical and comprehensive performance could provide critical and instructive insights for academic research,engineering practice,and commercial marketing of vehicles.In this paper,the technical performance index A=S∕T_(1)⋅T_(2)(m∕(s^(2)⋅L))and comprehensive performance index F=M⋅S∕T_(1)⋅T_(2),(kN⋅L^(−1),where M is the vehicle mass)are formulated by incorporating the vehicle 0–100 km⋅h^(−1) acceleration duration T_(1),100–0 km⋅h^(−1) braking duration T_(2),and fuel economy S(mileage per liter fuel at constant speed)to assess the vehicle’s longitudinal dynamic performance.A and F offer a clear physical implication of a vehicle’s acceleration capability and traction efficiency acquired per unit of fuel consumption,respectively.These indexes are used for wide case studies of popular market sedans and SUVs of joint ventures(JVs)and domestic brands in China over the last 17 years.The findings prove that this approach could be effectively and reliably utilized for the objective evaluation and analysis of the technical and comprehensive performance of automotive models.
基金This work was supported by Science and Technology Foundation of Jiangxi Educational Committee[grant number GJJ190287].
文摘The decision-making units(DMUs)in the modern service industries may produce desirable outputs and undesirable outputs.For the decision makers,some outputs may be more desired than others although all of them are desirable.Considering these characteristics,this work combines the data envelopment analysis(DEA)and the multiple attributes decision-making(MADM)method,to make a reasonable and comprehensive performance evaluation for DMUs.Specifically,three DEA-based models are modified to obtain more reasonable efficiency scores for DMUs.The MADM method is used to determine the weights of outputs based on the preference ratings within the outputs.The efficiency scores are then multiplied by the aggregated outputs quantities to obtain the comprehensive performance scores for evaluation.The effectiveness of the proposed models is demonstrated by extensive numerical experiments.
