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- W2326201835 abstract "Revealing the relations among parallel mechanism and robot comprehensive performance, topological structure and dimension is the basis to optimize mechanism. Due to the correlation and diversity of the single performance indexes, statistical principles of linear dimension reduction and nonlinear dimension reduction were introduced into comprehensive performance analysis and evaluation for typical parallel mechanisms and robots. Then the mechanism’s topological structure and dimension with the best comprehensive performance could be selected based on principal component analysis (PCA) and kernel principal component analysis (KPCA) respectively. Through comparing the results, KPCA could reveal the nonlinear relationship among different single performance indexes to provide more comprehensive performance evaluation information than PCA, and indicate the numerical calculation relations among comprehensive performance, topological structure and dimension validly." @default.
- W2326201835 created "2016-06-24" @default.
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- W2326201835 date "2015-08-02" @default.
- W2326201835 modified "2023-09-25" @default.
- W2326201835 title "Comprehensive Evaluation of Parallel Mechanism and Robot Performance Based on Principal Component Analysis and Kernel Principal Component Analysis" @default.
- W2326201835 doi "https://doi.org/10.1115/detc2015-47032" @default.
- W2326201835 hasPublicationYear "2015" @default.
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