An Approximative Bayes-Optimal Kernel Classifier Based on Version Space Reduction

Author(s):  
Karen Braga Enes ◽  
Saulo Moraes Villela ◽  
Gisele Lobo Pappa ◽  
Raul Fonseca Neto
2013 ◽  
Vol 33 (8) ◽  
pp. 2337-2340
Author(s):  
Zhiying TAN ◽  
Ying CHEN ◽  
Yong FENG ◽  
Xiaobo SONG

Author(s):  
Louisa Issaoui ◽  
Nizar Aifaoui ◽  
Abdelmajid Benamara

To develop a simulation tool for automatic disassembly in computer aid design (CAD) environment two difficulties are found: the huge space of generated sequences and their feasibility especially in combinatory generation. This article deals with automatic sequence generation for selective disassembly of mechanical product. Starting from a CAD model a new appropriate connection tree of a target component is constructed. This tree aims at reducing space solution by eliminatory rules. The generation of sequence is based on reading of connection tree branches and eliminatory tests of feasibility. The feasibility is checked by updating the disassembly mobility of each sequence’s element. A case study is presented to prove the effectiveness of the proposed approach.


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