Case-Based Reasoning Rapid Design Approach for CNC Turret

Hai Qiao Wang; Bei Bei Sun; Xian Fa Shen

doi:10.4028/www.scientific.net/AMR.819.304

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Dynamic Fuzzy Reliability Analysis of Mechanical Components with Small Samples of Load
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An Improved Parallel Computation Method for Delaunay Triangulation
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Case-Based Reasoning Rapid Design Approach for CNC Turret
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 819Case-Based Reasoning Rapid Design Approach for CNC...

Case-Based Reasoning Rapid Design Approach for CNC Turret

Abstract:

In order to provide more efficient knowledge services in the CNC turret design process, a rapid design method of a case-based reasoning is proposed. Firstly, according to different types of demand in case retrieval, the similarity measurement models for crisp and fuzzy attribute type demands are constructed respectively. Secondly, in the weights assignment, this paper utilized the deviation information of similarity values to calculate objective weights, and then combined the objective weights and subjective weights to form synthesis weights. Finally, the similarity measurement and weights coefficient assignment methods were applied in a CNC turret design CBR system, and using the calculation function of MATLAB. It was demonstrated that this method could improve the accuracy of case retrieval.

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Periodical:

Advanced Materials Research (Volume 819)

Pages:

304-310

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.819.304

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Online since:

September 2013

Authors:

Hai Qiao Wang, Bei Bei Sun, Xian Fa Shen

Keywords:

Case Retrieval, Case-Based Reasoning (CBR), CNC Turret, Combination Weight, Similarity

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References

[1] B. Bouchon-Meunier, M. Ramdani, L. Valverde, Fuzzy logic, inductive and analogical reasoning, Proc. Fuzzy Logic in Artificial Intelligence Workshop, IJCAI'93, Springer, Berlin, 1994, 38–50.

DOI: 10.1007/3-540-58409-9_4

Google Scholar

[2] Mantaras R L, Plaza E. Case-based reasoning: an overview. AI Communications, 1997, 10: 21～29.

Google Scholar

[3] LI Jun-jun, QI Jin, HU Jie, et al. Similarity measurement method based on membership function and its application. Application Research of Computers, 2010, 27(3): 891-893.

Google Scholar

[4] Chen S M, Yeh M S, Hsiao P Y. A comparison of similarity measures of fuzzy values. Fuzzy Sets and Systems, 1995, 72(1): 79-89.

DOI: 10.1016/0165-0114(94)00284-e

Google Scholar

[5] Liao T W, Zhang Z M, Mount C R. Similarity measures for retrieval in case-based reasoning systems. Applied Artificial Intelligence. 1998, 12(4), 267-288.

DOI: 10.1080/088395198117730

Google Scholar

[6] SLONIM T Y, SCHNEIDER M. Schneider, Design issues in fuzzy case-based reasoning. Fuzzy Sets and Systems, 2001, 117(2): 251-267.

DOI: 10.1016/s0165-0114(99)00055-x

Google Scholar

[7] Li D. Fuzzy multiattribute decision-making models and methods with incomplete preference in formation. Fuzzy Sets and Systems, 1999, 106(2): 113-119.

DOI: 10.1016/s0165-0114(97)00272-8

Google Scholar

[8] FIN N IE G, S U N Z. Similarity and metrics in case-based reasoning. International Journal of Intelligent Systems, 2002, 17(3): 273-287.

Google Scholar

[9] JIANG Zhan-si, CHEN Li-ping, LUO Nian-meng. Similarity analysis in nearest- neighbor case retrieval. Computer Integrated Manufacturing Systems, 2007, 13(6): 1165-1168.

Google Scholar