Abstract
In this paper, we propose a novel Nonlinear Nearest-Neighbor (NNN) matching for similarity measure based on Nonlinear Compensatory (NC) choice model. Based on fuzzy logic inference, we propose NC choice model which granulates the psychological boundary between linear and nonlinear compensatory in the decision-making. Based on our NC mode, we develop a NNN matching function to consider both linear and nonlinear psychological compensatory effects. Theory analysis and experiment have demonstrated the success of NNN matching and NC model.
Original language | English |
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Title of host publication | 2005 IEEE International Conference on Granular Computing |
Pages | 342-345 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2005 |
Externally published | Yes |
Event | 2005 IEEE International Conference on Granular Computing - Beijing, China Duration: 25 Jul 2005 → 27 Jul 2005 |
Publication series
Name | 2005 IEEE International Conference on Granular Computing |
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Volume | 2005 |
Conference
Conference | 2005 IEEE International Conference on Granular Computing |
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Country/Territory | China |
City | Beijing |
Period | 25/07/05 → 27/07/05 |
Keywords
- Compensation model
- Decision making
- Fuzzy logic
- Nearest-neighbor matching
- Similarity measure
ASJC Scopus subject areas
- General Engineering
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Zeng, Y., Zhou, M., & Wang, R. (2005). Similarity measure based on nonlinear compensatory model and fuzzy logic inference. In 2005 IEEE International Conference on Granular Computing (pp. 342-345). Article 1547300 (2005 IEEE International Conference on Granular Computing; Vol. 2005). https://doi.org/10.1109/GRC.2005.1547300