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Comparison between composite index solution surfaces with fuzzy composite index decision surfaces

Author
Cárdenas, R.; Nebot, A.; Mugica, F.
Type of activity
Presentation of work at congresses
Name of edition
2019 IEEE International Conference on Fuzzy Systems
Date of publication
2019
Presentation's date
2019-06-24
Book of congress proceedings
2019 IEEE International Conference on Fuzzy Systems: New Orleans, Louisiana, USA, June 23-26, 2019
First page
1
Last page
6
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
10.1109/FUZZ-IEEE.2019.8858871
Project funding
Computational Intelligence for Knowledge Discovery from G Protein-Coupled Receptors
Repository
http://hdl.handle.net/2117/176660 Open in new window
URL
https://ieeexplore.ieee.org/document/8858871 Open in new window
Abstract
Composite indices are used in many of the traditional approaches to measure risk to natural hazards. However, such indices are often built assuming linear interdependencies between the aggregated components, comprising in this way any realistic representation of the intricate and unseen processes that are behind each component along with their mutual influences when it comes to encapsulate a complex reality in a single construct. In this paper we used a Fuzzy Inference Systems type Mamdami to ag...
Citation
Cárdenas, R.; Nebot, A.; Múgica, F. Comparison between composite index solution surfaces with fuzzy composite index decision surfaces. A: IEEE International Conference on Fuzzy Systems. "2019 IEEE International Conference on Fuzzy Systems: New Orleans, Louisiana, USA, June 23-26, 2019". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 1-6.
Keywords
Composite indices, Fuzzy sets, Inference system, Risk management, Seismic hazard, Seismic vulnerability
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
SOCO - Soft Computing

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