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Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments
October 2011 (vol. 23 no. 10)
pp. 1455-1468
ASCII Text
x 
 
Shang-Ming Zhou, Francisco Chiclana, Robert I. John, Jonathan M. Garibaldi, "Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 10, pp. 1455-1468, October, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TKDE.2010.191,
author = {Shang-Ming Zhou and Francisco Chiclana and Robert I. John and Jonathan M. Garibaldi},
title = {Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {23},
number = {10},
issn = {1041-4347},
year = {2011},
pages = {1455-1468},
doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2010.191},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments
IS - 10
SN - 1041-4347
SP1455
EP1468
EPD - 1455-1468
A1 - Shang-Ming Zhou,
A1 - Francisco Chiclana,
A1 - Robert I. John,
A1 - Jonathan M. Garibaldi,
PY - 2011
KW - OWA operators
KW - aggregation
KW - fuzzy sets
KW - type-1 OWA operators
KW - Alpha-cuts
KW - Alpha level
KW - uncertain information
KW - soft decision making
KW - breast cancer treatments.
VL - 23
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 
Shang-Ming Zhou, Swansea University, Swansea
Francisco Chiclana, De Montfort University, Leicester
Robert I. John, De Montfort University, Leicester
Jonathan M. Garibaldi, University of Nottingham, Nottingham
Type-1 Ordered Weighted Averaging (OWA) operator provides us with a new technique for directly aggregating uncertain information with uncertain weights via OWA mechanism in soft decision making and data mining, in which uncertain objects are modeled by fuzzy sets. The Direct Approach to performing type-1 OWA operation involves high computational overhead. In this paper, we define a type-1 OWA operator based on the \alpha-cuts of fuzzy sets. Then, we prove a Representation Theorem of type-1 OWA operators, by which type-1 OWA operators can be decomposed into a series of \alpha-level type-1 OWA operators. Furthermore, we suggest a fast approach, called Alpha-Level Approach, to implementing the type-1 OWA operator. A practical application of type-1 OWA operators to breast cancer treatments is addressed. Experimental results and theoretical analyses show that: 1) the Alpha-Level Approach with linear order complexity can achieve much higher computing efficiency in performing type-1 OWA operation than the existing Direct Approach, 2) the type-1 OWA operators exhibit different aggregation behaviors from the existing fuzzy weighted averaging (FWA) operators, and 3) the type-1 OWA operators demonstrate the ability to efficiently aggregate uncertain information with uncertain weights in solving real-world soft decision-making problems.

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Index Terms:
OWA operators, aggregation, fuzzy sets, type-1 OWA operators, Alpha-cuts, Alpha level, uncertain information, soft decision making, breast cancer treatments.
Citation:
Shang-Ming Zhou, Francisco Chiclana, Robert I. John, Jonathan M. Garibaldi, "Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 10, pp. 1455-1468, Oct. 2011, doi:10.1109/TKDE.2010.191
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