Title :
Tree-Structured Multi-Layer Fuzzy Cognitive Maps for Modelling Large Scale, Complex Problems
Author :
Mateou, N.H. ; Andreou, A.S.
Author_Institution :
Dept. of Comput. Sci., Univ. of Cyprus, Nicosia
Abstract :
This paper proposes tree structured multi-layer fuzzy cognitive maps for modelling large-scale and complex real world problems and supporting the decision making process. Large-scale problems are characterized by a large number of parameters, concepts, variables, nonlinearities and uncertainties that make their analysis and modelling a very difficult task. The objective of the proposed methodology is to give an alternative approach for dealing with the aforementioned difficulties, offering a new computational algorithm designed so as to support the creation of layers of parameters and variables describing the system under study, as well as the simulation of its evolution dynamics
Keywords :
computational complexity; decision making; fuzzy neural nets; fuzzy set theory; tree data structures; computational algorithm; decision making process; large-scale problem; real world problem; tree-structured multi-layer fuzzy cognitive maps; Algorithm design and analysis; Computational intelligence; Computational modeling; Computer science; Decision making; Fuzzy cognitive maps; Information systems; Intelligent systems; Large-scale systems; Uncertainty;
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
DOI :
10.1109/CIMCA.2005.1631457