On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Communications of the ACM - Supporting community and building social capital
Editorial: semantics, resource and grid
Future Generation Computer Systems - Special issue: Semantic grid and knowledge grid: the next-generation web
Semantic profile-based document logistics for cooperative research
Future Generation Computer Systems - Special issue: Semantic grid and knowledge grid: the next-generation web
A fuzzy collaborative assessment approach for knowledge grid
Future Generation Computer Systems - Special issue: Semantic grid and knowledge grid: the next-generation web
Fuzzy reliability estimation using Bayesian approach
Computers and Industrial Engineering
A framework for multi-source data fusion
Information Sciences: an International Journal - Special issue: Soft computing data mining
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
The Knowledge Grid
Personalized mining of web documents using link structures and fuzzy concept networks
Applied Soft Computing
Machine learning of user profiles: representational issues
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Modeling of reliability with possibility theory
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Self-organizing fuzzy aggregation models to rank the objects with multiple attributes
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Expert Systems with Applications: An International Journal
Taking cooperative decisions in group-based wireless sensor networks
CDVE'11 Proceedings of the 8th international conference on Cooperative design, visualization, and engineering
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A knowledge grid is an intelligent interconnection environment, built on top of a computational grid, to facilitate the creation of virtual organizations. An important feature of a virtual environment is its support for collaborative decision-making. A major difficulty with current approaches is that they cannot easily handle environments where decision makers are added or removed dynamically. In this article, a new approach to alter the number of decision makers dynamically is suggested. The amount of decision accuracy made by each decision maker, for a given subject, is determined subjectively considering the other decision makers' opinions. The effect of decisions made by each decision maker varies gradually considering its past decisions. Assuming each decision maker provides a fuzzy answer set in response to each decision problem, an operator for fusing of the decision makers' decision sets is suggested. The aim of the fusion is improvement of the decision quality. The fusing operator provides a fuzzy answer set that is a function of the accuracy possibility of each decision maker and its fuzzy answer set.