A dynamic consensus scheme based on a nonreciprocal fuzzy preference relation modeling

Using Fuzzy Analytic Network Process to assess the risks in enterprise resource planning system implementation

“…Adequate transformation functions are helpful in converting heterogeneous preferences of information (e.g., qualitative or quantitative, ordinal, and even based on various types of scales (e.g., ordinal, interval, and ratio scales)) [20]. Moreover, one of the possible adequate methods for multi-criteria analysis is to consider an index of comparability to measure the possibility of distinguishing a doubtful judgment [21].…”

“…In addition, in order to increase individual consistency of each expert in the experts' group consensus, the web based consensus support system can also be utilized [23]. However, it is important to understand the advantages, weaknesses, and restrictions of these methods to adequately use those tools for avoiding the negative effect in the discussion process, namely inducing an expert to construct a complete fuzzy preference model with satisfying consistency conditions, but does not reflect the experts' real preferences [21].…”

D-CFPR: D numbers extended consistent fuzzy preference relations

“…The second one is fuzzy preference relation [6,7,8,9]which is described by fuzzy pairwise comparison with an additive reciprocal, i.e. r ij + r ji = 1.…”

Uniqueness of consensus functions for time-delayed swarm systems with time-varying topologies

“…If the relative motions among agents are asymptotically stable, then consensus is achieved, which has been extensively investigated in the literature (e.g., Refs. [1][2][3][4][5][6][7][8][9][10][11]). The absolute motion, which is usually described by a consensus function, represents the agreement state of all agents when consensus is achieved.…”