Titlebook: ;

crockery

連系

,Consensus Modeling under Fuzziness – A Dynamic Approach with Random Iterative Steps,ions. Repeating the process multiple times leads to many singular (different) consensus process paths. The imprecision of the overall result, the resulting different consensus outcomes, is captured by introducing a simple process to form an overall distribution of the outcomes. The model uses a rand

愛社交

施舍

menopause

大包裹

Spatial-Taxon Information Granules as Used in Iterative Fuzzy-Decision-Making for Image Segmentatio In image processing, an image can be similarly organized by means of a standardized natural-scene-taxonomy, borrowed from the study of human visual taxometrics. Such a method yields a three-dimensional representation comprised of a hierarchy of nested spatial-taxons. Spatial-taxons are information

闡明

Stricture

Fuzzy Optimization in Decision Making of Air Quality Management, the mathematical representation to find the equilibrium point. How to obtain and express these optimal data depends on the fuzzy optimization techniques. The methodology and algorithm of fuzzy decision making process by interactive multi-objective approach and iterative optimization method are desc

CLAY

Congestion

Hua Song,Jack Jarvis,Wenping Liom term that is drawn from a uniform distribution to introduce randomness in the consensus reaching process, and allows for the modeling of real-world behavioral aspects of negotiations, such as negotiator “power” issues by tuning the “amount” of randomness used for each negotiation participant. The new model is numerically illustrated.