Narrow Results

In this paper we define the following definition which is a natural combination of the definition for asymptotically equivalent and lacunary statistical convergence of fuzzy numbers. The two sequences of fuzzy numbers X = (X_k), and Y = (Y_k) of fuzzy numbers are said to be asymptotically lacunary statistical equivalent of multiple L provided that for every ∊ > 0

This paper establishes a novel environmental/economic load dispatch model in which the cost and emission functions are with uncertain coefficients. To solve the problem, this study first converts the model into a single objective optimization problem by using a novel weighting ideal point method. A hybrid genetic algorithm with quasi-simplex techniques is then developed to solve the corresponding single objective optimization problem. Fuzzy number ranking method is also applied to compare all fuzzy function values of different points for the single objective function. The test results have convinced the validity of the model and effectiveness of the algorithm used for achieving a solution for the economic dispatch problem.

Understanding a situation requires integrating many pieces of information which can be obtained by a group of data collectors from multiple data sources. Uncertainty is involved in situation assessment. How to integrate multi-source multi-member uncertain information to derive situation awareness is an important issue in supporting decision making for crisis problems. The study focuses on how uncertain situation information is presented, integrated and finally how situation awareness information is derived. A multi-sources team information integration approach is developed in the study to support a team's assessment for a situation in an uncertain environment. A numerical example is then shown for illustrating the proposed approach.

We analyze the behavior of the solutions for initial value problems associated to certain fuzzy differential equations, paying special attention to its advantages and disadvantages in relation with the modelization of real phenomena subject to uncertainty and comparing the results obtained with the corresponding results in the ordinary case.