Learn More
Intuitionistic fuzzy information aggregation plays an important part in Atanassov’s intuitionistic fuzzy set theory, which has emerged to be a new research direction receiving more and more attention in recent years. In this paper, we first introduce some operations on intuitionistic fuzzy sets, such as Einstein sum, Einstein product, Einstein(More)
7 This article proposes an approach to multiattribute decision making with incomplete 8 attribute weight information where individual assessments are provided as interval-valued 9 intuitionistic fuzzy numbers (IVIFNs). By employing a series of optimization models, the 10 proposed approach derives a linear program for determining attribute weights. The 11(More)
Aggregation of fuzzy information is a new branch of Atanassov's intuitionistic fuzzy set (AIFS) theory, which has attracted significant interest from researchers in recent years. In this paper, we treat the intuitionistic fuzzy aggregation operators with the help of Einstein operations. We first introduce some new operations of AIFSs, such as Einstein sum,(More)
Abstract. Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average) models for seasonal streamflow series). However, with McLeod-Li test and Engle’s Lagrange Multiplier(More)
The notion of interval-valued intuitionistic fuzzy set (IVIFS) is a generalization of that of Atanassov's intuitionistic fuzzy set (AIFS). The fundamental characteristic of IVIFS is that the values of its membership function and non-membership function are intervals rather than exact numbers. In this article, we develop some interval-valued intuitionistic(More)
In order to increase the elevators running efficiency and quality of service, the optimizing control strategy of elevators is studied. In this paper a new hybrid control method which optimizes passenger service in an elevator group is described. It is capable of optimizing the neural-controller based on Particle Swarm Optimization (PSO) of an elevator group(More)
In decision making problems there may be cases in which decision makers do not have an in-depth knowledge of the problem to be solved. In such cases, more and more research has been conducted within a fuzzy or intuitionistic fuzzy framework. In this paper, we investigate the group decision making problems in which all the evaluation information provided by(More)