Importance weighted averaging is a central information processing task in multicriteria decision problems of many kinds, such that selection, classification, object recognition, query answering, and information retrieval. These problems are characterized by a query, i.e., a set of importance weighted criteria, and a set of options queried. While each criterion determines a ranking of the option...

Interval-valued intuitionistic fuzzy sets (IVIFSs) are widely used to handle uncertainty and imprecision in decision making. However, in more complicated environment, it is difficult to express the uncertain information by an IVIFS with considering the decision-making preference. Hence, this paper proposes a group generalized interval-valued intuitionistic fuzzy soft set (G-GIVIFSS) which conta...

This paper addresses the problem of distributed Kalman filtering, with focus on limiting the required communication bandwidth. By distributed we refer to a scenario when all nodes in the network desire an estimate of the full state of the observed system and there is no centralized computation center. Communication only takes place between neighbors and only once each sample. To reduce bandwidt...

The determination of ordered weighted averaging (OWA) operator weights is a very important issue of applying the OWA operator for decision making. One of the first approaches, suggested by O’Hagan, determines a special class of OWA operators having maximal entropy of the OWA weights for a given level of orness; algorithmically it is based on the solution of a constrained optimization problem. I...

Ordered Weighted Averaging (OWA) operators have been successfully applied in many practical problems. We explain this empirical success by showing that these operators are indeed guaranteed to work (i.e., are universal), and that these operators are the best to use (in some reasonable sense). 1 Aggregation is needed In many areas of science and engineering, we have several estimates x 1 ; : : :...

Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between ...

NAA and lactate acquired with (a) cross-sectional RF excitations (63 averages) defining a square of 8x8 mm, i.e. the largest square fitting into the corpus callosum profile, and (b,c) with segmented 2DRF exciting the full corpus callosum profile shown in Fig. 1 with (b) standard averaging, i.e. 9 averages for each of the 7 segments, and (c) weighted averaging with 31 averages for the central k-...

Molodtsov initiated soft set theory that provided a general mathematicalframework for handling with uncertainties in which we encounter the data by affix parameterized factor during the information analysis as differentiated to fuzzy as well as bipolar fuzzy set theory.The main object of this paper is to lay a foundation for providing a new application of bipolar fuzzy soft tool in ...

This paper presents a method for fusing measurement samples from multiple sensors into a dependable robust estimation of a variable in the control environment. Each sensor measurement is represented by a measurement value and a confidence marker that corresponds to the respective variance of the measurement. We propose the Confidence-weighted Averaging (CWA) algorithm for fusing measurements wi...

We study different types of aggregation operators and the decision making process with minimization of regret. We analyze the original work developed by Savage and the recent work developed by Yager that generalizes the MMR method creating a parameterized family of minimal regret methods by using the ordered weighted averaging (OWA) operator. We suggest a new method that uses different types of...