Weighted averaging of classifier outputs is used in many MCSs, yet is still not well understood. Several empirical studies have investigated the effect that non-negativity and sum-one constraints have on the error rate of weighted averaging rules, but there is little theory available to understand the results. In this paper we study how constraints on the weights affect the location of the deci...

the present study is an attempt toward evaluating the performance of portfolios and asset selectionusing cross-efficiency evaluation. cross-efficiency evaluation is an effective way of ranking decisionmaking units (dmus) in data envelopment analysis (dea). conventional dea models assume nonnegativevalues for inputs and outputs. however, we know that unlike return and skewness, varianceis the on...

in this paper, an anomaly detection method in cluster-based mobile ad hoc networks with ad hoc on demand distance vector (aodv) routing protocol is proposed. in the method, the required features for describing the normal behavior of aodv are defined via step by step analysis of aodv and independent of any attack. in order to learn the normal behavior of aodv, a fuzzy averaging method is used fo...

in many computer vision applications, segmenting and extraction of moving objects in video sequences is an essential task. background subtraction, by which each input image is subtracted from the reference image, has often been used for this purpose. in this paper, we offer a novel background-subtraction technique for real-time dynamic background generation using color images that are taken fro...

The concepts of system load and capacity are pivotal in risk analysis. The complexity in risk analysis increases when the input parameters are either stochastic (aleatory uncertainty) and/or missing (epistemic uncertainty). The aleatory and epistemic uncertainties related to input parameters are handled through simulation-based parametric and non-parametric probabilistic techniques. The complex...

We develop the fuzzy generalized ordered weighted averaging distance (FGOWAD) operator. It is a new aggregation operator that uses the main characteristics of the generalized OWA (GOWA), the ordered weighted averaging distance (OWAD) and uncertain information represented as fuzzy numbers. This operator includes a wide range of distance measures and aggregation operators such as the fuzzy maximu...

We analyze different types of aggregation operators. We focus on the generalized OWA (GOWA) operator and the Quasi-OWA operator which generalize a wide range of aggregation operators. We also analyze a recent approach that unifies the weighted average and the OWA operator in the same formulation called ordered weighted averaging – weighted averaging (OWAWA) operator. We introduce the fuzzy gene...