In this paper, we present a new belief c K neighbor (BCKN) classifier based on evidence theory for data classification when the available attribute information appears insufficient to correctly classify objects in specific classes. In BCKN, the query object is classified according to its K nearest neighbors in each class, and c K neighbors are involved in the BCKN approach (c being the number o...

Discretionary models of data envelopment analysis (DEA) assume that all inputs and outputs can be varied at the discretion of management or other users. In any realistic situation, however, there may exist ”exogenously fixed” or non-discretionary factors that are beyond the control of a DMU’s management, which also need to be considered. Also DEA requires that the data for all discretionary inp...

Trajectory queries, which retrieve nearby objects for every point of a given route, can be used to identify alerts of potential threats along a vessel route, or monitor the adjacent rescuers to a travel path. However, the locations of these objects (e.g., threats, succours) may not be precisely obtained due to hardware limitations of measuring devices, as well as complex natures of the surround...

This paper presents a complete pipeline for learning continuous motion control policies for a mobile robot when only a non-differentiable physics simulator of robot-terrain interactions is available. The multi-modal state estimation of the robot is also complex and difficult to simulate, so we simultaneously learn a generative model which refines simulator outputs. We propose a coarse-to-fine l...

In possibilistic clustering the objects are assigned to clusters according to the so-called membership degrees taking values in the unit interval. Differently from fuzzy clustering, it is not required that the sum of the membership degrees of an object in all the clusters is equal to one. This is very helpful in the presence of outliers, which are usually assigned to the clusters with membershi...

Emerging applications using miniature electronic devices (e.g., tracking mobile objects using sensors) generate very large amounts of highly dynamic data that poses very high overhead on databases both in terms of processing and communication costs. A promising approach to alleviate the resulting problems is to exploit the application’s tolerance to bounded error in data in order to reduce the ...

Sustainability, a new interdisciplinary paradigm, can be defined as standard in terms of economic, environmental and social awareness company. In many applications, theoretical sustainability models considering the importance three aspects equally differed from used practice. A sustainable supplier selection problem generally contains conflicting information imprecise decision makers’ knowledge...

The purpose of this paper is to evaluate the revenue efficiency in the fuzzy network data envelopment analysis‎. ‎Precision measurements in real-world data are not practically possible‎, ‎so assuming that data is crisp in solving problems is not a valid assumption‎. ‎One way to deal with imprecise data is fuzzy data‎. ‎In this paper‎, ‎linear ranking functions are used to transform the full fuz...

This paper studies connections between two alternatives to the standard probability calculus for representing and reasoning about uncertainty: imprecise comparative probability. The goal is identify complete logics uncertainty in a probabilistic language whose semantics given terms of Comparative operators are interpreted as quantifying over set measures. Modal dynamic added epistemic possibili...