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There are many uncertainties during logistics operation. It's the best way for coping with influences of uncertainties and increasing the efficiency and effect of logistics system to maintain proper flexibility. Evaluation on flexibility of logistics system is precondition and key for building and holding the flexibility of logistics system. In this paper, the flexible indexes of three stages including...
This paper proposes a soft computing approach to manage uncertainty and rule discovery by reasoning over inconsistent, incomplete and fragmentary information using dominance-based rough set theories. A methodological and computational basis is illustrated in a sensor network application scenario of a forest fire detection system.
Top-k processing in Uncertain Databases is semantically and computationally different from traditional top-k processing. The interplay between score and uncertainty information makes traditional top-k processing techniques inapplicable to uncertain databases. The existing approaches are all based on the assumption that the underlying data are exact (or certain). We construct a framework that encapsulates...
This paper presents the optimal design of an overlapped ultrasonic sensor ring for minimal positional uncertainty in obstacle detection. It is assumed that a set of low directivity ultrasonic sensors of the same type are arranged in a circular array at a regular spacing with their beams overlapped. First, the optimal design index for an overlapped ultrasonic sensor ring is defined as the area ratio...
Considering the problem that it is difficult to quantify the uncertainty problem about risk assessment of power network planning projects, G1 method and F-DS evidential theory are adopted to establish the assessment model of power network planning projects. Put forward the weighted formula of evidence combination with the use of G1 method. Apply information fusion technology of F-DS evidential theory...
Organizations have to be competitive in their market throughout the globalization process. Thus, they need to achieve customer demands in strategic ways focusing on customer satisfaction. At this point, decision makers encounter with uncertainties based on reducing the deviation in the production/service processes. The uncertainty problem of supplier selection for a Turkish Machinery Industry Corporation...
Credibility evaluation process is a process in which the credibility values of each index are integrated, and total credibility value of simulation system is evaluated based on its evaluation indexes. Because of different methods used in VV & A process, VV & A results may be quantitative or qualitative. In this paper, a credibility evaluation method based on Cloud Model is brought forward,...
In view of the problems existing in the prediction methods of coal and gas outburst, a method for prediction of coal and gas outburst based on multi-agent information fusion is proposed. In the method, considering the measured data relevant to many influence factors, a multi-agent information fusion model for rapid, dynamic and accurate prediction of coal and gas outburst is given, Dempster-Shafer...
Capabilities that prognostics and system health management (PHM) system detect fault, isolate fault and forecast fault directly determine the effectiveness of the maintenance work. With the development of sensor technology and signal processing methods, in order to precisely detect and identify faults, fault diagnosis is a typical multi-sensor fusion problem. New challenges have arisen with regard...
Selecting the most suitable learning object in SCORM-compliant learning object recommendation system is a complex decision process. We exploit the techniques of collaborative concept map design, ontology explaining, an evidence reasoning that may be use to deal with uncertain decision making, an evaluation analysis model and the evidence combination rule of the Dempster-Shafer theory for supporting...
In the environment with objects moving randomly, the positions of moving objects can be modeled as a range of possible values, associated with a probability density function. Data mining of such positions of uncertain moving objects attracts more and more research interest recently. The definitions of probabilistic core object and probabilistic density-reachability are presented and a density-based...
This paper addresses the decision trees induction with uncertain data. In other words, it presents a novel method, called uncertain decision trees (UDT) to handle the uncertainty during the process of inducing decision trees. Here, uncertainty is depicted via cloud model theory, a quantitative-qualitative transforming model with uncertainty, which can well integrate the fuzziness and randomness of...
This paper discusses the use of a possibilistic framework for system monitoring tasks where a system model jointly with measurements is given as a set of algebraic equations. Uncertainty is handled via the introduction of slack variables and an optimization-based (linear or quadratic programming) approach is proposed to compute the possibility distributions of the internal variables to be monitored...
The uncertainty management problem for moving objects databases has been well studied recently, with many models and algorithms proposed. However, very limited work has dealt with the index of uncertain trajectories for a running moving objects database. In this paper, we propose an index framework, the UTR- Tree, for indexing the full uncertain trajectories of network constrained moving objects....
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