This paper investigates the minimum spanning tree problem in the framework of uncertainty theory, where the edge weights are assumed as uncertain variables. The concept of ideal uncertain minimum spanning tree is initiated by extending the definition of the uncertain α-minimum spanning tree. On the basis of this new concept, we propose the definition of uncertain distribution-minimum spanning t...

Uncertainty in data is caused by various reasons including data itself, data mapping, and data policy. For data itself, data are uncertain because of various reasons. For example, data from a sensor network, Internet of Things or Radio Frequency Identification is often inaccurate and uncertain because of devices or environmental factors. For data mapping, integrated data from various heterogono...

A computation-oriented representation of uncertain kinetic systems is introduced and analysed in this paper. It is assumed that the monomial coefficients of the ODEs belong to a polytopic set, which defines a set of dynamical systems for an uncertain model. An optimization-based computation model is proposed for the structural analysis of uncertain models. It is shown that the so-called dense r...

Large-scale, highly-interconnected networks pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs ar...

1.1 Review of MDP model formulation The major theme of my research since last autumn has been in the development of the MDP formulation of PRM route graphs with uncertain edges. In the last progress report (Kneebone 2007, section 2) details were given on how a PRM graph with uncertain edges (where the agent does not know a priori if they are traversable) could be represented as either an MDP or...

Uncertainty theory is a mathematical methodology for dealing withnon-determinate phenomena in nature. As we all know, uncertainprocess and uncertain integral are important contents of uncertaintytheory, so it is necessary to have deep research. This paperpresents the definition and discusses some properties of strongcomonotonic uncertain process. Besides, some useful formulas ofuncertain integr...

This paper presents a method for Entity Disambiguation in Information Extraction from different sources in the web. Once entities and relations between them are extracted, it is needed to determine which ones are referring to the same real-world entity. We model the problem as a graph partitioning problem in order to combine the available information more accurately than a pairwise classifier. ...

The inverse shortest path problem is to minimize the modification on the edge weights such that a predetermined path becomes the shortest one from the origin to the destination with respect to the new edge weights. In this paper, the inverse shortest path problem is considered on a graph with uncertain edge weights. It is shown that the model of the uncertain inverse shortest path problem can b...

In this paper we present a novel approach to searching a graph with probabilistic edge costs. By incorporating uncertainty information into the graph search we perform risk-aware planning. We present the results through a simple search domain, and report the improved results compared to traditional single heuristic search techniques (A*, D*, and greedy).