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In multiple attribute decision analysis (MADA) problems, one often needs to deal with assessment information with uncertainty. The evidential reasoning approach is one of the most effective methods to deal with such MADA problems. As a kernel of the evidential reasoning approach, an original evidential reasoning (ER) algorithm was firstly proposed by Yang et al, and later they modified the ER algorithm...
The expert selection is an important decision problem in the research and development process of complex product systems (CoPS) projects and suitable experts will facilitate the successful task achievement. Existing methods for the expert selection are mostly based on the individual performance, whereas the task characteristics of CoPS projects and the knowledge correlationship between candidates...
For the problem of multi-sensor data fusion on the decision level, an evidence fusion method based on the modified support degree distribution method is proposed. First, starting from the viewpoint of classical evidence fusion formula, the reason why confidence paradox is generated is analyzed and the general rule of generating confidence paradox is achieved; second, with analysis of support degree...
Pervasive mobile games utilise contextual data about players and their environment to explore new means of interaction and enhance the gaming experience. However, the inherent imperfection of contextual data acquisition poses a challenge for developers and designers of pervasive games. In these games, both sensor inaccuracies and uncertainties need to be identified and properly handled to prevent...
A Probabilistic Conditional Preference network (PCP-net) provides a compact representation of preferences characterized with uncertainty. We propose to enrich the expressive power of the PCP-net by adding constraints between some of the variables. We call this new model, the Constrained PCP-net (CPCP-net). We study the key preference reasoning task with the proposed CPCP-net which consists in finding...
Influence diagram is an effective mathematical representation of decision situations, in the traditional influence diagrams, the dependencies between nodes of uncertainty and the value table of value nodes are constructed through probability models, they get widely applied in intelligent decision analysis. But information system (IS) in our lives are very complicated, such as grey information data,...
[Context/Motivation]: The strategy of an organization defines its long-term goals and develop plans to achieve these goals. Strategic planning is the activity of deciding how to allocate resources within the organization to satisfy its strategy. Strategic planning precedes more detailed requirements engineering activities that clarify the requirements for the software systems concerned by the strategic...
When designing changes to a software product line (SPL), developers are faced with uncertainty about deciding among multiple possible SPL designs. Since each SPL design encodes a set of related products, dealing with multiple designs means that developers must reason about sets of sets of products. The additional degree of multiplicity is not well described by existing product line abstractions. In...
The need to mitigate the effects volatility, uncertainty, complexity, ambiguity characterises the modern project environment. At the project team level, this need requires coordination by competent team members highly proficient in efficient decision-making. Project team members and teams must demonstrate a capacity in adaptability to recognise patterns in a chaotic project situation, modify problem...
The Dempster-Shafer evidence combination method will appear inconsistent conclusions for the conflict evidence. One new universal evidence combination method was proposed. According to the concept of the Pearson correlation coefficient. Evidence distances which represent the conflict degree were calculated, and then the weight coefficient were further converted. The evidences probability were redistributed...
Safety assessment of complex systems such as micro energy grids has lately become an interesting open research field. In this article, fault diagnosis for a micro energy grid in the occurrence of incomplete data and expert knowledge is discussed. A hybrid technique of Bayesian belief networks and adaptive-network-based fuzzy inference system is proposed for fault diagnosis and safety assessment of...
Testability growth is a process that aims to improve the testability level of the equipment via identifying and removing the testability design defects (TDDs). The establishment of the existing testability growth model (TGM) needs to consider a variety of factors, it's difficult to describe it accurately. To solve this problem, a TGM based on evidential reasoning (ER) method with nonlinear optimization...
The question addressed in this paper is “what” is to be evaluated by the Uncertainty Representation and Reasoning Evaluation Framework (URREF) ontology. We thus identify the elements composing uncertainty representation and reasoning approaches, which constitute various subjects being assessed. We distinguish between primary evaluation subjects (Uncertainty Representation and Reasoning components...
Ensemble clustering consists in combining multiple clustering solutions into a single one, called the consensus, which can produce a more accurate and robust clustering of the data. In this paper, we attempt to implement ensemble clustering using Dempster-Shafer evidence theory. Individual clustering solutions are obtained using evidence theory and a novel diversity measure is proposed using the distance...
Edge detection is one of the most important tasks in image processing and pattern recognition. Edge detector with multiple color channels can provide more edge information. However, the uncertainty occurring with the edge detection in each single channel and the discordance existing in the fusion of multiple channels edge detectors make the detection difficult. In this paper, we propose a new edge...
In this paper, an approach has been proposed for compositional adaptation of the cases based on the semantic relations between the components in each case. Within this scope, a problem situation comprising some components with semantic nature operates over the stored cases to make a reasonable use of the related components and the corresponding similarities with its own components. In this regard...
Dempster-Shafer evidence theory (DST) is a theoretical framework for uncertainty modeling and reasoning. The determination of basic belief assignment (BBA) is crucial in DST, however, there is no general theoretical method for BBA determination. In this paper, a method of generating BBA using fuzzy numbers is proposed. First, the training data are modeled as fuzzy numbers. Then, the dissimilarities...
Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information. But some conditions or requirements, such as exclusiveness hypothesis and completeness constraint, limit the development and application of that theory to a large extend. To overcome the shortcomings and enhance its capability of representing...
The advent of widely available photo collections covering broad geographic areas has spurred significant advances in large-scale urban scene modeling. While much emphasis has been placed on reconstruction and visualization, the utility of such models extends well beyond. Specifically, these models should support a wide variety of reasoning tasks (or queries), and thus enable advanced scene study....
The International Society of Information Fusion (ISIF) Evaluation Techniques for Uncertainty Representation Working Group (ETURWG) investigates the quantification and evaluation of all types of uncertainty regarding the inputs, reasoning and outputs of the information fusion process. The ETURWG is developing an Uncertainty Representation and Reasoning Framework (URREF) ontology for this purpose. This...
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