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The probabilistic reliability assessment of large power systems is a very complicated and computation intensive task. So the standards of reliability be specified and used in all three sectors of the power system, i.e. generation, transmission and distribution. Since the forced outage rates (FOR) of generating plants is actually uncertain, security and reliability are two important challenges in modern...
Intermittent and uncertain nature of power output from weather-dependent renewable energy sources like solar is a major challenge in integrating them with traditional power grids that mostly consist of reliable power sources. We have created a framework for efficiently managing the weather-related uncertainty risk of solar generators and facilitating their integration into power grids while optimizing...
As non-functional properties of composite software services involve a good deal of uncertainty, we consider them as shared goals for an agent team. An architect is focused on choosing each service and its provider, while the consultant will suggest, when help is possible, an alternative so that the likelihood of success is maximized. We employ a structure called”Belief Recipe Tree”...
There are many differences between human faces, but still having common characteristics. The person's facial contour can be approximated as ellipses, and the relative position of eyebrows, eyes, nose, mouth and other organs is stable in the whole face. Such shapes are similar and can provide the basis for the realization of human face synthesis. Whether in technology or in the application, human face...
In this paper, we present a novel safety assessment approach to marine traffic based on cloud models, where various uncertainties in the complex system are well investigated and modeled by cloud theory. The proposed method focuses on the effective model of involved qualitative and quantitative elements in marine traffic safety systems. Optimal cloud models based on the relative cloud theory are used...
Cloud model is an effective tool in uncertain transforming between qualitative concepts and their quantitative expressions. In this paper, we introduce a new optimization method inspired from cloud model theory. The innovations of the algorithm are the estimation of good solution regions and new solution production according to the cloud model theory. First, the algorithm uses information obtained...
The complex network model is the research foundation of complex network, so it is important to evaluate and select model objectively .There is no effective evaluation way up to now. An evaluating method using cloud model is proposed to decrease randomness and fuzziness existing in conventional evaluation. The results of simulating experiments prove that such uncertainty is solved well.
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...
It is well known that no uniform prediction approaches were obtained regarding ground water level, though the neural network and some other so-called artificial intelligence methods consistently provide the smallest uncertainty and different medians warranting further research on their abilities. In the present paper, the lower reaches of Tarim River is taken as the study area, a grey correlation...
In the existing fuzzy clustering, membership is not easy to determine. In order to overcome the problem, we propose an efficient clustering algorithm based on random fuzziness model named RFKM, which can beset up mapping between randomness and fuzziness. This paper gives the operating steps of this method. Experiments prove that, compared with the FKM, the clustering method based on the random fuzziness...
In order to make the human facial expression recognition and analysis effectively, cloud model is used to mine the knowledge of human facial expression in this paper. Backward cloud generator without certainty degree treats the original input image as a cloud droplet image. The outputs are used to describe the three numerical characteristics-(Ex, En, He). How the three numerical characteristics of...
The accuracy and the real-time of the flood disaster evaluation are significant to the disaster rescue measures. However, itpsilas difficult to obtain accurate value of flood assessment factor because of the restrictions of objective conditions, which increases the difficulties of real-time evaluation. The traditional assessment methods have some limitations to some extent. In order to improve the...
In order to enhance the real time operability and efficiency of polling which are both crucial for network fault management, the current network polling schemes based on SNMP are discussed, and a novel dynamic polling scheme is put forward. By soft partition of variation amplitude concept and uncertainty reasoning based on cloud model, this scheme realizes the fine dynamic adjustment of polling intervals...
Various disasters have happened continually, and lead to massive loss to the people, loss assessment has become a critical role in alleviating disaster and defending disaster. But uncertainty is often found in disaster loss assessment, due to reasons such as imprecise measurement, outdated sources, or sampling errors. And a nationally consistent approach is absent in disaster loss assessment. In order...
Based on cloud transform and noclassical relation database theory, the paper define cloud relation model and discuss the significance of cloud relation model. At the same time, based on cloud relation model, the paper ameliorate the way of qualitative estimate about student scores, conquer the subjective factor and presents the objective way of qualitative estimate about students . The examples prove...
In this paper, we have made two improvements in region growing image segmentation. The First one is seeds select method, we use Harris corner detect theory to auto find growing seeds, through this method, we can improve the segmentation speed. The second one is growing rule. The homogeneity criterion usually depends on image formation properties that are not known to the user. We induced a new uncertainty...
For the aim of improving the simulation ability of neural network and being able to reflect the randomness, fuzziness and the relevance between the two existed in the real world, a new algorithm-cloud neural network (CNN) based on cloud transformation is presented in this paper. And the parameter adjustment method of CNN is given. The CNN based on cloud transformation could be used in the nonlinear...
Classical QFD can not analyze the uncertainty involved thoroughly. To deal with the problem, a new method based on cloud model was presented. The numerical character and certainty degree of the cloud drops were analyzed through the forward cloud generator, backward cloud generator and cloud expected curve. The importance of the customer demand and the engineering measures were described from both...
In order to resolve the problems of edge detection algorithm of images based on fuzzy seasoning or cellular automata, a new improved edge detection algorithm of images based on cloud model cellular automata is presented. This method uses direction information and edge order information as edge characteristic information, uses cloud model to inference these information, then gives accurate feedback...
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