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In this paper, the parameter λ would be introduced to forecast grey number sequence that was based on the paper with known whitenization weight function published by Bo Zeng. We use variable weight instead of no-preference generation. So the most appropriate parameter to build the DGM (1,1) would be chose by GA. Then an improved grey prediction model for forecasting interval grey number is proposed...
Although the Grey Discrete Model and its improved models have been successfully employed in some fields and have promising results, the prediction results may be inaccurate sometime. We bring a grey discrete parameters model by introducing quadratic time-varying terms, which is called as quadratic time-varying parameters discrete grey model (referred to as QDGM (1, 1)). The paper investigates the...
Nowadays the application of visualization technology is very wide while big data technology is rapidly developing. Data visualization can show the results of data analysis in an intuitive way, which has a very important practical significance. This paper studies a variety of media data visualization methods along with the development of media information. First of all, we introduce main basic contents...
To solve the problem that the growth of prediction of discrete grey model is constant, the paper establishes a new grey discrete parameters prediction model by instructing quadratic time-varying parameters, which is called as quadratic time-varying discrete grey model(referred to as QDGM(1,1)). We discuss the affine properties of QDGM model. The paper employed a majorization principle to optimizing...
To solve the problem that the growth of prediction of discrete grey model is constant, the paper establishes a new grey discrete parameters prediction model by instructing quadratic time-varying parameters, which is called as quadratic time-varying discrete grey model(referred to as QDGM(1,1)). We discuss the affine properties of QDGM model. The paper employed a majorization principle to optimizing...
Radial basis function (RBF) network is one of the significant neural networks. It has been used successfully in various fields. But in RBF network approximation algorithm, the initial value of the network weights, Gauss function center vector and broad-based vector is not easy to determine, and when these parameter choice is undeserved, RBF network approximation precision will decline and even the...
A new classification algorithm based on matrix degree of grey incidences for handwritten number recognition and natural image clustering is proposed in this paper. In order to recognize a handwritten numeral or to classify the type of images, we should extract the features that can describe the differences among all information efficiently ant first. Then the features matrix is build for the samples...
Clickers a wireless-keypad used in class-polling systems that enable students to answer questions during lectures. Such systems provide an interactive teaching environment with real time feedback for students and teachers on the progress of teaching and learning. Clicker use is becoming more widespread amongst faculty as a means of engaging students in US. However, there is few papers report its effectiveness...
The edges of an image are important information. Edge detection is the base of feature extraction, image analysis and comprehension. The quality of edge detection determines the performance of subsequent processing. The edge of an image stands for the discontinued information. We propos a new algorithm of image edge detection based on grey system theory in this paper. we calculate the relative degree...
Natural image classification is an important task. SIFT descriptors and bag-of-visterms (BOV) method have achieved very good results based on local image representation. Many studies use the support vector machine to classify and identify the image category after finished representation of the image. However, due to support vector machine (SVM) its own characteristics, it shows inflexible and less...
Data mining can be greatly beneficial in many areas, such as telecommunication, broadcasting, television and so on. In order to make sense of alarming data in satellite TV broadcasting monitoring system, an application approach of data mining in satellite TV broadcasting monitoring is discussed in this paper. By introducing an improved algorithm for discovering frequent episodes into satellite TV...
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