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The algorithm of fractal dimension and co-occurrence matrices is proposed and is applied to material Vickers hardness image segmentation. Based on the characteristics of the indentation images, this article uses texture features to extract the indentation silhouette from the point view of texture segmentation. We adopt fractal dimension and co-occurrence matrix algorithm to describe the texture characteristics...
The evolutionary model of ERP cluster system is studied to show the idea of evolutionary analysis of large-scale ERP cluster system for big corporation. After the analysis of ERP cluster system, the state model is built; the evaluation problem of ERP system is studied; then, an evolutionary model of ERP cluster is built by a process model and an evolutionary algorithm framework. Finally, by simulation...
By analyzing the evaluation method and working characteristics of the design courses in universities, a fuzzy comprehensive evaluation method is advanced, which based on fuzzy clustering analysis. According to the fuzzy membership degree theory, the author translated the qualitative evaluation into quantitative evaluation. Through this, the problem that the qualitative and quantitative evaluation...
Cluster analysis based on Delaunay diagrams has been widely researched in all kinds of fields. In this article, a new method is proposed to treat with datasets of non-spherical and multi-density clustering. As well as, the problem of noise data is solved by defining the conceptions of In_Points and Out_Points in this method. The above points was illustrated by two simulation experiments.
Aiming at the problem of higher false positive and missing report rate in network intrusion detection, an intrusion detection method based on clustering algorithm is proposed in this paper. This method applies Fuzzy C-means clustering Algorithm to the detection of network intrusion. Through the building of intrusion detection model, carries out fuzzy partition and the clustering of data, and this...
Hough transform (HT) is a well-established method for curve detection and recognition due to its robustness and processing capability. Being the core principle, voting principle needs to find the max voting rate, which makes it impossible to detect many targets from single image synchronously. In this paper, an improved Hough transform algorithm which combines with clustering is presented. The algorithm...
A new clustering algorithm is proposed based on particle swarm optimization (PSO). The main idea of the new algorithm is to solve clustering problem using the fast search ability of the particle swarm optimization, each particle is composed of a cluster center vector, and represents a possible solution of the clustering problem. To escape from local optimum, a new idea is proposed, that is the neighborhood...
Clustering data stream is a challenging work due to the limited memories and a single pass. In this paper, a new grid based algorithm for clustering high-dimensional data stream (called GHStream) is proposed, which adopts a two-phase clustering formwork. In the online component, a High-dimensional Dense Grid Tree (abbreviated HDG-Tree) is presented to summarize streaming data. As data streams evolve,...
In order to solve the problem of easily fall into local optimal solutions, lower convergent precision, slower convergence rates and the poor population diversity, an improved PSO algorithm was proposed in this paper. The diversity was improved by the application of fuzzy clustering method. The sub-populations were classified automatically based on the feature of the population, and the information...
Self-organizing feature map is able to represent the topological structure of the input data in a lower dimensional space, but however, at the cost of a huge amount of iterations. This paper presents an efficient approach to refining input data before it has been presented to forming the feature map. By using a data pre-processing inspired by the genetic selection, the improved self-organizing map...
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