Segmentation algorithm for complicated infrared image based on superparamagnetic clustering
On the other hand, this strategy imposes that layered clustering methods have high nicety and provide suitable initial clustering centers.
The law of fuzzy clustering confirms the best threshold and determines the dynamic clustering figure by data's standardization, shift and range transform.
A new grid clustering method based on the random sampling is proposed in the dissertation.
The data are reduced in both horizontal and vertical directions by using hierarchical clustering and rough set methods.
After the clustering characteristics of image wavelet coefficients' significance distribution in each sub-band was analyzed, run-length coding (RLC) was introduced into SPIHT's output stage.
Using maximum likelihood criterion in clustering algorithms, the clusters have spherical or ellipsoidal receptive fields and match the distributes of patterns better.
An efficient segmentation method based upon fuzzy c-means (FCM) clustering principles is proposed. The approach utilizes a pyramid data structure for the hierarchical ana - lysis of color images.
How is GlassFish server's clustering different from traditional clustering implementation?
Application of gray association degree clustering algorithm in image retrieval
A simple example of clustering was given in the introduction.
We propose a data mining model based on clustering and rough set.
Attenuation reflectance Fourier transformation infrared spectrometry(ATR FTIRs) combined with clustering analysis was used to identify genus Zanthoxlum .
This study investigates the effect of word clustering in the environment of Second language vocabulary learning software (Sevols).
This paper discusses how to deal with the clustering problem with categorical attributes by means of the theory of similarity coefficients and the theory of entropy, and emphatically studies the equivalence of the two similarity measures in resolving the clustering problem for intrusion detection.
The experiment results show that the cluster initial centroids selected by the new method is more closed to the desired cluster centers, and the better clustering accuracy can be achieved.
Can you devise a clustering metric or a clustering algorithm that is appropriate in such cases?
MQ queue managers do not restart automatically after crashing, and in general, neither MQ clustering nor hardware-based clustering like HACMP provide this behavior by default.
The strong household clustering of MTI suggests that family sources of exposure are important.
Next, a fast fuzzy conceptual clustering algorithm is proposed to cluster the fuzzy concept lattice into conceptual clusters.
With the characteristic of 3d laser scanning on road and the distribution analysis of points clouds normal vectors, the filtering algorithm based on fuzzy clustering of normal vectors is proposed.
A clustering analysis of reticulocyte in thalassemia
Moreover, Siwpas Enterprise Edition includes clustering and failover of stateful EJB and CDI beans with Tomcat native clustering.
In the near future at clustering periodic time series data study up have more and more extensive trend.
Allowing too much free space, however, could cause extra pages to be read for queries and largely defeat the purpose of using a clustering index.
She made the sombre crowd cheerful by her erratic and glistening ray, even as a bird of bright plumage illuminates a whole tree of dusky foliage by darting to and fro, half seen and half concealed amid the twilight of the clustering leaves.
In view of the similarities between data clustering analysis and optimization questions, this paper deals with data clustering analysis by using simulation anneal algorithms.
This paper provides a model of the clustering and an optimized ant colony-clustering algorithm which is based on the swarm intelligence and that mathematic model is provided at the same time.
Then the membership matrix obtained by clustering algorithm was used to reduce attribute set. Finally, based on entropy, a knowledge acquisition method of fuzzy Rough Set (RS) was put forward.
How can we incorporate such prior knowledge into a clustering algorithm?
The hairy roots transformed by ATCC15834 grew rapidly on MS medium without any phytohormones, and were characterized by strongly branching, clustering and non-geotropism, etc.
The paper applies the clustering method in image recognition system.
It is hoped that by clustering these circles in one location, in a country normally not the center of focus during the crop circle season, the message may get better focus and attention.
The basic ant colony clustering algorithm in the calculation of similarity, due to not take direction between adjacent objects, often caused by clustering algorithms do not even slow convergence.
In this paper, we analyses why the clustering algorithms are put out in Ad Hoc Networks.
The premise structure of fuzzy model is confirmed by the improved fuzzy clustering, and fuzzy relation matrix of fuzzy model is confirmed by orthogonal least square.
Vertical clustering is achieved by clustering the queue managers using WebSphere MQ clustering, which optimizes processing and provides the following advantages.
It will output a low quality clustering result if user set unsuitable parameters before clustering operation.
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