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To find unknown celestial bodies is one of main goals in mankind's universe exploration, and outlier mining is a kind of effective way of finding unknown celestial bodies from mass spectrum data. In the present work, using VC++ and Oracle9i as development tools, an outlier mining system for star spectra is designed and realized, and its software(More)
OBJECTIVE To explore the main factors influencing the therapeutic effect of acupuncture on neck pain caused by cervical spondylosis, so as to provide references for further increasing the therapeutic effect of acupuncture. METHODS One hundred and six cases were randomly divided into an observation group and a control group, 53 cases in each group. The(More)
OBJECTIVE To observe the clinical effect of acupuncture in treating cervical spondylosis with different syndrome types. METHODS One hundred and seventeen patients were randomized into the treated group: (59 cases), treated with normal acupuncture, and the control group (58 cases), treated with sham acupuncture, operated once every other day, 9 times in(More)
A novel high-dimensional clustering algorithm is proposed. On the basis of this, a two-stage fuzzy clustering approach, named TSPFCM, is presented. On the first stage, data is clustered by a new clustering method. On the second stage, the result of the first stage is taken as the initial cluster centers, and PSO mechanism is inducted into fuzzy clustering(More)
Concept lattice is an effective formal tool for data analysis and knowledge extraction. Constrained concept lattice, with the characteristics of higher constructing efficiency, practicability and pertinency, is a new concept lattice structure. For the automatic classification task of star spectrum, a classification rule mining method based on constrained(More)
It is an effective method of the mankind seeking after the celestial law that the inherent and unknown interrelationships between characteristics of celestial spectrum data and its physical and chemical properties are mined from the mass celestial body spectrum data. In the present paper, the interrelation analysis system of celestial body spectrum data(More)
Discretization of continuous numerical attribute is one of the important research works in the preprocessing of celestial spectrum data. For characteristic line of celestial spectrum, a soft discretization algorithm is presented by using improved fuzzy C-means clustering. Firstly, candidate fuzzy clustering centers of characteristic line are chosen by using(More)
In M star population, some special objects, which may be of magnetic activity, may be giant stars, or may be of other rare properties, are very important for the follow-up observation and the scientific research on galactic structure and evolution. For local bias of M-type star spectral characteristic lines contained in subspace, a late-type star spectra(More)
Frequent pattern, frequently appearing in the data set, plays an important role in data mining. For the stellar spectrum classification tasks, a classification rule mining method based on classification pattern tree is presented on the basis of frequent pattern. The procedures can be shown as follows. Firstly, a new tree structure, i. e., classification(More)