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11.
12.
The paper is devoted to statistical nonparametric estimation of multivariate distribution density. The influence of data pre-clustering
on the estimation accuracy of multimodal density is analyzed by means of the Monte Carlo method. It is shown that the soft
clustering is more advantageous than the hard one. While a moderate increase in the number of clusters also increases the
calculation time, it considerably reduces the estimation error. 相似文献
13.
It was proved in 1957 by Huber that any complete surface with integrable Gauss curvature is conformally equivalent to a compact
surface with a finite number of points removed. Counterexamples show that the curvature assumption must necessarily be strengthened
in order to get an analogous conclusion in higher dimensions. We show in this paper that any non compact Riemannian manifold
with finite -norm of the Ricci curvature satisfies Huber-type conclusions if either it is a conformal domain with volume growth controlled
from above in a compact Riemannian manifold or if it is conformally flat of dimension 4 and a natural Sobolev inequality together
with a mild scalar curvature decay assumption hold. We also get partial results in other dimensions.
Received: April 14, 2000; revised version: March 20, 2001 相似文献
14.
Fabio Schoen 《Journal of Global Optimization》1994,4(1):17-35
In this paper a new algorithm is proposed for global optimization problems. The main idea is that of modifying a standard clustering approach by sequentially sampling the objective function while adaptively deciding an appropriate sample size. Theoretical as well as computational results are presented. 相似文献
15.
首先采用模糊聚类分析对煤与瓦斯突出的样本集合进行分类,建立不同突出程度的模糊模式。然后用关联分析确定待预报样本与模式的关联程度,以此预测预报样本的煤与瓦斯突出危险程度。这种预报方法相对于模糊聚类分类后,将模式与待预报样本组成新的样本集合,再进行聚类分析,以此分类结果进行预报法。不仅可靠程度高,而且能定量描述待报样本与模式的亲和程度。 相似文献
16.
This paper describes the k-means range algorithm, a combination of the partitional k-means clustering algorithm with a well known spatial data structure, namely the range tree, which allows fast range searches. It offers a real-time solution for the development of distributed interactive decision aids in e-commerce since it allows the consumer to model his preferences along multiple dimensions, search for product information, and then produce the data clusters of the products retrieved to enhance his purchase decisions. This paper also discusses the implications and advantages of this approach in the development of on-line shopping environments and consumer decision aids in traditional and mobile e-commerce applications. 相似文献
17.
本文用Fuzzy数学的观点探讨了Fuzzy聚类分析,并通过对脊髓灰质炎病毒抗体水平的Fuzzy聚类分析,获得了良好的聚类效果,为该项问题的研究提供了科学依据。 相似文献
18.
A method is described for the rapid and automatic analysis of flexible molecular alignments using multidimensional scaling and a normalized scoring scheme. A projection scheme was devised to separate orientational and conformational effects. It is shown that the approach can be utilized for the identification of common binding orientations or to the study of differences in partioning behavior. It is suggested that the method can be employed as a novel approach exploring molecular similarity as a dynamic property, so that it includes aspects of motion (by way of mutual orientations), conformations and molecular properties. 相似文献
19.
Manuel Urbano Cuadrado Gonzalo Cerruela García Irene Luque Ruiz Miguel Ángel Gómez-Nieto 《Journal of mathematical chemistry》2006,40(1):15-27
A method for the treatment of long-dimensional chemical data arrays is presented in this work with the aim of maximising classification models. The method is based on the construction of fingerprints and the subsequent generation of a similarity matrix. The similarity calculation has been modified through a scaling process to take into account different significance shown by the variables. The method was applied to spectral measurements of wines and several aspects were studied, namely: threshold considered in the construction of fingerprints and patterns, weighting factor used for scaling, normalisation method, etc. The application of both Principal Components Analysis and Soft-Independent Modelling of Class Analogies to the similarity matrices gave better classifications of the information than those obtained using original data. 相似文献
20.
Chemical and physical analyses of malt, the main ingredient of beer, have been used to predict the concentration of certain volatile compounds in the finished beer.The prediction was done by means of the partial least squares regression (PLS2) in SIMCA. The total data set as well as individual malt clusters were submitted to PLS analysis. Best prediction was obtained by separating the total object matrix in classes according to similarity found by fuzzy pattern recognition (FCV). FCV was also used to separate the beer variables in classes and to select the subset of variables to be predicted.A joint approach of fuzzy pattern recognition to identify groups of samples and SIMCA-PLS2 to predict several dependent variables is suggested as a powerful tool in process-analytical chemistry. 相似文献