Search results for "CLUSTER"
showing 10 items of 3640 documents
Comparison of Micro X-ray Computer Tomography Image Segmentation Methods: Artificial Neural Networks Versus Least Square Support Vector Machine
2013
Micro X-ray computer tomography (XCT) is a powerful non-destructive method for obtaining information about rock structures and mineralogy. A new methodology to obtain porosity from 2D XCT digital images using artificial neural network and least square support vector machine is demonstrated following these steps: the XCT image was first preprocessed, thereafter clustering algorithms such as K-means, Fuzzy c-means and self-organized maps was used for image segmentation. Then artificial neural network was applied for image classification. For comparison, least square support vector machine approach was used for classification labeling of the scan images. The methodology shows how artificial ne…
A Cluster Analysis of Stock Market Data Using Hierarchical SOMs
2016
The analysis of stock markets has become relevant mainly because of its financial implications. In this paper, we propose a novel methodology for performing a structured cluster analysis of stock market data. Our proposed method uses a tree-based neural network called the TTOSOM. The TTOSOM performs self-organization to construct tree-based clusters of vector data in the multi-dimensional space. The resultant tree possesses interesting mathematical properties such as a succinct representation of the original data distribution, and a preservation of the underlying topology. In order to demonstrate the capabilities of our method, we analyze 206 assets of the Italian stock market. We were able…
Neural Network-Based Process Analysis in Sport
2011
Processes in sport like motions or games are influenced by communication, interaction, adaptation, and spontaneous decisions. Therefore, on the one hand, those processes are often fuzzy and unpredictable and so have not extensively been dealt with, yet. On the other hand, most of those processes structurally are roughly determined by intention, rules, and context conditions and so can be classified by means of information patterns deduced from data models of the processes. Self organizing neural networks of type Kohonen Feature Map (KFM) help for classifying information patterns – either by mapping whole processes to corresponding neurons (see Perl & Lames, 2000; McGarry & Perl, 200…
Clustering Quality and Topology Preservation in Fast Learning SOMs
2008
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original …
Discovering representative models in large time series databases
2004
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical observations could allow to perform diagnosis and/or prognosis. Moreover, the efficient discovery of frequent patterns may play an important role in several data mining tasks such as association rule discovery, clustering and classification. However, in order to identify interesting repetitions, it is necessary to allow errors in the matching patterns; in this context, it is difficult to select one pattern particularly suited to represent the set of similar ones, whereas modelling this set with a single model could…
Cosmological parameters degeneracies and non-Gaussian halo bias
2010
We study the impact of the cosmological parameters uncertainties on the measurements of primordial non-Gaussianity through the large-scale non-Gaussian halo bias effect. While this is not expected to be an issue for the standard Lambda CDM model, it may not be the case for more general models that modify the large-scale shape of the power spectrum. We consider the so-called local non-Gaussianity model, parametrized by the f(NL) non-Gaussianity parameter which is zero for a Gaussian case, and make forecasts on f(NL) from planned surveys, alone and combined with a Planck CMB prior. In particular, we consider EUCLID- and LSST-like surveys and forecast the correlations among f(NL) and the runni…
Search for eccentric binary black hole mergers with advanced LIGO and advanced Virgo during their first and second observing runs
2019
When formed through dynamical interactions, stellar-mass binary black holes may retain eccentric orbits ($e>0.1$ at 10 Hz) detectable by ground-based gravitational-wave detectors. Eccentricity can therefore be used to differentiate dynamically-formed binaries from isolated binary black hole mergers. Current template-based gravitational-wave searches do not use waveform models associated to eccentric orbits, rendering the search less efficient to eccentric binary systems. Here we present results of a search for binary black hole mergers that inspiral in eccentric orbits using data from the first and second observing runs (O1 and O2) of Advanced LIGO and Advanced Virgo. The search uses min…
The Gaia-ESO survey: Metallicity of the chamaeleon i star-forming region
2014
Context. Recent metallicity determinations in young open clusters and star-forming regions suggest that the latter may be characterized by a slightly lower metallicity than the Sun and older clusters in the solar vicinity. However, these results are based on small statistics and inhomogeneous analyses. The Gaia-ESO Survey is observing and homogeneously analyzing large samples of stars in several young clusters and star-forming regions, hence allowing us to further investigate this issue. Aims. We present a new metallicity determination of the Chamaeleon I star-forming region, based on the products distributed in the first internal release of the Gaia-ESO Survey. Methods. 48 candidate member…
Searches for clustering in the time integrated skymap of the ANTARES neutrino telescope
2014
Adrián-Martínez, S. et al.
Thinking outside the box: effects of modes larger than the survey on matter power spectrum covariance
2012
Considering the matter power spectrum covariance matrix, it has recently been found that there is a potentially dominant effect on mildly non-linear scales due to power in modes of size equal to and larger than the survey volume. This {\it beat coupling} effect has been derived analytically in perturbation theory and while it has been tested with simulations, some questions remain unanswered. Moreover, there is an additional effect of these large modes, which has so far not been included in analytic studies, namely the effect on the estimated {\it average} density which enters the power spectrum estimate. In this article, we work out analytic, perturbation theory based expressions including…