Support Vector Machines
Mostrando 1-12 de 86 artigos, teses e dissertações.
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1. Prediction of restrained shrinkage crack width of slag mortar composites using data mining techniques
ABSTRACT The purpose of this study is to develop data mining models to predict restrained shrinkage crack widths of slag mortar cementitious composites. A database published by BILIR et al. [1] was used to develop these models. As a modelling tool R environment was used to apply these data mining (DM) techniques. Several algorithms were tested and analyzed u
Matéria (Rio J.). Publicado em: 25/11/2019
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2. Predico do Câncer de Mama com Aplicação de Modelos de Inteligência Computacional
RESUMO O uso de modelos para diagnóstico auxiliado por computador (CAD) tem sido proposto para auxiliar na detecção e classificação do câncer de mama. Neste trabalho, avaliou-se o desempenho dos modelos de rede neural de perceptrons de múltiplas camadas e máquina de vetores de suporte não linear para classificar nódulos de câncer de mama. Dez cara
TEMA (São Carlos). Publicado em: 16/09/2019
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3. A Regional Legacy Soil Dataset for Prediction of Sand and Clay Content with Vis-Nir-Swir, in Southern Brazil
ABSTRACT The success of soil prediction by VIS-NIR-SWIR spectroscopy has led to considerable investment in large soil spectral libraries. The aims of this study were 1) to develop a soil VIS-NIR-SWIR spectroscopy approach using legacy soil samples to improve spectral soil information in a regional scale; (2) to compare six spectral preprocessing techniques;
Rev. Bras. Ciênc. Solo. Publicado em: 15/08/2019
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4. AlradSpectra: a Quantification Tool for Soil Properties Using Spectroscopic Data in R
ABSTRACT Soil reflectance spectroscopy has become an innovative method for soil property quantification supplying data for studies in soil fertility, soil classification, digital soil mapping, while reducing laboratory time and applying a clean technology. This paper describes the implementation of a Graphical User Interface (GUI) using R named AlradSpectra.
Rev. Bras. Ciênc. Solo. Publicado em: 29/07/2019
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5. An SHM approach using machine learning and statistical indicators extracted from raw dynamic measurements
Abstract Structural Health Monitoring using raw dynamic measurements is the subject of several studies aimed at identifying structural modifications or, more specifically, focused on damage assessment. Traditional damage detection methods associate structural modal deviations to damage. Nevertheless, the process used to determine modal characteristics can in
Lat. Am. j. solids struct.. Publicado em: 14/03/2019
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6. Principal Component Analysis with Linear and Quadratic Discriminant Analysis for Identification of Cancer Samples Based on Mass Spectrometry
Mass spectrometry (MS) is a powerful technique that can provide the biochemical signature of a wide range of biological materials such as cells and biofluids. However, MS data usually has a large range of variables which may lead to difficulties in discriminatory analysis and may require high computational cost. In this paper, principal component analysis wi
J. Braz. Chem. Soc.. Publicado em: 2018-03
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7. THE USE OF ARTIFICIAL INTELLIGENCE FOR ESTIMATING SOIL RESISTANCE TO PENETRATION
ABSTRACT The aim of this study was to present and to evaluate methodologies for the estimation of soil resistance to penetration (RP) using artificial intelligence prediction techniques. In order to do so, a data base with values of physical-water characteristics of the soils available in the literature was used, and the performances of Artificial Neural Net
Eng. Agríc.. Publicado em: 2018-01
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8. Detecção de mudanças baseada em objetos utilizando indices do semivariograma derivados de imagens NDVI: O disastre ambiental em Mariana, Brasil
RESUMO Recentemente, variáveis geoestatísticas derivadas de imagens de sensoriamento remoto ganharam espaço dentre os procedimentos de detecção de mudanças, porém, o potencial temporal destas variáveis para o mapeamento das mudanças baseado na análise por objetos ainda é pouco estudado. Neste estudo, o desempenho de um conjunto de índices calcula
Ciênc. agrotec.. Publicado em: 2017-09
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9. Breast tumor classification in ultrasound images using support vector machines and neural networks
Abstract Introduction The use of tools for computer-aided diagnosis (CAD) has been proposed for detection and classification of breast cancer. Concerning breast cancer image diagnosing with ultrasound, some results found in literature show that morphological features perform better than texture features for lesions differentiation, and indicate that a reduc
Res. Biomed. Eng.. Publicado em: 10/10/2016
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10. Proposta de metodologia para a criação de etiqueta de classificação – estudo de caso: desempenho escolar
Resumo A qualidade na educação tem sido objeto de muita discussão, seja nas escolas e entre seus gestores, seja na mídia ou na literatura. No entanto, uma análise mais profunda na literatura parece não indicar técnicas que explorem bancos de dados com a finalidade de obter classificações para o desempenho escolar, nem tampouco há um consenso sobre
Gest. Prod.. Publicado em: 22/03/2016
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11. CLASSIFICATION OF POWER QUALITY CONSIDERING VOLTAGE SAGS IN DISTRIBUTION SYSTEMS USING KDD PROCESS
In this paper, we propose a methodology to classify Power Quality (PQ) in distribution systems based on voltage sags. The methodology uses the KDD process (Knowledge Discovery in Databases) in order to establish a quality level to be printed in labels. The methodology was applied to feeders on a substation located in Curitiba, Paraná, Brazil, considering at
Pesqui. Oper.. Publicado em: 2015-08
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12. Seleção de componentes em ensembles de clasificadores multirrótulo / Component Selection in Ensembles of Multi-label Classifiers
The selection of components in ensembles of classifiers is a very common activity in the field of Machine Learning with several studies showing its effectiveness in obtaining significant gains in accuracy. However, the most studied classification task involves mutually exclusive labels (classes). The objective of this work is to present a study on the select
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 27/07/2012