Svm Support Vector Machines
Mostrando 1-12 de 41 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. 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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3. 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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4. 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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5. 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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6. 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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7. 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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8. Detecção e classificação de arritmias em eletrocardiogramas usando transformadas wavelets, máquinas de vetores de suporte e rede Bayesiana
The cardiopathies are currently, according the Ministério da Saúde, the second biggest cause of mortality among the Brazilians, behind only the brain vascular diseases. The motivation for the work here presented is the identification and classification of cardiopathies registered in Electrocardiogram exams, ECG, such as premature contractions, branches blo
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 02/03/2012
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9. Detecção de falhas em motores elétricos através das máquinas de vetores de suporte / Fault detection in induction motors using support vector machines
Motores elétricos são componentes essenciais na grande maioria dos processos industriais. As diversas falhas nas máquinas de indução podem gerar consequências drásticas para um processo industrial. Os principais problemas estão relacionados ao aumento dos custos, piora nas condições do processo e de segurança e qualidade do produto final. Muitas d
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 24/02/2012
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10. Monitoramento da cobertura do solo no entorno de hidrelétricas utilizando o classificador SVM (Support Vector Machines). / Land cover monitoring in hydroelectric domain area using Support Vector Machines (SVM) classifier.
A classificação de imagens de satélite é muito utilizada para elaborar mapas de cobertura do solo. O objetivo principal deste trabalho consistiu no mapeamento automático da cobertura do solo no entorno da Usina de Lajeado (TO) utilizando-se o classificador SVM. Buscou-se avaliar a dimensão de áreas antropizadas presentes na represa e a acurácia da cl
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 07/12/2011
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11. Aplicação de máquinas de vetores de suporte para desenvolvimento de modelos de classificação e calibração multivariada em espectroscopia no infravermelho / Application of support vector machines in development of classification and multivariate calibration models in infrared spectroscopy
O objetivo desta tese de doutorado foi de utilizar o algoritmo Máquinas de Vetores de Suporte (SVM) em problemas de classificação e calibração, onde algoritmos mais tradicionais (SIMCA e PLS, respectivamente) encontram problemas. Foram realizadas quatro aplicações utilizando dados de espectroscopia no infravermelho. Na primeira o SVM se mostrou ser um
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 15/07/2011
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12. SENTIMENT ANALYSIS FOR FINANCIAL NEWS ABOUT PETROBRAS COMPANY / CLASSIFICAÇÃO DE SENTIMENTO PARA NOTÍCIAS SOBRE A PETROBRAS NO MERCADO FINANCEIRO
A huge amount of information is available online, in particular regarding financial news. Current research indicate that stock news have a strong correlation to market variables such as trade volumes, volatility, stock prices and firm earnings. Here, we investigate a Sentiment Analysis problem for financial news. Our goal is to classify financial news as fav
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 01/07/2011