K Nearest Neighbor Algorithm
Mostrando 1-12 de 13 artigos, teses e dissertações.
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1. Identifying olive oil fraud and adulteration using machine learning algorithms
As olive oil (OO) is more expensive than other vegetable oils, it is usually adulterated by blending it with more economic edible oils such as cottonseed oil (CSO), canola oil (CO), and soybean oil (SO). This research aimed to determine the fatty acid compositions obtained as a result of blending different proportions of CSO, CO and SO with OO using a gas ch
Química Nova. Publicado em: 2022
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2. Quantitative MRI data in Multiple Sclerosis patients: a pattern recognition study
Abstract Introduction Multiple Sclerosis (MS) is a neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Quantitative Magnetic Resonance Imaging (qMRI) enables a detailed characterization of brain tissue, but generates a large number of numerical results. In this study, we elucidated the main qMRI techniques a
Res. Biomed. Eng.. Publicado em: 28/05/2018
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3. Estudo da influÃncia de diversas medidas de similaridade na previsÃo de sÃries temporais utilizando o algoritmo KNN-TSP / Study of the influence of similarity measures in Time Series Prediction with the kNN-TSP algorithm
SÃries temporais podem ser entendidas como qualquer conjunto de observaÃÃes que se encontram ordenadas no tempo. Dentre as vÃrias tarefas possÃveis com dados temporais, uma que tem atraÃdo crescente interesse, devido a suas vÃrias aplicaÃÃes, Ã a previsÃo de sÃries temporais. O algoritmo k-Nearest Neighbor - Time Series Prediction (kNN-TSP) Ã um
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 11/04/2012
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4. Soluções aproximadas para algoritmos escaláveis de mineração de dados em domínios de dados complexos usando GPGPU / On approximate solutions to scalable data mining algorithms for complex data problems using GPGPU
The increasing availability of data in diverse domains has created a necessity to develop techniques and methods to discover knowledge from huge volumes of complex data, motivating many research works in databases, data mining and information retrieval communities. Recent studies have suggested that searching in complex data is an interesting research field
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 22/09/2011
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5. Classificação orientada ao objeto de imagem Quickbird-2 para a identificação da Araucária / Object-oriented classification of Quickbird-2 image for the identification of Araucaria
O objetivo do presente estudo foi mapear as copas de Araucaria angustifolia em uma imagem Quickbird-2 através da classificação orientada ao objeto. A área de estudos está inserida em um fragmento de Floresta Ombrófila Mista localizada na Floresta Nacional de Irati PR. Baseado em fotografias aéreas em escala 1:2.000, foi realizado o trabalho de campo e
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 10/02/2011
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6. Algoritmo kNN para previsão de dados temporais: funções de previsão e critérios de seleção de vizinhos próximos aplicados a variáveis ambientais em limnologia / Time series prediction using a KNN-based algorithm prediction functions and nearest neighbor selection criteria applied to limnological data
A análise de dados contendo informações sequenciais é um problema de crescente interesse devido à grande quantidade de informação que é gerada, entre outros, em processos de monitoramento. As séries temporais são um dos tipos mais comuns de dados sequenciais e consistem em observações ao longo do tempo. O algoritmo k-Nearest Neighbor - Time Serie
Publicado em: 2009
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7. Conversão simbólica de sinais digitais por meio da Teoria de Extremos Relativos
The goal is to develop a new technique for symbolic conversion of digital signals, called Quantization based on Relative Extrema (QBER). This technique can convert unidimensional digital signals into strings. The technique QBER, formalized in this proposal, uses Relative Extrema Theory (TER ) and signals similarity functions, as metric Edit Distance with Rea
Publicado em: 2009
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8. Investigation of a framework based on artificial immune system applied to the pattern recognition / InvestigaÃÃo de uma arquitetura baseada em sistemas imunolÃgicos artificiais aplicada ao reconhecimento de dÃgitos manuscritos
The discovery of new functionalities through the study of human physiology has contributed toward the evolution of Artificial Immune Systems. The present work investigates a new architecture through observations of natural immunological behavior. New functionalities observed in the biological environment were studied for the modeling of this immunological ap
Publicado em: 2007
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9. Projeto e implementação de circuitos classificadores digitais com controle da generalização baseado na regra do vizinho-mais-próximo modificada
This work aims at the implementation of classifying binary patterns with digital circuits in order to get a embedded system with the following features: portability, on-line training, operating in real time and with capacity of generalization. The proposed method makes use of training data filtering (or selection) before digital circuit synthesis. It is prop
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 22/02/2006
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10. DBM-Tree: trading height-balancing for performance in metric access methods
Metric Access Methods (MAM) are employed to accelerate the processing of similarity queries, such as the range and the k-nearest neighbor queries. Current methods, such as the Slim-tree and the M-tree, improve the query performance minimizing the number of disk accesses, keeping a constant height of the structures stored on disks (height-balanced trees). How
Journal of the Brazilian Computer Society. Publicado em: 2006-04
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11. A self-organizing principle for learning nonlinear manifolds
Modern science confronts us with massive amounts of data: expression profiles of thousands of human genes, multimedia documents, subjective judgments on consumer products or political candidates, trade indices, global climate patterns, etc. These data are often highly structured, but that structure is hidden in a complex set of relationships or high-dimensio
National Academy of Sciences.
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12. Rapid identification of mycolic acid patterns of mycobacteria by high-performance liquid chromatography using pattern recognition software and a Mycobacterium library.
Current methods for identifying mycobacteria by high-performance liquid chromatography (HPLC) require a visual assessment of the generated chromatographic data, which often involves time-consuming hand calculations and the use of flow charts. Our laboratory has developed a personal computer-based file containing patterns of mycolic acids detected in 45 speci