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| Registros recuperados: 39 | |
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| Maia,Ana Paula de Assis; Oliveira,Stanley Robson de Medeiros; Moura,Daniella Jorge de; Sarubbi,Juliana; Vercellino,Rimena do Amaral; Medeiros,Brenda Batista Lemos; Griska,Paulo Roberto. |
| Thermal comfort is of great importance in preserving body temperature homeostasis during thermal stress conditions. Although the thermal comfort of horses has been widely studied, there is no report of its relationship with surface temperature (T S). This study aimed to assess the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. T S was obtained using infrared thermography image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The variables of armpit, croup, breast and groin T S of horses and the predicted classes were then subjected to a machine learning process. All variables in the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Feature selection methods; Data mining; Surface temperature; Infrared thermography; Thermoregulation. |
| Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162013000600001 |
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| Pereira,Paulo Rodrigo Ramos Xavier; Barcellos,Júlio Otávio Jardim; Federizzi,Luiz Carlos; Lampert,Vinícius do Nascimento; Canozzi,Maria Eugênia Andrighetto; Marques,Pedro Rocha. |
| The objectives of this research were to analyse data on the international market of frozen boneless beef and to classify its participants into groups according to their trade relationships, identifying the main factors that influence the preference of a country to beef from a determined supplier country. International beef trade is composed of two markets: in one of them, the relationships between supplier and client depend on the lowest price, and Brazil is found in favorable conditions; and the other, the relationships are preferably based on the sanitary quality of the herd and traceability systems recognized by the purchaser, to which Brazilian participation is low. |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Bovine spongiform encephalopaty (BSE); Cluster analysis; Data mining; Foot and mouth disease; International trade beef. |
| Ano: 2011 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982011000100028 |
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| Riaño Pachón, Diego Mauricio; González Estrada, Elizabeth; Alexa, Adrian; Ramírez, Fidel; Vischi Winck, Flavia; Gómez Merino, Fernando, Coord.; Silva Rojas, Hilda Victoria, Coord.; Pérez Rodríguez, Paulino, Coord.. |
| En esta publicación intitulada “Bioinformática: aplicaciones a la genómica y proteómica” se detallan algunos de los avances más sobresalientes de los temas de genómica y proteómica, derivados de un curso internacional sobre el tema, organizado por el Colegio de Postgraduados. Estos avances incluyen aspectos de las dos ciencias ómicas, incluyendo genómica y biología estructural, código R, análisis comparativo y evolución, agrupamiento y minería de datos en R, redes de interacciones entre proteínas y proteómica bioinformática. BIOINFORMATICS : APPLICATIONS TO GENOMICS AND PROTEOMICS. ABSTRACT : In this publication entitled "Bioinformatics: applications to genomics and proteomics" are some of the most salient issues of genomics and proteomics, derived from an... |
| Tipo: Libro |
Palavras-chave: Bioinformática; Proteómica; Genómica; ADN; Proteínas; Modelación; Simulación; Análisis de genómas; Biología estructural; Código R; Análisis comparativo; Minería de datos; Computación aplicada; Bioinformatics; Proteomics; DNA; Proteins; Models; Genomics; Simulation; R Code; Data mining; Computing; Genome analysis. |
| Ano: 2010 |
URL: http://hdl.handle.net/10521/313 |
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| Schonlau, Matthias. |
| Boosting, or boosted regression, is a recent data-mining technique that has shown considerable success in predictive accuracy. This article gives an overview of boosting and introduces a new Stata command, boost, that implements the boosting algorithm described in Hastie, Tibshirani, and Friedman (2001, 322). The plugin is illustrated with a Gaussian and a logistic regression example. In the Gaussian regression example, the R2 value computed on a test dataset is R2 = 21.3% for linear regression and R2 = 93.8% for boosting. In the logistic regression example, stepwise logistic regression correctly classifies 54.1% of the observations in a test dataset versus 76.0% for boosted logistic regression. Currently, boost accommodates Gaussian (normal), logistic,... |
| Tipo: Journal Article |
Palavras-chave: Boost; Boosted regression; Boosting; Data mining; Research Methods/ Statistical Methods. |
| Ano: 2005 |
URL: http://purl.umn.edu/117524 |
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| Farhate,Camila Viana Vieira; Souza,Zigomar Menezes de; Oliveira,Stanley Robson de Medeiros; Carvalho,João Luís Nunes; Scala Júnior,Newton La; Santos,Ana Paula Guimarães. |
| ABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil CO2 emission; Data mining; Variable selection; Soil temperature; Soil organic matter. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000300216 |
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| Dota,Mara Andrea; Cugnasca,Carlos Eduardo; Barbosa,Domingos Sávio. |
| Agriculture, roads, animal farms and other land uses may modify the water quality from rivers, dams and other surface freshwaters. In the control of the ecological process and for environmental management, it is necessary to quickly and accurately identify surface water contamination (in areas such as rivers and dams) with contaminated runoff waters coming, for example, from cultivation and urban areas. This paper presents a comparative analysis of different classification algorithms applied to the data collected from a sample of soil-contaminated water aiming to identify if the water quality classification proposed in this research agrees with reality. The sample was part of a laboratory experiment, which began with a sample of treated water added with... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Environmentalcontrol; Runoff; Wireless sensor networks; Machine learning; Data mining. |
| Ano: 2015 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782015000200267 |
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| Prudente,Victor H. R.; Silva,Bruno B. da; Johann,Jerry A.; Mercante,Erivelto; Oldoni,Lucas V.. |
| ABSTRACT: The traditional per-pixel classification methods consider only spectral information, and may be limited. Object-based classifiers, however, also consider shape and texture, firstly segmenting the image, and then classifying individual objects. Thus, a Geographic Object-Based Image Analysis (GEOBIA) was compared in conjunction with data mining techniques and a traditional per-pixel method. A cut of Landsat-8, bands 2 to 7, orbit/point 223/77, located between the municipalities of Cascavel, Corbélia, Cafelândia and Tupãssi, in the west part of the state of Paraná, from 12/18/2013 was used. In the GEOBIA approach was realized image segmentation, spatial and spectral attribute extraction, and classification using the decision tree supervised... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: GeoDMA; Data mining; Decision tree. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000501015 |
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| Celik,Senol; Eyduran,Ecevit; Karadas,Koksal; Tariq,Mohammad Masood. |
| ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: ANN; Artificial intelligence; Data mining; Decision tree; MARS algorithm. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017001100863 |
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| Szucs, Imre. |
| Applying modelling techniques for getting acquainted with customer behaviour, predicting the customers’ next step is neccessary to keep in competition, by decreasing the capital requirement (Basel II - IRB) or making the portfolio more profitable. According to the easily implementable modelling techniques, data mining solutions widespread in practice. Using these models with no conditions can lead into inconsistent future on portfolio change. Consequence of this situation, contradictory predictions and conclusions come into existence. Recognizing and conscious handling of inconsistent predictions is an important task for experts working on different scene of the knowledge based economy and society. By realizing and solving the problem of inconsistency in... |
| Tipo: Journal Article |
Palavras-chave: Model aggregation; Consistent future; Data mining; CRM; Basel II; Research and Development/Tech Change/Emerging Technologies. |
| Ano: 2007 |
URL: http://purl.umn.edu/58928 |
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| Arruda,Gustavo Pais de; Demattê,José A. M.; Chagas,César da Silva; Fiorio,Peterson Ricardo; Souza,Arnaldo Barros e; Fongaro,Caio Troula. |
| ABSTRACT Digital soil mapping is an alternative for the recognition of soil classes in areas where pedological surveys are not available. The main aim of this study was to obtain a digital soil map using artificial neural networks (ANN) and environmental variables that express soil-landscape relationships. This study was carried out in an area of 11,072 ha located in the Barra Bonita municipality, state of São Paulo, Brazil. A soil survey was obtained from a reference area of approximately 500 ha located in the center of the area studied. With the mapping units identified together with the environmental variables elevation, slope, slope plan, slope profile, convergence index, geology and geomorphic surfaces, a supervised classification by ANN was... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Map extrapolation; Pedological survey; Landscape attributes; Pedological classes; Data mining. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000300266 |
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| Pereira,DF; do Vale,MM; Zevolli,BR; Salgado,DD. |
| Layer mortality due to heat stress is an important economic loss for the producer. The aim of this study was to determine the mortality pattern of layers reared in the region of Bastos, SP, Brazil, according to external environment and bird age. Data mining technique were used based on monthly mortality records of hens in production, 135 poultry houses, from January 2004 to August 2008. The external environment was characterized according maximum and minimum temperatures, obtained monthly at the meteorological station CATI in the city of Tupã, SP, Brazil. Mortality was classified as normal (£ 1.2%) or high (> 1.2%), considering the mortality limits mentioned in literature. Data mining technique produced a decision tree with nine levels and 23 leaves,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data mining; Layer production; Mortality; Thermal comfort. |
| Ano: 2010 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2010000400008 |
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| Lopes,Allan R.; Marcolin,Jonatas; Johann,Jerry A.; Boas,Márcio A. Vilas; Schuelter,Adilson R.. |
| ABSTRACT The aim of this study is to identify homogeneous rainfall zones in the winter and summer 1st and 2nd crops, in the state of Paraná, Brazil. The zones were defined by clustering using the expectation-maximization (EM) algorithm to transform seasonal rainfall series. Monthly average rainfall data collected from 157 weather stations for 20 years (1996 to 2015) were employed. The results show that the number of homogeneous zones varied among growing seasons. The summer crop presented two clusters, with rainfall averages of 1489 and 1925 mm; the second crop presented four clusters, with averages of 1849, 1004, 1454, and 1182 mm; and the winter crop had three clusters, with averages of 969, 1498, and 1171 mm. Clustering was a useful instrument to... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data mining; Clusters; Expectation-maximization; Weka; Soybean; Maize; Wheat. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000600707 |
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| Registros recuperados: 39 | |
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