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A decentralized predictive maintenance system based on data mining concepts IPB - Escola Superior Agrária
Lopes, Isabel; Pires, L.C.M.; Bastos, Pedro.
In the last years we have assisted to several and deep changes in industrial manufacturing. Induced by the need of increasing efficiency, bigger flexibility, better quality and lower costs, it became more complex [1]. Enterprises had had the need to cope with market expectations, incorporating in their production philosophies new paradigms such as JIT- Just in time, MTOMake to order, Mass Customization, agile manufacturing or Lean Manufacturing, that allow them to satisfy markets with a big diversity of products and also big quantities, becoming therefore more competitive. All this complexity has caused big pressure under enterprises maintenance systems. Maintenance mission is to make equipment and facilities available when requested. Maintenance function,...
Tipo: ConferenceObject Palavras-chave: Management; Maintenance; Data mining; E-collaboration protocols; Reference architectures.
Ano: 2010 URL: http://hdl.handle.net/10198/3927
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A decision-tree-based model for evaluating the thermal comfort of horses Scientia Agricola
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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A importância do data mining na descoberta de padrões e tendências nos dados IPB - Escola Superior Agrária
Bastos, Pedro.
Hoje em dia, a quantidade de dados gerados e armazenados no decurso de uma qualquer actividade excede a capacidade de análise desses mesmos dados sem o uso de técnicas de análise automatizadas. Como consequência deste aumento efetivo de informação, o processamento através de métodos tradicionais tornou-se mais difícil e complexo. As ferramentas convencionais de análises de dados têm capacidades limitadas em detetar padrões e descobrir o conhecimento inserido nos dados, pois só utilizam métodos estatísticos. Surgiu então a urgente necessidade de uma nova geração de técnicas e ferramentas computacionais de forma a assistir o ser humano na extração de informação útil, isto é, conhecimento. Assim, no final dos anos 80 emergiu a área da descoberta de...
Tipo: ConferenceObject Palavras-chave: Descoberta de conhecimento em bases de dados; Data mining.
Ano: 2011 URL: http://hdl.handle.net/10198/4315
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A legume genomics resource: The Chickpea Root Expressed Sequence Tag Database Electron. J. Biotechnol.
Jayashree,B; Buhariwalla,Hutokshi K; Shinde,Sanjeev; Crouch,Jonathan H.
Chickpea, a lesser-studied grain legume, is being investigated due to its taxonomic proximity with the model legume genome Medicago truncatula and its ability to endure and grow in relatively low soil water contents making it a model legume crop for the study of agronomic response to drought stress. Public databases currently contain very few sequences from chickpea associated with expression in root tissues. However, root traits are likely to be one of the most important components of drought tolerance in chickpea. Thus, we have generated a set of over 2800 chickpea expressed sequence tags (ESTs) from a library constructed after subtractive suppressive hybridization (SSH) of root tissue from two closely related chickpea genotypes possessing different...
Tipo: Journal article Palavras-chave: Cloning; Data mining; Drought avoidance; Drought tolerance; EST database; Root traits; Stress.
Ano: 2005 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582005000200002
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Advantages and challenges for Brazilian export of frozen beef R. Bras. Zootec.
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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An Intelligent Procedure for the Detection and Classification of Chickens Infected by Clostridium Perfringens Based on their Vocalization Rev. Bras. Ciênc. Avic.
Sadeghi,M; Banakar,A; Khazaee,M; Soleimani,MR.
ABSTRACT In this study, an intelligent method was implemented for the detection and classification of chickens by infected Clostridium perfringens type A based on their vocalization. To this aim, the birds were first divided into two groups that were placed in separate cages with 15 chickens each. Chickens were inoculated with Clostridium perfringens type A on day 14. In order to ensure the absence of secondary diseases and their probable effect on bird vocalization, vaccines for common diseases were administered. During 30 days of the experiment, chicken vocalization was recorded every morning at 8 a.m. using a microphone and a data collection card under equal and controlled conditions. Sound signals were investigated in time domains, and 23 features were...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Poultry health; Bird sound classification; Clostridium perfringens type A; Data mining; Artificial neural network.
Ano: 2015 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2015000400537
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Authentication of Virgin Olive Oil by Using Dielectric spectroscopy combined with Some Artificial Intelligence Methods CIGR Journal
Soltani, Mahmoud; Rashvand, Mahdi; Teimouri, Nima; Omid, Mahmoud.
Adulteration is a serious problem in the food industry. Olive oil is widely adulterated with other cheap edible oils such as sunflower and canola oils. Therefore, developing a low-cost, practical and rapid analytical method for detecting such adulteration in olive oil would be useful and needed.  In this research, we aimed to develop a dielectric measurement based system combined with complementary analytical intelligent techniques to recognize authentication of virgin olive oil from adulterated with vegetable oils (canola and sunflower). 192 sinusoidal signals in the range of 20 kHz and 20 MHz were feed into the cylindrical dielectric sensor filled with oil sample. Correlation based feature selection (CFS) was applied to select the most appropriate...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Postharvest Engineering Olive oil; Authentication; Dielectric properties; Data mining.
Ano: 2019 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/5483
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Bioinformática : Aplicaciones a la proteómica y genómica Colegio de Postgraduados
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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Biometric characteristics and canopy reflectance association for early-stage sugarcane biomass prediction Scientia Agricola
Rocha,Murillo Grespan da; Barros,Flávio Margarito Martins de; Oliveira,Stanley Robson de Medeiros; Amaral,Lucas Rios do.
ABSTRACT: Knowing the spatial variability of sugarcane biomass in the early stages of development may help growers in their management decision-making. Proximal canopy sensing is a promising technology that can identify this variability but is limited to quantifying plant-specific parameters. In this study, we evaluated whether biometric variables integrated with canopy reflectance data can assist in the generation of models for early-stage sugarcane biomass prediction. To substantiate this assertion, four sugarcane-producing fields were measured with an active crop canopy sensor and 30 sampling plots were selected for manually quantifying chlorophyll content, plant height, stalk number and aboveground biomass. We determined that Random Forest and Multiple...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Random forest; Canopy sensor; Vegetation indices; Precision farming; Data mining.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019001400274
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Boosted regression (boosting): An introductory tutorial and a Stata plugin AgEcon
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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C4.5: um recurso para geração de árvores de decisão. Infoteca-e
BERNARDES, R. M..
O Sistema de Indução C4.5. Requerimentos-chave para a utilização do software. Um exemplo ilustrativo. Algumas dicas de uso.
Tipo: Séries anteriores (INFOTECA-E) Palavras-chave: Árvores de decisão; Mineração de dados; Data mining; KDD; Knowledge Discovery in Databases; Sistema de indução C4; 5.
Ano: 2001 URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/8304
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Classification of soil respiration in areas of sugarcane renewal using decision tree Scientia Agricola
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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Comparative analysis of decision tree algorithms on quality of water contaminated with soil Ciência Rural
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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COMPARATIVE ASSESSMENT BETWEEN PER-PIXEL AND OBJECT-ORIENTED FOR MAPPING LAND COVER AND USE REA
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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Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan R. Bras. Zootec.
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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Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum) Electron. J. Biotechnol.
Torres-Avilés,Francisco; Romeo,José S; López-Kleine,Liliana.
Background Molecular mechanisms of plant-pathogen interactions have been studied thoroughly but much about them is still unknown. A better understanding of these mechanisms and the detection of new resistance genes can improve crop production and food supply. Extracting this knowledge from available genomic data is a challenging task. Results Here, we evaluate the usefulness of clustering, data-mining and regression to identify potential new resistance genes. Three types of analyses were conducted separately over two conditions, tomatoes inoculated with Phytophthora infestans and not inoculated tomatoes. Predictions for 10 new resistance genes obtained by all applied methods were selected as being the most reliable and are therefore reported as potential...
Tipo: Journal article Palavras-chave: Classification; Data mining; Functional gene prediction; GEE models; Gene expression data; Plant immunity genes.
Ano: 2014 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582014000200004
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DATA MINING BASED MODEL AGGREGATION AgEcon
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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Digital soil mapping using reference area and artificial neural networks Scientia Agricola
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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Estimating mortality in laying hens as the environmental temperature increases Rev. Bras. Ciênc. Avic.
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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IDENTIFICATION OF HOMOGENEOUS RAINFALL ZONES DURING GRAIN CROPS IN PARANÁ, BRAZIL REA
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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