|
|
|
Registros recuperados: 29 | |
|
| |
|
| |
|
|
OLDONI, L. V.; CATTANI, C. E. V.; MERCANTE, E.; JOHANN, J. A.; ANTUNES, J. F. G.; ALMEIDA, L.. |
ABSTRACT: In the state of Paraná, Brazil, there are no major changes in areas cultivated with annual crops, mainly due to environmental laws that do not allow expansions to new areas. There is a great contribution of the annual crops to the domestic demand of food and economic demand in the exports. Thus, the area and distribution of annual crops are information of great importance. New methodologies, such as data mining, are being tested with the objective of analyzing and improving their potential use for classification of land use and land cover. This study used the classifiers decision tree and random forest with Normalized Difference Vegetation Index (NDVI) temporal metrics on images from Operational Land Imager (OLI)/Landsat-8. The results were... |
Tipo: Artigo de periódico |
Palavras-chave: Árvore de decisão; Métricas temporais de NDVI; Mineração de dados; Séries temporais; Decision tree; NDVI temporal metrics; Random forest; Data mining; Normalized difference vegetation index; Time series analysis. |
Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1114915 |
| |
|
|
Oldoni,Lucas V.; Cattani,Carlos E. V.; Mercante,Erivelto; Johann,Jerry A.; Antunes,João F. G.; Almeida,Luiz. |
ABSTRACT In the state of Paraná, Brazil, there are no major changes in areas cultivated with annual crops, mainly due to environmental laws that do not allow expansions to new areas. There is a great contribution of the annual crops to the domestic demand of food and economic demand in the exports. Thus, the area and distribution of annual crops are information of great importance. New methodologies, such as data mining, are being tested with the objective of analyzing and improving their potential use for classification of land use and land cover. This study used the classifiers decision tree and random forest with Normalized Difference Vegetation Index (NDVI) temporal metrics on images from Operational Land Imager (OLI)/Landsat-8. The results were... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Decision tree; Random forest; NDVI temporal metrics. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001200952 |
| |
|
| |
|
| |
|
|
FARHATE, C. V. V.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M.; CARVALHO, J. L. N.; LA SCALA JÚNIOR, N.; SANTOS, A. P. G.. |
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: Artigo de periódico |
Palavras-chave: Mineração de dados; Emissão de gás carbônico no solo; Seleção de variável; Temperatura no solo; Matéria orgânica no solo; Árvore de decisão; Data mining; Variable selection; Decision tree; Respiração do Solo; Carbon dioxide; Soil temperature; Soil organic matter. |
Ano: 2018 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1105884 |
| |
|
|
BROWN, J. C.; KASTENS, J. H.; COUTINHO, A. C.; VICTORIA, D. de C.; BISHOP, C. R.. |
MODIS 250-m NDVI and EVI datasets are now regularly used to classify regional-scale agricultural land-use practices in many different regions of the globe, especially in the state of Mato Grosso, Brazil, where rapid land-use change due to agricultural development has attracted considerable interest from researchers and policy makers. Variation exists in which MODIS datasets are used, how they are processed for analysis, and what ground reference data are used. Moreover, various and-use/land-cover classes are ultimately resolved, and as yet, crop-specific classifications (e.g. soy?corn vs. soy?cotton double crop) have not been reported in the literature, favoring instead generalized classes such as single vs. double crop. The objective of this study is to... |
Tipo: Artigo de periódico |
Palavras-chave: Cross validation; Soybean.; Decision tree; Cotton; Land cover.. |
Ano: 2013 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/964430 |
| |
|
|
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 |
| |
|
| |
|
|
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 |
| |
|
|
Cruz-Cárdenas,Gustavo; Ortiz-Solorio,Carlos Alberto; Ojeda-Trejo,Enrique; Martínez-Montoya,Juan Felipe; Sotelo-Ruiz,Erasto Domingo; Licona-Vargas,Atenogenes Leobardo. |
Map units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Decision tree; Digital elevation model; Map quality. |
Ano: 2011 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832011000300003 |
| |
|
| |
|
|
Roucan-Kane, Maud; Boehlje, Michael; Gray, Allan W.; Akridge, Jay T.. |
The objective of this paper is to present the teaching note of a case study. The case study outlines the strategic issues facing Excel Cooperative as a result of the rapid expansion of biofuel production capacity in the Midwestern U.S. Excel Cooperative is a mid-sized, ‘local’, farmer-owned cooperative serving farmers in north central Indiana. Excel is composed of four divisions: agronomy, energy, grain, and feed/livestock. With the Excel case, the reader must think strategically about the broad impacts of the biofuel “boom”, apply strategic management tools and decision-making under uncertainty concepts to better understand the impacts, and frame a response. The methodology proposed in the teaching note is composed of a SWOT analysis, scorecarding and... |
Tipo: Working or Discussion Paper |
Palavras-chave: Uncertainty; Risk; Heat mapping; Scorecarding; Scenario analysis; Payoff matrix; Decision tree; Real option; Traps; Agribusiness; D81. |
Ano: 2009 |
URL: http://purl.umn.edu/53584 |
| |
|
| |
|
|
Mengue,Vagner P.; Fontana,Denise C.; Silva,Tatiana S. da; Zanotta,Daniel; Scottá,Fernando C.. |
ABSTRACT This study aimed to verify the applicability of using MODIS-EVI sensor time series for land use and vegetation cover mapping in the Pampa biome, Rio Grande do Sul state, Brazil. The study period comprised the months from June 2013 to June 2014. The procedures included the use of MODIS Sensor images, altimetric data and nighttime images, associated with a hierarchical decision tree classifier, constructed using the C4.5 algorithm. The proposed approach stems from the consideration that the study area has varying characteristics and, therefore, should be treated simultaneously by different and intuitive classifiers, which justifies the choice of decision tree. To evaluate the results, reference data acquired from Landsat 8-OLI satellite images and... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Decision tree; Soybean; Multitemporal. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001100812 |
| |
|
| |
|
| |
|
|
DI GIROLAMO NETO, C.; RODRIGUES, L. H. A.; MEIRA, C. A. A.. |
RESUMO: A ferrugem é a principal doença do cafeeiro, podendo gerar perdas significativas na produção, caso medidas de controle não sejam adotadas. Modelos de alerta de doenças agrícolas são capazes de gerar informações para aplicações de defensivos somente quando necessário, reduzindo gastos por parte do produtor e impactos ambientais. Objetivou-se, neste trabalho, desenvolver, comparar e selecionar modelos de alerta baseados em técnicas de mineração de dados para a predição da ferrugem do cafeeiro, em anos de alta e baixa carga pendente de frutos. Foram utilizados dados obtidos em lavouras de café em produção, ao longo de 13 anos (1998-2011). Vinte e três atributos foram considerados como variáveis independentes (preditoras) e, como variável dependente, a... |
Tipo: Artigo de periódico |
Palavras-chave: Ferrugem do cafeeiro; Alerta de doenças; Florestas aleatórias; Máquinas de vetores suporte; Redes neurais artificiais; Árvores de decisão; Decision tree; Neural networks. |
Ano: 2014 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/991078 |
| |
|
| |
Registros recuperados: 29 | |
|
|
|