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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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| Alves,Daniel Pedrosa; Tomaz,Rafael Simões; Laurindo,Bruno Soares; Laurindo,Renata Dias Freitas; Silva,Fabyano Fonseca e; Cruz,Cosme Damião; Nick,Carlos; Silva,Derly José Henriques da. |
| ABSTRACT: Artificial neural networks (ANN) are computational models inspired by the neural systems of living beings capable of learning from examples and using them to solve problems such as non-linear prediction, and pattern recognition, in addition to several other applications. In this study, ANN were used to predict the value of the area under the disease progress curve (AUDPC) for the tomato late blight pathosystem. The AUDPC is widely used by epidemiologic studies of polycyclic diseases, especially those regarding quantitative resistance of genotypes. However, a series of six evaluations over time is necessary to obtain the final area value for this pathosystem. This study aimed to investigate the utilization of ANN to construct an AUDPC in the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Phytophthora infestans; ANN; AUDPC; Artificial intelligence; Plant breeding. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162017000100051 |
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| zaki, hassan; khorasani, Mohammad Esmail; aghili nategh, nahid; Sheikhdavoodi, Mohammad; andekaiezadeh, Korosh. |
| Specific draft is one of the important parameters in the design of tillage tools and estimation of energy consumption in tillage operations, which makes it useful. For this reason, it’s prediction and modeling about different working conditions (depth of plowing and advance velocity) provide the possibility to determine the proper working conditions of tillage implements. In this study, two groups of tillage implements with different geometry including combined tillage implements (combined tiller and chisel packer) and simple tillage implements (moldboard plow, disk plow, chisel plow and offset disk harrow) are used. Also 3 speeds (3, 4.5 and 6 km / h) and 3 different depths (15, 20 and 25 cm) in silty clay loamy soil (47% silt, 22% sand and 31% clay) with... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Specific Draft; Tillage tools; Regression; ANN; Depth; Forward speed. |
| Ano: 2022 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/6433 |
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| SCHIKOWSKI,ANA B.; CORTE,ANA P.D.; RUZA,MARIELI S.; SANQUETTA,CARLOS R.; MONTAÑO,RAZER A.N.R.. |
| Abstract Taper functions and volume equations are essential for estimation of the individual volume, which have consolidated theory. On the other hand, mathematical innovation is dynamic, and may improve the forestry modeling. The objective was analyzing the accuracy of machine learning (ML) techniques in relation to a volumetric model and a taper function for acácia negra. We used cubing data, and fit equations with Schumacher and Hall volumetric model and with Hradetzky taper function, compared to the algorithms: k nearest neighbor (k-NN), Random Forest (RF) and Artificial Neural Networks (ANN) for estimation of total volume and diameter to the relative height. Models were ranked according to error statistics, as well as their dispersion was verified.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Artificial intelligence; Data mining; Random forest; ANN. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000703389 |
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