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| Registros recuperados: 64 | |
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| Menezes,Paulo L. de; Azevedo,Carlos A. V. de; Eyng,Eduardo; Dantas Neto,José; Lima,Vera L. A. de. |
| ABSTRACTDetermining uniformity coefficients of sprinkle irrigation systems, in general, depends on field trials, which require time and financial resources. One alternative to reduce time and expense is the use of simulations. The objective of this study was to develop an artificial neural network (ANN) to simulate sprinkler precipitation, using the values of operating pressure, wind speed, wind direction and sprinkler nozzle diameter as the input parameters. Field trials were performed with one sprinkler operating in a grid of 16 x 16, collectors with spacing of 1.5 m and different combinations of nozzles, pressures, and wind conditions. The ANN model showed good results in the simulation of precipitation, with Spearman's correlation coefficient (rs)... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Sprinkler; Water distribution uniformity; Artificial intelligence; Computational model. |
| Ano: 2015 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662015000900817 |
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| Bernhardt, Heinz. |
| The topic logistic has become more and more important in German agriculture during the last years. This is caused by a growth of enterprises and machines but also be the enormous extension of the cultivation of renewable resources for the production of energy. To manage these logistical tasks in agriculture in Germany at the moment different transport systems are preferred. The classical system with tractor and agricultural trailer, transport via truck like it is typical for the commercial transport of goods and the transport with specialized vehicles which can be classified between both systems. To evaluate these transport processes it is decisive for the farmers to know the key parameters of the single systems like the average fuel consumption (energy)... |
| Tipo: Info:eu-repo/semantics/article |
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| Ano: 2015 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3140 |
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| hosseinzadeh, bahram; Esmaeili, Zahra; Rostami, Sajad; Zareiforoush, Hemad. |
| In the present study, a grading system based on fuzzy logic was developed to simulate the behavior of an expert in the evaluation and classification of physical properties of rice grains (paddy) for pricing the product. Based on two desired quality indices in this study and the input linguistic variables of fuzzy grading system, 250 samples were prepared with different quality conditions which include all the possible states for the rice grains (paddy). Lighting and imaging were carried out from each 250 samples of rice products in the same condition. Image processing algorithm was conducted to extract geometric features and light intensity of grains and also fuzzy product pricing model was developed in MATLAB software. Fuzzy inference system was designed... |
| Tipo: Info:eu-repo/semantics/article |
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| Ano: 2016 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/4022 |
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| Szesz Junior,Albino; Monteiro Junior,Marcos; Dias,Ariangelo Hauer; Mathias,Ivo Mário; Conti,Giuvane. |
| ABSTRACT: Aeration is currently the most commonly used technique to improve the drying and storage of grain, depending on temperature and water content of the grain, as of the temperature and relative humidity of the outside air. In order to monitor temperature and humidity of the grain mass, it is possible to have a network of sensors in the cells of both internal and external storage. Use of artificial intelligence through Fuzzy theory, has been used since the 60s and enables their application on various forms. Thus, it is observed that the aeration of grain in function of representing a system of controlled environment can be studied in relation to the application of this theory.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Arduino; Agriculture; Mathematical model; Fuzzy logic; Grain aeration. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016001101917 |
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| Roberto, Moscetti; Riccardo, Massantini. |
| Globalization of market entails the availability of produces regardless their production date, pursued through innovation in products and processes to obtain meat, fish and fruit vegetables with improved shelf-life, organoleptic quality, nutritional value, safety and healthiness during the whole agrofood chain. Consequently, market value of perishable commodity mainly depends on the preservation method used to guarantee food stability and thus to delay physicochemical, biochemical and microbiological spoilage. Among processing methods, drying is one of the oldest, typical, effective and viable preservation process throughout the world, which allow to prevent food spoilage and decay through moisture removal. It... |
| Tipo: Conference paper, poster, etc. |
Palavras-chave: "Organics" in general; Food systems. |
| Ano: 2017 |
URL: http://orgprints.org/34390/1/Document_8.pdf |
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| Campos, Bráulio Pizziôlo Furtado; Silva, Gilson Fernandes da; Binoti, Daniel Henrique Breda; Mendonça, Adriano Ribeiro de; Leite, Helio Garcia. |
| The objective of this study was to analyze the ability of an artificial neural network (ANN) to describe the stem profile of trees of different genera and species in different growing conditions. For comparative purposes, equations were fit, using regression analysis to describe the stem profile. For neural network as well as for the regression equations, evaluation of accuracy was based on correlation coefficient between observed and estimated diameters along the stem, square root of the mean square percentage error (RMSE) and graphical analysis. Artificial intelligence methods, especially ANN, can be effective in describing trees bole profile of different species in different growth... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Inventário florestal; Modelos de Crescimento e Produção; Estatística Inventário Florestal; Manejo Florestal; Inteligência artificial Forest inventory; Forest management; Artificial intelligence. |
| Ano: 2017 |
URL: http://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1181 |
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| Silva,Gabi Nunes; Nascimento,Moysés; Sant’Anna,Isabela de Castro; Cruz,Cosme Damião; Caixeta,Eveline Teixeira; Carneiro,Pedro Crescêncio Souza; Rosado,Renato Domiciano Silva; Pestana,Kátia Nogueira; Almeida,Dênia Pires de; Oliveira,Marciane da Silva. |
| Abstract: The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Coffea arabica; Hemileia vastatrix; Artificial intelligence; Molecular markers; Prediction. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017000300186 |
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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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| Michelon, Gabriela Karoline; de Menezes, Paulo Lopes; Júnior, Arnaldo Cândido; Bazzi, Claudio Leones; Barbosa, Marcela Marques. |
| Soybean is one of the major oleaginous, used for food and feed to processed products and also as an alternative source of biofuel. Due to its great uses that is highly valued and cultivated in the world. Therefore, this study sought to apply an artificial intelligence technique to predict soybean yield and therefore maximize production from farmlands, increase the profit of the producer and reduce environmental impacts. There were then used the support vector machine technique, to find a prediction model of soybean yield from the leaf nutrients, allowing therefore that fertilization is carried out only in necessary locations predicted as low productivity points for best support vector... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Agricultura de Precisão Inteligência Artificial; Nutrientes Foliares; Regressão. |
| Ano: 2017 |
URL: http://www.seer.ufv.br/seer/index.php/reveng/article/view/745 |
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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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| Ferreira,Mariane Gonçalves; Azevedo,Alcinei Mistico; Siman,Luhan Isaac; da Silva,Gustavo Henrique; Carneiro,Clebson dos Santos; Alves,Flávia Maria; Delazari,Fábio Teixeira; da Silva,Derly José Henriques; Nick,Carlos. |
| ABSTRACT Germplasm classification by species requires specific knowledge on/of the culture of interest. Therefore, efforts aimed at automation of this process are necessary for the efficient management of collections. Automation of germplasm classification through artificial neural networks may be a viable and less laborious strategy. The aims of this study were to verify the classification potential of Capsicum accessions regarding/ the species based on morphological descriptors and artificial neural networks, and to establish the most important descriptors and the best network architecture for this purpose. Five hundred and sixty-four plants from 47 Brazilian Capsicum accessions were evaluated. Neural networks of multilayer perceptron type were used in... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Capsicum spp.; Garson’s method; Artificial intelligence; Taxonomy; Germplasm bank. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162017000300203 |
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| Pereira,Tonismar dos S.; Robaina,Adroaldo D.; Peiter,Marcia X.; Torres,Rogerio R.; Bruning,Jhosefe. |
| ABSTRACT The aim of this study was to present and to evaluate methodologies for the estimation of soil resistance to penetration (RP) using artificial intelligence prediction techniques. In order to do so, a data base with values of physical-water characteristics of the soils available in the literature was used, and the performances of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were evaluated. The models generated from the ANNs were implemented through the multilayer perceptron with backpropagation algorithm of Matlab software, varying the number of neurons in the input and intermediate layers. For the procedure from SVM, the RapidMiner software was used, varying... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil compaction; Machine learning; Support vector machines; Artificial neural networks. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100142 |
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| Dornelles,Eldair F.; Kraisig,Adriana R.; Silva,José A. G. da; Sawicki,Sandro; Roos-Frantz,Fabricia; Carbonera,Roberto. |
| ABSTRACT Artificial intelligence may represent an efficient strategy for simulation and optimization of important processes in agriculture. The main goal of the study is to propose the use of artificial intelligence, namely artificial neural networks and genetic algorithms, respectively, in the simulation of oat grain yield and optimization of seeding density, considering the main succession systems of southern Brazil. The study was conducted in a randomized complete block design with four replicates, following a 4 x 2 factorial scheme, for seeding densities (100, 300, 600 and 900 seeds m-2) and oat cultivars (Brisasul and... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Avena sativa; Artificial neural networks; Genetic algorithms; Innovation. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000300183 |
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| mohammadigolafshani, nima; koulaian, ali. |
| Estimation of evapotranspiration (ET) is needed in water resources management, scheduling of farm irrigation, and environmental assessment. Hence, in practical hydrology, it is often crucial to reliably and constantly estimate evapotranspiration. Accordingly, 3 artificial intelligence (AI) techniques comprising adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference- wavelet (ANFIS-Wavelet) were applied in to estimate wheat crop evapotranspiration (ETc). A case study in a Dashtenaz region located in Mazandaran, Iran, was conducted with weather daily data, including maximum temperature, minimum temperature, maximum relative humidity,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Adaptive neuro-fuzzy inference system; Adaptive neuro-fuzzy inference-wavelet; Evapotranspiration; Neural network; Wheat. |
| Ano: 2018 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/4459 |
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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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| Registros recuperados: 64 | |
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