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| Registros recuperados: 17 | |
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| Mehri,M; Ghazaghi,M. |
| A uniform design (UD) was used to construct models to explain the growth response of Japanese quails to dietary metabolizable energy (ME), and digestible methionine (dMet) and lysine (dLys) under tropical condition. In total, 100 floor pens with seven birds each were fed 25 UD different diets containing 25 ME (2808-3092 kcal/kg), dMet (0.31-0.49% of diet), and dLys (0.91-1.39% of diet) levels from 7 to 14 d of age. A platform of artificial neural network based on UD (ANN-UD) was generated to describe the growth response of the birds to dietary inputs using random search. Artificial neural networks of body weight gain (BWG) and feed conversion ratio (FCR) were optimized using random search algorithm. The optimization the ANN-UD results showed that maximum... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Quail chick; Nutritional requirement; Uniform design; Neural network. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2014000300013 |
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| Aoki, I; Komatsu, T. |
| This paper examines the use of a neural network to analyse and predict the winter catch, in the Joban-Boso Seas off the Pacific coast of central Japan, of young Japanese sardine (Sardinops melanostictus) representing the index of recruits in the sardine stock. The supervised learning paradigm, a three-layer network and a back-propagation algorithm were employed in constructing the neural net. A number of biological, hydrographic and climatic factors constituted an input vector, the output being the catch of young sardine. The association of sardine abundance with environmental factors was quantified in the form of the trained neural network, which indicated important associations with the Southern Oscillation Index, with patterns of the Kuroshio and the... |
| Tipo: Text |
Palavras-chave: Neural network; Japanese sardine; Recruit; Climatic change; Kuroshio-Oyashio. |
| Ano: 1997 |
URL: http://archimer.ifremer.fr/doc/00093/20436/18103.pdf |
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| Jaksic,Damjan; Lilic,Ljubisa; Popovic,Stevo; Matic,Radenko; Molnar,Slavko. |
| It is well known that the most evident differences in humans are those related to anthropometric characteristics, and that during continuous monitoring the relation between human behavior and human abilities concerning their anthropometric characteristics was observed. The aim of this study was to detect and define the morphological types with the use of slightly different and more advanced methodologies. The sample included 149 male subjects, first-year students of the Faculty of Sport and Physical Education in Novi Sad, using an anthropometric measurement technique. A total of 12 anthropometric measures, defined according to the four-dimensional morphological model was used. For all variables, basic descriptive statistics were calculated while student... |
| Tipo: Journal article |
Palavras-chave: Neural network; Intruder; Students; Anthropometry; Somatotypology. |
| Ano: 2014 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022014000100019 |
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| Sauzede, Raphaelle; Claustre, Hervé; Bittig, Henry; Pasqueron De Fommervault, Orens; Gattuso, Jean-pierre; Legendre, Louis; Johnson, Kenneth S. |
| A neural network-based method (CANYON: CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network) was developed to estimate water-column biogeochemically relevant variables in the Global Ocean. These are the concentrations of 3 nutrients [nitrate (NO3−), phosphate (PO43−) and silicate (Si(OH)4)] and 4 carbonate system parameters [total alkalinity (AT), dissolved inorganic carbon (CT), pH (pHT) and partial pressure of CO2 (pCO2)], which are estimated from concurrent in situ measurements of temperature, salinity, hydrostatic pressure and oxygen (O2) together with sampling latitude, longitude and date. Seven neural-networks were developed using the GLODAPv2 database, which is largely representative of the... |
| Tipo: Text |
Palavras-chave: Neural network; Nutrients; Carbonate system; Global ocean; GLODAPv2 database; Profiling floats. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00383/49467/49952.pdf |
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| Guo, Qiang; Luo, Chang-shou; Wei, Qing-feng. |
| Considering the complexity of vegetables price forecast, the prediction model of vegetables price was set up by applying the neural network based on genetic algorithm by using the characteristics of genetic algorithm and neural work. Taking mushrooms as an example, the parameters of the model are analyzed through experiment. In the end, the results of genetic algorithm and BP neural network are compared. The results show that the absolute error of prediction data is in the scale of 10%; in the scope that the absolute error in the prediction data is in the scope of 20% and 15%. The accuracy of genetic algorithm based on neutral network is higher than the BP neutral network model, especially the absolute error of prediction data is within the scope of 20%.... |
| Tipo: Journal Article |
Palavras-chave: Genetic algorithm; Neural network; Vegetables price; Prediction; China; Agribusiness. |
| Ano: 2011 |
URL: http://purl.umn.edu/117430 |
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| Sarmento,Eliana Casco; Giasson,Elvio; Weber,Eliseu; Flores,Carlos Alberto; Hasenack,Heinrich. |
| The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Appellation of origin; Decision tree; Digital elevation model; Geographic information systems; Neural network; Soil mapping. |
| Ano: 2012 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2012000900025 |
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| Landschuetzer, P.; Gruber, N.; Bakker, D. C. E.; Schuster, U.. |
| We present a new observation-based estimate of the global oceanic carbon dioxide (CO2) sink and its temporal variation on a monthly basis from 1998 through 2011 and at a spatial resolution of 1 degrees x1 degrees. This sink estimate rests upon a neural network-based mapping of global surface ocean observations of the partial pressure of CO2 (pCO(2)) from the Surface Ocean CO2 Atlas database. The resulting pCO(2) has small biases when evaluated against independent observations in the different ocean basins, but larger randomly distributed differences exist particularly in high latitudes. The seasonal climatology of our neural network-based product agrees overall well with the Takahashi et al. (2009) climatology, although our product produces a stronger... |
| Tipo: Text |
Palavras-chave: Sea surface pCO(2); Neural network; Air-sea exchange of CO2; Ocean carbon cycle; Observations. |
| Ano: 2014 |
URL: https://archimer.ifremer.fr/doc/00292/40345/38920.pdf |
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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, minimum relative humidity, wind speed, and solar radiation since... |
| 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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| Registros recuperados: 17 | |
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