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Palavra-chave Neural network (17) Evapotranspiration (2) Adaptive neuro-fuzzy inference system (1) Adaptive neuro-fuzzy inference-wavelet (1) Agribusiness (1) Air flow (1) Air-sea exchange of CO2 (1) Anthropometry (1) Appellation of origin (1) Bites and stings (1) Broiler (1) CO2 (1) Carbonate system (1) China (1) Classification (1) Climatic change (1) Decision tree (1) Digital Watermarking (1) Digital elevation model (1) Discrete Wavelet Transform (1) Mais... Tipo do documento Info:eu-repo/semantics/article (9) Text (4) Journal article (2) Journal Article (1) Ano 2018 (2) 2017 (3) 2016 (1) 2015 (1) 2014 (3) 2012 (2) 2011 (2) 2007 (1) 2004 (1) 1997 (1) Mais... País Brazil (7) France (4) Chile (2) China (2) Mexico (1) United States (1) Mais... Idioma Inglês (16) Espanhol (1)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 17 Primeira ... 1 ... Última Utilization of new computational intelligence methods to estimate daily Evapotranspiration of wheat using Gamma pre processing 111 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 Comparative study of acoustic signals of rolling eggs on inclined plate and impulse response in eggshell crack detection 111 Lashgari, Majid; Mohammadigol, Reza. The potential of acoustic signals of rolling eggs on an inclined plate and impulse response for nondestructive detection of eggshell crack was investigated. Discrimination of hairline cracked and star cracked eggs from intact ones were carried out using artificial neural network. Ten features were used based on one-way ANOVA F-test statistics. According to the result, holdout detection accuracy of inclined plate and impulse response methods were 92.3% and 94.6%, respectively. The results indicated that these two methods were potentially useful for discrimination of eggs according to detection of different eggshell cracks. Tipo: Info:eu-repo/semantics/article Palavras-chave: Eggshell crack; Inclined plate; Impulse response; Neural network; Classification. Ano: 2018 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/4140 Hybrid Geoid Model: Theory and Application in Brazil 42 ARANA,DANIEL; CAMARGO,PAULO O.; GUIMARÃES,GABRIEL N.. Determination of the ellipsoidal height by Global Navigation Satellite Systems (GNSS) is becoming better known and used for purposes of leveling with the aid of geoid models. However, the disadvantage of this method is the quality of the geoid models, which degrade heights and limit the application of the method. In order to provide better quality in transforming height using GNSS leveling, this research aims to develop a hybridization methodology of gravimetric geoid models EGM08, MAPGEO2015 and GEOIDSP2014 for the State of São Paulo, providing more consistent models with GNSS technology. Radial Basis Function (RBF) neural networks were used to obtain the corrector surface, based on differences between geoid model undulations and the undulations obtained... Tipo: Info:eu-repo/semantics/article Palavras-chave: EGM08; GEOIDSP2014; GNSS leveling; MAPGEO2015; Neural network. Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000401943 An Efficient Watermarking Scheme for Medical Data Security With the Aid of Neural Network 52 Kalaivani,K.. ABSTRACT Digital watermarking has emerged as major technique for ensuring security for various types of data like medical data, digital copyright protection, transaction tracing and so on. With the advancement in digital data distribution over the network there has been increase in the need for protection of such data from unauthorized copying or usages. Watermarking helps in providing the security to some extent. Robustness against any sort of unauthenticated attack is the major requirement of watermarking. In this paper we proposed an efficient watermarking technique for medical data security with the aid of neural network. Usage of neural network is generally used to create and control watermarking strength automatically. This method provides better... Tipo: Info:eu-repo/semantics/article Palavras-chave: Digital Watermarking; Medical data security; HVS Model; Discrete Wavelet Transform; Neural network. Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132016000300406 Máquinas de soporte vectorial en el análisis de series de tiempo. 32 Rivera Castillo, Enrique. La evapotranspiración de referencia (ETo) es un proceso no lineal empleado para determinar la cantidad de agua utilizada en los programas de irrigación. El nivel de precisión de esta variable a partir de datos históricos, ha sido siempre fundamental. En este trabajo, se presenta una aplicación de las Máquinas de Soporte Vectorial (SVMs) para la predicción de ETo y se compara su capacidad predictiva con otras dos metodologías de predicción: Redes Neuronales Artificiales de Multicapa (MLP) y modelos Autoregresivos Integrados de Promedio Móvil (ARIMA). Se propone un algoritmo heurístico de refinamiento para la implementación de las SVM resultando en una predicción mucho mejor que la obtenida con los otros dos métodos. La capacidad de predicción fue evaluada... Palavras-chave: Evapotranspiración; Red neuronal; Predicción; Máquina de soporte vectorial; Evapotranspiration; Neural network; Forecasting; Support vector machine; Estadística; Maestría. Ano: 2012 URL: http://hdl.handle.net/10521/1693 EVATUATION SYSTEM OF EXHAUST FANS USED ON VENTILATION SYSTEM IN COMMERCIAL BROILER HOUSE 70 Silva,Wagner; Moura,Daniella; Carvalho-Curi,Thayla; Seber,Rogério; Massari,Juliana. ABSTRACT: This study aim to develop a system, called FANS-N, for evaluation the exhaust fans in the ventilation system of broiler facilities. The system is divided into: 1) Mechanical Structure - consisting of two stepper motors for positioning a anemometer sensor in the vertical and horizontal coordinates; 2) Electronic Interface - control of the anemometer positioning and record data of wind speed; 3) Control Programming Module – accountable for the cursor movement, measurement and record the wind speed data with the anemometer at predetermined points; and 4) Analysis Programming Module - responsible for the interpretation of wind speed values at each point. The software uses artificial neural networks (Multi-Layer Perceptron) for images analyses of data... Tipo: Info:eu-repo/semantics/article Palavras-chave: Broiler; Neural network; Ventilation systems; Air flow. Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000500887 SINGLE-PASS SEA/ICE DISCRIMINATION USING ERS-2 SCATTEROMETER DATA 72 Neyt,Xavier; Pettiaux,Pauline; Manise,Nicolas; Acheroy,Marc. This paper presents a new method to perform sea/ice discrimination in single-pass ERS-2 scatterometer data. Existing methods are 1rst reviewed and compared in a consistent framework. Next, the ice probability according to the individual existing methods is learned through the use of a neural network. Finally, the individual criteria are combined together in order to increase the sea-ice discrimination accuracy. The proposed method is shown to provide an acceptable performance even on single-pass data, i.e., without requiring temporal averaging Tipo: Journal article Palavras-chave: Scatterometry; Ice discrimination; Neural network. Ano: 2004 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-65382004000300021 Rules extraction from neural networks applied to the prediction and recognition of prokaryotic promoters 74 Silva,Scheila de Avila e; Gerhardt,Günther J.L.; Echeverrigaray,Sergio. Promoters are DNA sequences located upstream of the gene region and play a central role in gene expression. Computational techniques show good accuracy in gene prediction but are less successful in predicting promoters, primarily because of the high number of false positives that reflect characteristics of the promoter sequences. Many machine learning methods have been used to address this issue. Neural Networks (NN) have been successfully used in this field because of their ability to recognize imprecise and incomplete patterns characteristic of promoter sequences. In this paper, NN was used to predict and recognize promoter sequences in two data sets: (i) one based on nucleotide sequence information and (ii) another based on stability sequence... Tipo: Info:eu-repo/semantics/article Palavras-chave: Neural network; Promoter; Rule extraction. Ano: 2011 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572011000200031 Analysis and prediction of the fluctuation of sardine abundance using a neural network 5 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 Estimates of Water-Column Nutrient Concentrations and Carbonate System Parameters in the Global Ocean: A Novel Approach Based on Neural Networks 5 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 Surface ocean CO2 in 1990–2011 modelled using a feed-forward neural network 5 Zeng, Jiye; Nojiri, Yukihiro; Nakaoka, Shin-ichiro; Nakajima, Hideaki; Shirai, Tomoko. This dataset includes the monthly distributions of CO2 fugacity in the world surface oceans reconstructed using a feed-forward neural network model and the CO2 measurements of the Surface Ocean CO2 Atlas version 2.0. It has a spatial resolution of 1 9 1° and spans a period of 22 years, from January 1990 to December 2011. The dataset also includes necessary parameters for the reconstruction and an estimate of the CO2 fluxes between the ocean and the atmosphere. The aim of this work is to provide a dataset for estimating the oceans’ contribution to the global carbon budget. Tipo: Text Palavras-chave: Ocean; CO2; Neural network; Model. Ano: 2015 URL: https://archimer.ifremer.fr/doc/00293/40400/38957.pdf Recent variability of the global ocean carbon sink 5 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 Application of a More Advanced Procedure in Defining Morphological Types 77 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 Neural network-based species identification in venom-interacted cases in India 80 Maheshwari,R.; Kumar,V.; Verma,H. K.. India is home to a number of venomous species. Every year in harvesting season, a large number of productive citizens are envenomed by such species. For efficient medical management of the victims, identification of the aggressor species as well as assessment of the envenomation degree is necessary. Species identification is generally based on the visual description by the victim or a witness and is therefore quite likely to be erroneous. Symptomatic identification remains the only available method. In a previous published work, the authors proposed a classification table for snake species based on manifested symptoms applicable in Indian subcontinent. The classification table serves the purpose to a great deal but as a manual method it demands human... Tipo: Info:eu-repo/semantics/article Palavras-chave: Bites and stings; Symptoms; Species identification; Neural network. Ano: 2007 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1678-91992007000400008 Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density 86 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 Prediction and Research on Vegetable Price Based on Genetic Algorithm and Neural Network Model 31 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 A hybrid model of uniform design and artificial neural network for the optimization of dietary metabolizable energy, digestible lysine, and methionine in quail chicks 89 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 Registros recuperados: 17 Primeira ... 1 ... Última

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