Neural Network Architecture
Mostrando 1-12 de 62 artigos, teses e dissertações.
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1. Discrimination of pores and cracks in iron ore pellets using deep learning neural networks
Abstract The discrimination between pores and cracks is an important step in the microstructural analysis of iron ore pellets. While the porosity is fundamental during the reduction process in blast furnaces, cracks are strongly detrimental to the mechanical strength. The usual image processing tools cannot automatically discriminate between these two types
REM, Int. Eng. J.. Publicado em: 2020-06
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2. Preliminary investigation of Terahertz spectroscopy to predict pork freshness non-destructively
Abstract Freshness, a very important criterion for pork quality control, is normally assessed by the index of K value. In this paper, Terahertz (THz) spectroscopy was employed to predict K value of pork nondestructively. The THz spectra (0.2~2.0THz) of 80 pork samples with different freshness in the attenuated total reflectance (ATR) mode were acquired. Simu
Food Sci. Technol. Publicado em: 22/07/2019
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3. Predicting breeding value of body weight at 6-month age using Artificial Neural Networks in Kermani sheep breed
ABSTRACT. The present study aimed to apply artificial neural networks to predict the breeding values of body weight in 6-month age of Kermani sheep. For this purpose, records of 867 lambs including lamb sex, dam age, birth weight, weaning weight, age at 3-month (3 months old), age at 6-month (6 months old) and body weight at 3 months of age were used. Firstl
Acta Sci., Anim. Sci.. Publicado em: 04/07/2019
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4. Automation in accession classification of Brazilian Capsicum germplasm through artificial neural networks
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
Sci. agric. (Piracicaba, Braz.). Publicado em: 2017-06
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5. Estimation of fatigue lives of fly ash modified dense bituminous mixtures based on artificial neural networks
This study deals with estimation of fatigue lives of bituminous mixtures using artificial neural networks. Different types of fly ash were used as filler replacing agents in a dense bituminous mixture. Fatigue tests were performed using repeated load indirect tensile test apparatus under controlled stress conditions. For determination of fatigue life, the in
Mat. Res.. Publicado em: 01/04/2014
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6. Editorial
The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output
Food Sci. Technol. Publicado em: 2013-12
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7. Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks
This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series,
Quím. Nova. Publicado em: 2013
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8. Uma arquitetura híbrida aplicada em problemas de aprendizagem por reforço / A hybrid architecture to address reinforcement learning problems
With the evergrowing use of cognitive systems in various applications, it has been created a high expectation and a large demand for machines more and more autonomous, intelligent and creative in real world problem solving. In several cases, the challenges ask for high adaptive and learning capability. This work deals with the concepts of reinforcement learn
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 07/02/2012
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9. An hybrid architecture for clusters analysis: rough setstheory and self-organizing map artificial neural network
The database of real world contains a huge volume of data and among them there are hidden piles of interesting relations that are actually very hard to find out. The knowledge discovery in databases (KDD) appears as a possible solution to find out such relations aiming at converting information into knowledge. However, not all data presented in the bases are
Pesquisa Operacional. Publicado em: 08/03/2012
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10. Um algoritmo de aprendizado por reforço para redes neurais utilizando metaotimização estatística / A reinforcement learning algorithm for neural networks using statistical meta optimization
Esse trabalho analisa as principais técnicas de treinamento de redes neurais para problemas de aprendizado por reforço, e finalmente propõe um novo modelo utilizando suas melhores características, além de metaotimização baseada em amostragem estatística. O estudo tem por objetivos a obtenção de um método com alta taxa de sucesso, baixo número de
Publicado em: 2011
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11. Modelagem matemática na previsão de colheita de bananeira: regressão linear múltipla x redes neurais artificiais / Mathematical modeling to predict crop of banana: multiple regression x neural networks
One of the barriers relevant to the banana crop in Brazil is the lack of productive commercial varieties with adequate size, resistant to major pests and diseases and adapted to different ecosystems. The development of cultivars is the strategy for solving this problem through breeding programs, as well as its characterization and evaluation in areas of prod
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 07/12/2010
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12. A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened steel turning
The use of artificial neural networks for prediction in hard turning has received considerable attention in literature. An often quoted drawback of ANNs is the lack of a systematic way for the design of high performance networks. This study presents a DOE based approach for the design of ANNs of Radial Basis Function (RBF) architecture applied to surface rou
Journal of the Brazilian Society of Mechanical Sciences and Engineering. Publicado em: 2010-12