Back Propagation
Mostrando 13-24 de 108 artigos, teses e dissertações.
-
13. DOSIS DEL NITRÓGENO EN EL ABONADO DE MINIJARDIN CLONAL DE PITANGUERAS (Eugenia uniflora)
ABSTRACT The minicutting is an effective and quick method of vegetative propagation, dedicated to spread of forest and fruit trees, providing the formation of homogeneous orchards. In order to determine the adubation management in multiplication of Surinam cherry trees by minicutting in clonal gardens, we tested increased nitrogen (N) doses in fertilizer fo
Rev. Bras. Frutic.. Publicado em: 29/09/2016
-
14. Influence of Fiber Properties on Shear Failure of Steel Fiber Reinforced Beams Without Web Reinforcement: ANN Modeling
Abstract In this paper, an artificial neural network (ANN-10) model was developed to predict the ultimate shear strength of steel fiber reinforced concrete (SFRC) beams without web reinforcement. ANN-10 is a four-layered feed forward network with a back propagation training algorithm. The experimental data of 70 SFRC beams reported in the technical literatur
Lat. Am. j. solids struct.. Publicado em: 2016-08
-
15. Digital soil mapping using reference area and artificial neural networks
ABSTRACT Digital soil mapping is an alternative for the recognition of soil classes in areas where pedological surveys are not available. The main aim of this study was to obtain a digital soil map using artificial neural networks (ANN) and environmental variables that express soil-landscape relationships. This study was carried out in an area of 11,072 ha l
Sci. agric. (Piracicaba, Braz.). Publicado em: 2016-06
-
16. Modelling the Hot Flow Behaviors of AZ80 Alloy by BP-ANN and the Applications in Accuracy Improvement of Computations
Hot compressions of as-cast AZ80 magnesium alloy in a wide temperature range of 523-673 K and strain rate range of 0.01-10 s–1 with a height reduction of 60% were conducted by a Gleeble-1500 thermo-mechanical test simulator. The hot flow behaviors show highly non-linear intrinsic relationships with temperature, strain and strain rate. In order to model the
Mat. Res.. Publicado em: 03/11/2015
-
17. PRELIMINARY MODELING OF AN INDUSTRIAL RECOMBINANT HUMAN ERYTHROPOIETIN PURIFICATION PROCESS BY ARTIFICIAL NEURAL NETWORKS
Abstract In the present study a preliminary neural network modelling to improve our understanding of Recombinant Human Erythropoietin purification process in a plant was explored. A three layer feed-forward back propagation neural network was constructed for predicting the efficiency of the purification section comprising four chromatographic steps as a func
Braz. J. Chem. Eng.. Publicado em: 2015-09
-
18. The Prediction of the Man-Hour in Aircraft Assembly Based on Support Vector Machine Particle Swarm Optimization
ABSTRACT: As the representative of manufacturing industry, aircraft assembly lacks of effective method to forecast man-hour. The forecasting accuracy of existing methods is universally pretty low. On the basis of full analysis of aircraft assembly's feature, this study proposes a forecasting model based on support vector machine (SVM), which is optimized by
J. Aerosp. Technol. Manag.. Publicado em: 2015-03
-
19. Neural networks for predicting breeding values and genetic gains
Analysis using Artificial Neural Networks has been described as an approach in the decision-making process that, although incipient, has been reported as presenting high potential for use in animal and plant breeding. In this study, we introduce the procedure of using the expanded data set for training the network. Wealso proposed using statistical parameter
Sci. agric. (Piracicaba, Braz.). Publicado em: 2014-12
-
20. A characterization for the constitutive relationships of 42CrMo high strength steel by Artificial Neural Network and its application in isothermal deformation
In hot working process, the prediction of material constitutive relationship can improve the optimization design process. Recently, the artificial neural network models are considered as a powerful tool to describe the elevated temperature deformation behavior of materials. Based on the experimental data from the isothermal compressions of 42CrMo high streng
Mat. Res.. Publicado em: 05/08/2014
-
21. Nonlinear effects compensation in Optical Coherent PDM-QPSK Systems
Nonlinear effects has been appointed as the main limitation in coherent optical fiber transmission. Digital Back-Propagation algorithms and Maximum Likelihood Sequence Estimation are two of the current studied methods to cope with such impairment and extend the systems maximum reach. In this article, we analyzed both methods in a 112 Gb/s Dual Polarization Q
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2013-12
-
22. 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
-
23. Predição recursiva de diâmetros de clones de eucalipto utilizando rede Perceptron de múltiplas camadas para o cálculo de volume
O volume de madeira plantado é uma informação essencial no direcionamento racional e sustentável dos recursos disponíveis nas florestas. Assim, é muito importante quantificá-lo da forma mais precisa possível. A atividade da Engenharia Florestal que trata da quantificação de madeira nas florestas é o Inventário Florestal. Este inventário é a bas
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 13/04/2012
-
24. Introducing a new formula based on an artificial neural network for prediction of droplet size in venturi scrubbers
Droplet size is a fundamental parameter for Venturi scrubber performance. For many years, the correlations proposed by Nukiyama and Tanasawa (1938) and Boll et al. (1974) were used for calculating mean droplet size in Venturi scrubbers with limited operating parameters. This study proposes an alternative approach on the basis of artificial neural networks (A
Braz. J. Chem. Eng.. Publicado em: 2012-09