Optimization Of Artificial Neural Networks
Mostrando 1-12 de 52 artigos, teses e dissertações.
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1. ARTIFICIAL NEURAL NETWORKS APPLIED IN FOREST BIOMETRICS AND MODELING: STATE OF THE ART (JANUARY/2007 TO JULY/2018)
ABSTRACT Artificial Intelligence has been an important support tool in different spheres of activity, enabling knowledge aggregation, process optimization and the application of methodologies capable of solving complex real problems. Despite focusing on a wide range of successful metrics, the Artificial Neural Network (ANN) approach, a technique similar to t
CERNE. Publicado em: 09/09/2019
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2. COMPARISON OF RESPONSE SURFACE METHODOLOGY (RSM) AND ARTIFICIAL NEURAL NETWORKS (ANN) TOWARDS EFFICIENT OPTIMIZATION OF FLEXURAL PROPERTIES OF GYPSUM-BONDED FIBERBOARDS
ABSTRACT In this study, the hydration behavior of gypsum paste mixed with bagasse and kenaf fibers as lignocellulosic material and fiberglass as inorganic material is evaluated. Moreover, the properties of gypsum-bonded fiberboard (GBFB) are examined using bagasse fibers (Saccharum officinarum.L), kenaf fibers (Hibiscus cannabinus.L) and industrial fiberglas
CERNE. Publicado em: 2018-03
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3. MODELADO DE PARTÍCULAS PM10 Y PM2.5 MEDIANTE REDES NEURONALES ARTIFICIALES SOBRE CLIMA TROPICAL DE SAN FRANCISCO DE CAMPECHE, MÉXICO
In this paper, a computational methodology based on Artificial Neural Networks (ANN) was developed to estimate the index of PM10 and PM2.5 concentration in air of San Francisco de Campeche city. A three layer ANN architecture was trained using an experimental database composed by days of the week, time of day, ambient temperature, atmospheric pressure, wind
Quím. Nova. Publicado em: 2017-09
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4. Use of an Artificial Neural Network in determination of iron ore pellet bed permeability
Abstract The thermal processing of iron ore pellets in pelletizing plants is a decisive stage regarding final product quality and knowledge of its characteristics has a fundamental importance in its process optimization. This study evaluated the variable sensitivity involved in pellet bed formations and their permeability using the artificial neural networks
REM, Int. Eng. J.. Publicado em: 2017-06
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5. MACHINE LEARNING TECHNIQUES APPLIED TO LIGNOCELLULOSIC ETHANOL IN SIMULTANEOUS HYDROLYSIS AND FERMENTATION
Abstract This paper investigates the use of machine learning (ML) techniques to study the effect of different process conditions on ethanol production from lignocellulosic sugarcane bagasse biomass using S. cerevisiae in a simultaneous hydrolysis and fermentation (SHF) process. The effects of temperature, enzyme concentration, biomass load, inoculum size and
Braz. J. Chem. Eng.. Publicado em: 2017-01
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6. A hybrid model of uniform design and artificial neural network for the optimization of dietary metabolizable energy, digestible lysine, and methionine in quail chicks
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), a
Rev. Bras. Cienc. Avic.. Publicado em: 2014-09
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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. Estimação e previsão da estrutura a termo das taxas de juros usando técnicas de inteligência computacional / Term structure of interest rate modeling and forecasting using computational intelligence techniques
This work proposes the term structure of interest rates modeling and forecasting using computational intelligence techniques, based on data from the US and Brazilian fixed income markets. The yield curve modeling includes the use of some evolutionary computation methods like Genetic Algorithms, Differential Evolution and Evolution Strategies in comparison wi
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 25/06/2012
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9. Otimização e dinâmica dos fluidos computacional aplicadas a turbinas eólicas
The present work consists in the application of optimization methods and computational fluid dynamics to wind turbines. The massive growth in renewable energies demands more powerful turbines and more accuracy in their design and analysis. This work has three objectives: optimization of an airfoil for wind turbines, simulation of a wind turbine airfoil in de
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 2012
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10. Otimização multidisciplinar em projeto de asas flexíveis utilizando metamodelos / Multidisciplinary design optimization of flexible wings using metamodels
A Otimização Multidisciplinar em Projeto (em inglês, Multidisciplinary Design Optimization - MDO) é uma ferramenta de projeto importante e versátil e seu uso está se expandindo em diversos campos da engenharia. O foco desta metodologia é unir disciplinas envolvidas no projeto para que trabalhem suas variáveis concomitantemente em um ambiente de otimi
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 11/08/2011
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11. Busca heurística e inferência de parâmetros cinéticos de reações de hidrotratamento de óleo diesel a partir de dados experimentais escassos
Currently, the amount of contaminants (such as sulfur, nitrogen and aromatics) in diesel oil is strictly controlled, due to their impact on pollutant emissions. The most important process used to meet fuel specifications regarding contaminants is the catalytic hydrogenation, specifically hydrotreatment (HDT). Optimization of the HDT process can benefit from
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 30/06/2011
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12. GENETIC-NEURAL MODEL FOR PORTFOLIO OPTIMIZATION WITH FINANCIAL OPTIONS IN THE BRAZILIAN MARKET / MODELO GENÉTICO-NEURAL PARA OTIMIZAÇÃO DE CARTEIRAS COM OPÇÕES FINANCEIRAS NO MERCADO BRASILEIRO
This dissertation develops an intelligent, quantitative and probabilistic model to determine an optimal composition of a portfolio consisting of a financial asset and options over this asset. Initially we studied the characteristics of the historical distribution of returns and volatility of the most liquid stocks from the BOVESPA Stock Exchange, from Januar
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 08/02/2011