Neural Network Model
Mostrando 1-12 de 290 artigos, teses e dissertações.
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1. ADDITION OF NATURAL EXTRACTS WITH ANTIOXIDANT PROPERTIES IN BIODIESEL: ANALYSIS BY NEURAL NETWORKS OF THE MULTILAYER PERCEPTRON TYPE
Biodiesel is capable of replacing diesel because it has similar physicochemical properties, but this biofuel is susceptible to oxidation, which makes the application of antioxidant substances necessary. For this study, alcoholic extracts of senna leaves, hibiscus flowers, and blackberry were used. Biodiesel samples were submitted to physicochemical analysis
Química Nova. Publicado em: 2022
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2. FUZZY MODELING OF THE EFFECTS OF DIFFERENT IRRIGATION DEPTH IN RADISH CROP. PART II: BIOMETRIC VARIABLES ANALYSIS
ABSTRACT In order to estimate the response of biometric variables in different irrigation depths in radish crop, as well as their relations in the development of the crop, a fuzzy mathematical analysis was carried out from irrigation with depths of different percentages of the crop evapotranspiration (ETc), using Gaussian pertinence functions for the input v
Eng. Agríc.. Publicado em: 2021-05
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3. PREDICTING THE PERFORMANCE PARAMETERS OF CHISEL PLOW USING NEURAL NETWORK MODEL
ABSTRACT This study examines the capability of an artificial neural network (ANN) approach using a backpropagation-learning algorithm to predict performance parameters for a chisel plow at three field sites with differing soils. The draft force, effective field capacity (EFC), fuel consumption rate (FC), overall energy efficiency (OEE), and rate of plowed so
Eng. Agríc.. Publicado em: 2020-12
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4. Forecasting mass and metallurgical balance at a gold processing plant using modern multivariate statistics
Abstract Knowing the quantity and the quality of products and tailings generated by a beneficiation plant, even before ore processing, can make the mining operations more sustainable, more profitable, and safer. To forecast these values, it is necessary to submit samples to batch tests which mimic the processing workflow used on an industrial scale. Then, th
REM, Int. Eng. J.. Publicado em: 2020-12
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5. Hopfield Neural Network-Based Algorithm Applied to Differential Scanning Calorimetry Data for Kinetic Studies in Polymorphic Conversion
A general kinetic equation to simulate differential scanning calorimetry (DSC) data was employed along this work. Random noises are used to generate a thousand data, which are considered to evaluate the performance of Levenberg-Marquardt (LM) and a Hopfield neural network (HNN) based algorithm in the fitting process. The HNN-based algorithm showed better res
J. Braz. Chem. Soc.. Publicado em: 2020-07
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6. EVALUATION OF MECHANICAL AND FLAME RETARDANT PROPERTIES OF MEDIUM DENSITY FIBERBOARD USING ARTIFICIAL NEURAL NETWORK
ABSTRACT The present study presents the application of artificial neural network (ANN) to predict the modulus of rupture (MOR) and mass loss (ML) of the fire retarded fiberboard. Hence, the effect of adding the fire retardants including boric acid, borax and ammonium sulfate was evaluated on MOR and ML of fiberboard manufactured at different press temperatur
CERNE. Publicado em: 2020-06
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7. Enurese noturna: uma condição comórbida,
ABSTRACT The present study presents the application of artificial neural network (ANN) to predict the modulus of rupture (MOR) and mass loss (ML) of the fire retarded fiberboard. Hence, the effect of adding the fire retardants including boric acid, borax and ammonium sulfate was evaluated on MOR and ML of fiberboard manufactured at different press temperatur
J. Pediatr. (Rio J.). Publicado em: 2020-06
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8. Kinetics of Lumefantrine Thermal Decomposition Employing Isoconversional Models and Artificial Neural Network
Thermal analysis can be used to determine shelf-life and kinetic parameters in pharmaceutical systems. This work investigates the kinetic of lumefantrine thermal decomposition, an antimalarial, using non-isothermal and isothermal experimental data. The non-isothermal conditions are analyzed applying Vyazovkin method, while isothermal conditions employ models
J. Braz. Chem. Soc.. Publicado em: 2020-03
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9. Transverse Load Discrimination in Long-Period Fiber Grating via Artificial Neural Network
Abstract We present a general investigation of a Long-Period Grating (LPG) for transverse strain measurement. The transverse strain sensing characteristics, for instance, the load intensity and azimuthal angle, are analyzed with the data set generated by the LPG sensor and probed by artificial neural network (ANN). Furthermore, we evaluate and compare the pr
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2020-03
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10. MULTILEVEL NONLINEAR MIXED-EFFECTS MODEL AND MACHINE LEARNING FOR PREDICTING THE VOLUME OF Eucalyptus SPP. TREES
ABSTRACT Volumetric equations is one of the main tools for quantifying forest stand production, and is the basis for sustainable management of forest plantations. This study aimed to assess the quality of the volumetric estimation of Eucalyptus spp. trees using a mixed-effects model, artificial neural network (ANN) and support-vector machine (SVM). The datab
CERNE. Publicado em: 2020-03
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11. Prediction of restrained shrinkage crack width of slag mortar composites using data mining techniques
ABSTRACT The purpose of this study is to develop data mining models to predict restrained shrinkage crack widths of slag mortar cementitious composites. A database published by BILIR et al. [1] was used to develop these models. As a modelling tool R environment was used to apply these data mining (DM) techniques. Several algorithms were tested and analyzed u
Matéria (Rio J.). Publicado em: 25/11/2019
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12. Strain-deformation Reconstruction of Carbon Fiber Composite Laminates Based on BP Neural Network
The Carbon Fiber Reinforced Polymer (CFRP) laminate structural components used in the aerospace and military domains require high precision and strong stability. Usually the deformation of these structural components is difficult to be measured directly during operation, but the deformation of the CFRP laminate structure can be reconstructed with strain info
Mat. Res.. Publicado em: 14/11/2019