Neural Network
Mostrando 1-12 de 875 artigos, teses e dissertações.
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1. Identifying olive oil fraud and adulteration using machine learning algorithms
As olive oil (OO) is more expensive than other vegetable oils, it is usually adulterated by blending it with more economic edible oils such as cottonseed oil (CSO), canola oil (CO), and soybean oil (SO). This research aimed to determine the fatty acid compositions obtained as a result of blending different proportions of CSO, CO and SO with OO using a gas ch
Química Nova. Publicado em: 2022
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2. 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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3. Long Term Meteorological Drought Forecasting for North-western Region of Bangladesh Using Wavelet Artificial Neural Network
Resumo A seca meteorológica é um evento atmosférico temporário e recorrente, originado pela falta de precipitação por um período considerável em uma determinada área. A parte noroeste de Bangladesh enfrenta anomalias de precipitação que podem se transformar em seca meteorológica e, por isso, é necessário investigar a confirmação do surgimento
Revista Brasileira de Meteorologia. Publicado em: 2022
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4. Mathematical Modeling of the Film Influence on the Salting Time of Mozzarella Cheese in a Static and Dynamic System: Application of Artificial Neural Networks of the Multilayer Perceptron Type
The NaCl and KCl diffusion in the film formed on the cheese surface during salting was simulated by the finite element method. The time and salts concentration values on the cheese surface were determined, tabulated, and presented to the multilayer perceptron neural network (MLP) for the regression modeling. The samples were divided into 70, 15 and 15% for t
Journal of the Brazilian Chemical Society. Publicado em: 2022
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5. THE INFLUENCE OF THE FILM FORMED ON THE PRATO CHEESE SURFACE DURING THE NACL AND KCL SALTING PROCESS: APPLICATION OF THE FINITE ELEMENT METHOD AND NEURAL NETWORKS OF THE SELF-ORGANIZING MAP (SOM) AND MULTILAYER PERCEPTRON (MLP) TYPES
Sodium chloride is used in the cheese salting process as it promotes sensory changes and food preservation. However, in excess can cause hypertension problems, and for this reason, it has been partially replaced by potassium chloride. In the present work, Prato cheese was subjected to joint diffusion of NaCl and KCl by immersion in static and stirred brine.
Química Nova. Publicado em: 2022
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6. APLICAÇÃO DA REDE NEURAL DE RETROPROPAGAÇÃO EM INDICADORES DE FADIGA ESPORTIVA
RESUMO Introdução O treinamento de reabilitação de alta intensidade produzirá fadiga ao exercício. Objetivo Um algoritmo neural de backpropagation network (BP) é proposto para prever a fadiga esportiva com base em imagens de sinais de eletromiografia (EMG). Métodos O algoritmo de análise de componente principal é usado para reduzir a dimensã
Rev Bras Med Esporte. Publicado em: 2021-09
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7. 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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8. ARTIFICIAL NEURAL NETWORK-BASED METHOD TO IDENTIFY FIVE VARIETIES OF EGYPTIAN FABA BEAN ACCORDING TO SEED MORPHOLOGICAL FEATURES
ABSTRACT One of the new crop varieties that have been adopted for high yield is the Egyptian faba bean. However, poor-quality faba bean has reduced economic value. Quality evaluation is thus important and can be performed using computational intelligence. We developed a robust method based on morphological features and artificial neural network for quality g
Eng. Agríc.. Publicado em: 2020-12
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9. 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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10. 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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11. Open stope stability assessment through artificial intelligence
Abstract Underground mining is a set of methods that allows the extraction of ore in depth, ensuring sustainability and economic viability. One of the problems that arise in underground mine operations is open stope stability. The method for assessing stabil ity of open stopes is the stability graph proposed by Mathews et al. (1981). It is possible to estima
REM, Int. Eng. J.. Publicado em: 2020-09
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12. 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