Artificial Neural Network Ann
Mostrando 1-12 de 118 artigos, teses e dissertações.
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1. 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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2. 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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3. 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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4. 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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5. 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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6. 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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7. ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF PHYSIOLOGICAL AND PRODUCTIVE VARIABLES OF BROILERS
ABSTRACT Due to a number of factors involving the thermal environment of a broiler cutting installation and its interaction with the physiological and productive responses of birds, artificial intelligence has been shown to be an interesting methodology to assist in the decision-making process. For this reason, the main aim of this work was to develop an art
Eng. Agríc.. Publicado em: 2020-02
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8. 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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9. Breast Cancer Prediction Using Dominance-based Feature Filtering Approach: A Comparative Investigation in Machine Learning Archetype
Abstract Breast cancer is the most commonly witnessed cancer amongst women around the world. Computer aided diagnosis (CAD) have been playing a significant role in early detection of breast tumors hence to curb the overall mortality rate. This work presents an enhanced empirical study of impact of dominance-based filtering approach on performances of variou
Braz. arch. biol. technol.. Publicado em: 25/11/2019
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10. Semi-automated counting model for arbuscular mycorrhizal fungi spores using the Circle Hough Transform and an artificial neural network
Abstract: Arbuscular Mycorrhizae (AM) are mutualistic associations between Arbuscular Mycorrhizal Fungi (AMF) and the roots of many plant species. AMF spores give rise to filaments that develop in the root system of plants and contribute to the absorption of water and some nutrients. This article introduces a semi-automated counting model of AMF spores in sl
An. Acad. Bras. Ciênc.. Publicado em: 21/10/2019
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11. Review of Power Device for Solar-Powered Aircraft Applications
ABSTRACT This paper reviews various power device components of solar-powered aircraft such as photovoltaic (PV) cells, maximum power point tracker (MPPT) and rechargeable batteries. The various power device components were highlighted, and the ones applicable to aircraft were analyzed, based on criteria as efficiency for photovoltaic cells; energy densities
J. Aerosp. Technol. Manag.. Publicado em: 10/10/2019
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12. Modeling of tree recruitment by artificial neural networks after wood harvesting in a forest in eastern Amazon rain forest
Resumo A modelagem do recrutamento em florestais tropicais é importante para estudos de sustentabilidade do manejo florestal, por dar subsídio adequado à recuperação do estoque de madeira. O objetivo do trabalho foi estimar o recrutamento após a colheita de madeira, empregando um modelo de rede neural artificial (RNA). A área de estudo está localizad
Ciênc. Florest.. Publicado em: 30/09/2019