Artificial neural networks
TítuloUsing Artificial Neural Networks for Identifying Patients with Mild Cognitive Impairment Associated with Depression Using Neuropsychological Test Features
... the artificial neural networks (ANNs) are flexible, non-linear, and multidimensional mathematical systems, easily implemented and handled, and capable of solving complex functions in very diverse ...
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TítuloDeep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications
... Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other ...Deep ...
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Predicting the Cardioactivity of Tivela stultorum clam with Digoxin Using Artificial Neural Networks
... Artificial neural networks (ANN) are a computational method that has been widely used to solve complex prob- lems and carry out predictions on nonlinear ...perceptron artificial neural ...
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Environmental risk assessment in the mediterranean region using artificial neural networks
... Vulnerability maps have been used worldwide to assess the risk of groundwater contamination (Almasri, 2008; Andreo et al., 2005; Martínez-Bastida et al., 2010; Martínez-Santos et al., 2008; Masetti et al., 2009; Neukum ...
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Predicting the particle size distribution of eroded sediment using artificial neural networks
... as artificial neural networks (ANNs) have been used to predict soil properties and soil related process (Baker and Ellison, 2008; Koekkoek and Booltink, 1999; Licznar and Nearing, 2003; Merdun et ...
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Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks
... Artificial neural networks (ANNs) are biologically inspired networks based on the neuron organization and decision-making process of the human brain ...
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A target oriented averaging search trajectory and its application in artificial neural networks
... Machine Learning (ML) concieved with the ambitious goal to automatically reproduce the human learning. A first example of this was the Perceptron Algorithm [7], a model of an arti- ficial neuron learning from samples. ...
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Microcalcification Detection Applying Artificial Neural Networks and Mathematical Morphology in Digital Mammograms
... ABSTRACT- Breast cancer is one of the leading causes to women mortality in the world and early detection is an important means to reduce the mortality rate. The presence of microcalcifications clusters has been ...
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TítuloAvoiding interference in planar arrays through the use of artificial neural networks
... of Artificial Neural Networks (ANN) in a variety of fields makes possible their use in signal processing, and synthesis or optimi- zation for radiating ...Function Neural Network (RBFNN) that ...
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Ensembles of Artificial Neural Networks: Analysis and Development of Design Methods
... The application of neural networks in order to solve classification tasks has been introduced in this chapter. In fact, two network architectures, MF and RBF, have been described and some basic experiments ...
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Modelado de transistores de microondas utilizando redes neuronalesModeling of microwave transistors using artificial neural networks
... a neural network based quasi-static model of a commercial AlGaN/GaN HEMT, which accurately reproduces the current and charge storage characteristics of the device was ...
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Predicción de series de tiempo aplicando redes neuronales artificiales.Time series prediction using artificial neural networks
... Based on the results obtained when applying the Gamma test to the SOI data, TDNN models were built with architectures n i – 30 –24 – 1, where n i represents the number of input units, depending on the mask used. The ...
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Parametric analysis of carbonation process in reinforced concrete structures through Artificial Neural Networks
... The aim of this paper is parametrically analyze the main factors that influence on the progress of concrete carbonation front. Therefore, a numerical model was developed using Artificial Neural ...
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TítuloArtificial Neural Networks Manipulation Server: Research on the Integration of Databases and Artificial Neural Networks
... data networks; support to their integration with heterogeneous systems; automation of the generation process of training and test sets, and improvement of the pattern-preprocessing ...
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Artificial neural networks applied to forecasting time series
... With respect to the limitations and criticisms received, ANN lack a theoretical foundation and a systematic procedure for the construction of the model, comparable to the classical approximations such as the Box-Jenkins ...
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Development of technologies and techniques for wide field astronomical observations
... the artificial neural networks is achieved, the results can lead to the development of future AO systems based on this technique, which is relevant for the next generation of extremely large ...
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Frost prediction with machine learning techniques
... A BSTRACT : Frost is the condition that exists when the temperature of the earth's surface and earthbound objects falls below freezing (0°C). These events may have serious consequences on crop production, so actions must ...
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Implementación de Redes Generativas Adversarias (GANs) para la generación de imágenes de tejido humano
... Adversarial Networks (GANs), a well-known technique of Deep ...two artificial neural networks that compete with each other in a zero-sum ...
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Estimation of real traffic radiated emissions from electric vehicles in terms of the driving profile using neural networks
... The arrangement of the measurement system used in this test is outlined in Figure 15. Tests have been done inside a semi-anechoic chamber in Thales in Hengelo (the Netherlands) [174] in the 150 kHz – 30 MHz range. Most ...
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