Artificial Neural Networks (ANN)
A target oriented averaging search trajectory and its application in artificial neural networks
... these artificial neurons which is well-known as Artificial Neural Networks ...(ANNs). ANN and all ML prediction models likewise employ an ML algorithm to solve an optimization problem ...
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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 ...An ANN can approximate the ...
11
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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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 ...
13
TítuloDeep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications
... Feedforward Neural Networks (DFNN), Deep Belief Networks (DBN), Deep AutoEncoder Networks, Deep Boltzmann Machines (DBM), Deep Convolutional Neural Networks (DCNN) and Deep ...
26
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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Predicting soil bulk density using hierarchical pedrotransfer functions and artificial neural networks
... the ANN was compared with those of the calibrated PTFs evaluated in section ...the ANN compared with the already existing ...the ANN technique cannot significantly enhance the quality of estimates ...
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TítuloArtificial Neural Networks Manipulation Server: Research on the Integration of Databases and Artificial Neural Networks
... Another interesting aspect, which increases the usefulness of the AMS, and makes the system very friendly, is that of using descriptive fields of the variables used by the ANNs. The descriptive fields must also be part ...
14
Artificial neural networks applied to forecasting time series
... used neural network in time series forecasting has been the MLP (Multilayer Perceptron) (Bishop, ...other neural network models with respect to the MLP model in this type of task (Liu & Quek, ...as ...
8
Microcalcification Detection Applying Artificial Neural Networks and Mathematical Morphology in Digital Mammograms
... Clustering algorithms help us to get a better comprehension and knowledge of the analysed data with the objective to segment the image into different areas according to the problem at hand. In this work, we propose an ...
6
Modelado de transistores de microondas utilizando redes neuronalesModeling of microwave transistors using artificial neural networks
... the ANN-based terminal charge ...charge ANN models can be directly developed from the imaginary part of the intrinsic admittance parameters of the device, improving the numerical path-integration technique ...
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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 ...an ANN direction ...Function ...
12
Ensembles of Artificial Neural Networks: Analysis and Development of Design Methods
... Prior to our research, Verikas et al. introduced an important combiner analysis [76]. However, we consider that this comparison was not complete enough because only one ensemble model, CVCv2, was trained on four ...
415
Development of technologies and techniques for wide field astronomical observations
... Artificial Neural Networks have been implemented in many applications such as pat- tern recognition, data clustering, open-loop automatic control, among many other ...Optics, ANN has been used ...
145
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 ...
11
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 ...
50
Glucose-Insulin regulator for type 1 diabetes using high order neural networks
... using artificial neural ...recurrent neural identifier in order to reproduce the dynamical behavior of a discrete-time virtual patient model with ...This neural identifier is trained with a ...
8
Computer simulation of an excess proton in aqueous systems
... As shown in this thesis confining environments with characteristic lengths at the nanometer scale were able to significantly change the equilibrium properties and dynamics associated with any reactive process in solution ...
157
Identifying Desert locust breeding areas by means of Earth Observation in Mauritania
... forward neural networks offer a flexible method to generalize linear regression ...function. ANN accuracy is merely handled by two parameters: the amount of weight decay and the number of hidden ...
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