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Materias / palabras clave: Architecture; Arquitectura; Computers; Informática; Neural Networks (Computer); Redes neuronales (Informática)

Abstract Background Preterm low birth weight (PLBW) is a major global contributor to neonatal morbidity and mortality. This study aims to develop and evaluate a novel artificial neural network (ANN) based predictive mode...

Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Abstract Background Chronic kidney disease (CKD) frequently causes death in older cats; its early detection is challenging. Objectives To build a sensitive and specific model for early prediction of CKD in cats using art...

"Data-driven simulation of pedestrian dynamics is an incipient and promising approach for building reliable microscopic pedestrian models. We propose a methodology based on generalized regression neural networks, which d...

The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle th...

Speaker identification techniques are one of those most advanced modern technologies and there are many different systems had been developed, from methods that used to extract characteristics and classification. The appl...

Background: In calibration, analytical figures of merit (AFOMs) are statistical parameters of great importance for method validation. In recent decades, relevant contributions have been made to estimate AFOMs in many cal...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

Abstract Nanofluids have emerged as promising heat transfer media due to their superior thermal performance associated to conventional fluids, yet their behavior under mutual impacts of radiation, heat source/sink, and m...

Abstract Background The research shows the impact of land use forms and population density on the spatial variation of COVID-19 cases and deaths. Selected elements of land use that influence the number of COVID-19 cases ...

"Data-driven simulation of pedestrian dynamics is an incipient and promising approach for building reliable microscopic pedestrian models. We propose a methodology based on generalized regression neural networks, which d...

Accidental ignition of energetic compounds by electrostatic discharge poses significant safety risks, highlighting the need for precise prediction of electric spark sensitivity. Here we develop a novel interpretable mach...

Abstract The Broad Learning System (BLS) provides an effective framework for nonlinear mapping, offering advantages over traditional deep neural networks through its expanded input node architecture. While BLS has demons...

Abstract The conversion of solar radiation into thermal energy has gained increasing attention due to the growing demand for renewable sources of heat and electricity. Nanofluids, owing to their enhanced heat transfer ca...

Materias / palabras clave: Computer science; Feed forward; Feedforward neural network; Artificial intelligence; Artificial neural network; Control theory (sociology); Control engineering; Control (management); Engineering

Materias / palabras clave: Feed forward; Feedforward neural network; Computer science; Class (philosophy); Function (biology); Space (punctuation); Artificial neural network; Degree (music); Control theory (sociology); Artificial intelligence; Alg...

High-dimensional data can be converted to low-dimensional codes by training a multilayer neural network with a small central layer to reconstruct high-dimensional input vectors. Gradient descent can be used for fine-tuni...

The recognition of handwritten numerals has many important applications, such as automatic lecture of zip codes in post offices, and automatic lecture of numbers in checknotes. In this paper we present a preprocessing me...

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning alg...

Materias / palabras clave: Computer science; Task (project management); Convergence (economics); Measure (data warehouse); Backpropagation; Artificial intelligence; Multilayer perceptron; Perceptron; Domain (mathematical analysis); Artificial neur...