Buscar
Mostrando ítems 21-30 de 265
Energy Consumption Minimization In An Innovative Hybrid Power Production Station By Employing Pv And Evacuated Tube Collector Solar Thermal Systems
(PERGAMON-ELSEVIER SCIENCE LTDOXFORD, 2016)
Tidal forecasting using RNN in Bahia Blanca estuary, Argentina
(Interciencia, 2009-12)
In recent years, the availability of accurate ocean tide models has become increasingly important, as tides are the main contributor to disposal and movement of sediments, tracers and pollutants, and ...
Deep-Learning for Volcanic Seismic Events Classification
(Quito, 2020)
Imputation method based on recurrent neural networks for the internet of things
(Universidad EAFITMaestría en IngenieríaEscuela de Ingeniería, 2018)
The Internet of Things (IoT) refers to the new technological paradigm in which sensors and common objects, like household appliances, connect to and interact through the Internet -- This new paradigm, and the use of ...
GRASP heuristics for Wide Area Network design
(UR. FI-INCO,, 2005)
A wide area network (WAN) can be considered as a set of sites and a set of communication lines that interconnect the sites. Topologically a WAN is organized in two levels: the backbone network and the access network composed ...
Análisis predictivo en Bitcoin utilizando técnicas de aprendizaje profundo
(UR.FI.INCO, 2019)
El prominente mercado de las criptomonedas, caracterizado por un alto nivel especulativo y de gran volatilidad, plantea un novedoso y desafiante escenario para la aplicación de métodos de pronósticos sobre series temporales. ...
Estimación de la temperatura del suelo mediante técnicas de aprendizaje profundo
(2021)
La temperatura del suelo cumple un rol fundamental en el funcionamiento de microorganismos, tasas de descomposición de residuos y en el ciclo hidrológico. Sin embargo, la ausencia de monitoreo y la baja disponibilidad de ...
Identifying the knee joint angular position under neuromuscular electrical stimulation via long short-term memory neural networks
(2020-01-01)
Purpose: Recurrent neural networks (RNNs) offer a promising opportunity for identifying nonlinear systems. This paper investigates the effectiveness of the long short-term memory (LSTM) RNN architecture in the specific ...