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Can artificial neural networks estimate potential evapotranspiration in Peruvian highlands?
(Springer Link, 2019)
Evapotranspiration (ETo) is one of the most important variables of the water cycle when water requirements for irrigation, water resource planning or hydrological applications are analyzed. In this context, models based ...
Potential of neural networks for structural damage localization
(USFQ PRESS, departamento editorial de la Universidad San Francisco de Quito USFQ, 2019)
Multiple response optimization of styrene–butadiene rubber emulsion polymerization
(Pergamon-Elsevier Science Ltd, 2009-04)
A multiple response optimization of styrene-butadiene rubber (SBR) emulsion batch polymerization is proposed. Several properties of latex and rubber were optimized to obtain a particular grade of SBR, namely 1712. Artificial ...
Prediction of Arrhythmias and Acute Myocardial Infarctions using Machine LearningPredicción de arritmias e infartos agudos de miocardio usando aprendizaje automático
(Universidad Politécnica Salesiana, 2023)
A neural network based error correction method for radio occultation electron density retrieval
(Elsevier, 2015-10-19)
Abel inversion techniques have been widely employed to retrieve electron density profiles (EDPs) from radio occultation (RO) measurements, which are available by observing Global Navigation Satellite System (GNSS) satellites ...
Optimal Canny's Parameters Regressions for Coastal Line Detection in Satellite-Based SAR Images
(Institute of Electrical and Electronics Engineers, 2020-01)
Canny's algorithm is a very well-known and widely implemented multistage edge detector. The extraction of coastal lines in space-borne-based synthetic aperture radar (SAR) images using this algorithm is particularly ...
ESTIMATING LATENT HEAT FLUX OVER RESERVOIRS USING AN ARTIFICIAL NEURAL NETWORKEstimativa de Fluxo de Calor Latente em Reservatórios Através de uma Rede Neural Artificial
(Universidade Federal de Santa Maria, 2016)
A flexible and practical approach for real-time weed emergence prediction based on Artificial Neural Networks
(2018-06)
Most popular emergence prediction models require species-specific population-based parameters to modulate thermal/hydrothermal accumulation. Such parameters are frequently unknown and difficult to estimate. Moreover, such ...
Producing non-traditional flour from watermelon rind pomace: Artificial neural network (ANN) modeling of the drying process
(Academic Press Ltd - Elsevier Science Ltd, 2021-03)
An artificial neural network (ANN) model was developed to simulate the convective drying process of watermelon rind pomace used in the fabrication of non-traditional flour. Also, the drying curves obtained experimentally ...