Buscar
Mostrando ítems 21-30 de 2548
Neural network based estimation of torque in induction motors for real-time applications
(Taylor & Francis Inc, 2005-04-01)
Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal ...
Neural network based estimation of torque in induction motors for real-time applications
(Taylor & Francis Inc, 2005-04-01)
Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal ...
Damage detection in beams by using artificial neural networks and dynamical parameters
(IMPRENTA UNIV ANTIOQUIAMEDELLIN, 2012-06)
In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal ...
Enhancing 5G Small Cell Selection: A Neural Network and IoV-Based Approach
(Sensors (Basel), 2021)
The ultra-dense network (UDN) is one of the key technologies in fifth generation (5G) networks. It is used to enhance the system capacity issue by deploying small cells at high density. In 5G UDNs, the cell selection process ...
Modeling sterilization process of canned foods using artificial neural networks
(Chemical Engineering and Processing: Process Intensification, 2018)
LIPSNN: A Light Intrusion-Proving Siamese Neural Network Model for Facial Verification
Facial verification has experienced a breakthrough in recent years, not only due to the improvement in accuracy of the verification systems but also because of their increased use. One of the main reasons for this has been ...
Explainable prediction of chronic renal disease in the Colombian population using neural networks and case-based reasoning
This paper presents a neural network-based classifier to predict whether a person is at risk of developing chronic kidney disease (CKD). The model is trained with the demographic data and medical care information of two ...
Impedance-based structural health monitoring with artificial neural networks
(2000-03-01)
This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based ...