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Now showing items 11-20 of 28
Quasi seven-level operation of multilevel converters with selective harmonic elimination
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
Generally, selective harmonic elimination (SHE) complexity for multilevel inverters increases with the increase in number of levels. In this paper, a novel approach for SHE is introduced. This approach is based on cancelling ...
Control of doubly-fed induction machine storage system for constant charging/discharging grid power using artificial neural network
(
IET
, 2012 , Conference Paper)
A large-capacity low-speed flywheel energy storage system based on a doubly-fed induction machine (DFIM) basically consists of a wound-rotor induction machine, and a back-to-back converter for rotor excitation. It has been ...
A power control strategy for flywheel doubly-fed induction machine storage system using artificial neural network
(
Elsevier Ltd
, 2013 , Article)
A large-capacity low-speed flywheel energy storage system (FESS) based on a doubly-fed induction machine (DFIM) consists of a wound-rotor induction machine and a back-to-back converter rated at 30-35% of the machine power ...
Health monitoring and degradation prognostics in gas turbine engines using dynamic neural networks
(
American Society of Mechanical Engineers (ASME)
, 2015 , Conference Paper)
In this paper two artificially intelligent methodologies are proposed and developed for degradation prognosis and health monitoring of gas turbine engines. Our objective is to predict the degradation trends by studying ...
A hybrid prognosis and health monitoring strategy by integrating particle filters and neural networks for gas turbine engines
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, a novel hybrid structure is proposed for the development of health monitoring techniques of nonlinear systems by integration of model-based and computationally intelligent and data-driven techniques. In our ...
Multiple-model sensor and components fault diagnosis in gas turbine engines using autoassociative neural networks
(
American Society of Mechanical Engineers
, 2014 , Article)
In this paper the problem of fault diagnosis in an aircraft jet engine is investigated by using an intelligent-based methodology. The proposed fault detection and isolation (FDI) scheme is based on the multiple model ...
Partial synchronization of biological neural networks and the anesthetic cascade
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
With the advances in biochemistry, molecular biology, and neurochemistry there has been impressive progress in understanding the molecular properties of anesthetic agents. However, there has been little focus on how the ...
Efficiency validation of one dimensional convolutional neural networks for structural damage detection using a SHM benchmark data
(
International Institute of Acoustics and Vibration, IIAV
, 2018 , Conference Paper)
In this paper, a novel one dimensional convolution neural network (1D-CNN) based structural damage assessment technique is validated with a benchmark study published by IASC-ASCE Structural Health Monitoring Task Group in ...
Progressive Operational Perceptrons
(
Elsevier B.V.
, 2017 , Article)
There are well-known limitations and drawbacks on the performance and robustness of the feed-forward, fully-connected Artificial Neural Networks (ANNs), or the so-called Multi-Layer Perceptrons (MLPs). In this study we ...
Learned vs. hand-designed features for ECG beat classification: A comprehensive study
(
Springer Verlag
, 2017 , Conference Paper)
In this study, in order to find out the best ECG classification performance we realized comparative evaluations among the state-of-the-art classifiers such as Convolutional Neural Networks (CNNs), multi-layer perceptrons ...