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Neural network model-based predictive control of liquid–liquid extraction contactors
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Elsevier Ltd
, 2004 , Article)
The inherent complex nonlinear dynamic characteristics and time varying transients of the liquid–liquid extraction process draw the attention to the application of nonlinear control techniques. In this work, neural ...
Representation of Adsorption Data for the Isopropanol-Water System using Neural Network Techniques
(
WILEY-VCH Verlag
, 2005 , Article)
Molecular sieves and palm stone, a newly developed bio-based adsorbent, were used to break an azeotropic isopropanol-water system via an adsorptive distillation process. Equilibrium data at different inlet water contents ...
MASACAD: A multi-agent approach to information customization for the purpose of academic advising of students
(
Elsevier B.V.
, 2006 , Article)
The growth and advancement in the Internet and the World Wide Web has led to an explosion in the amount of available information. This staggering amount of information has made it extremely difficult for users to locate ...
Adaptive and Predictive Control of Liquid-Liquid Extractors Using Neural-Based Instantaneous Linearization Technique
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WILEY-VCH Verlag GmbH & Co.
, 2006 , Article)
Nonlinearity of the extraction process is addressed via the application of instantaneous linearization to control the extract and raffinate concentrations. Two feed-forward neural networks with delayed inputs and outputs ...
Artificial neural network-based kinematics Jacobian solution for serial manipulator passing through singular configurations
(
Elsevier Ltd
, 2009 , Article)
Singularities and uncertainties in arm configurations are the main problems in kinematics robot control resulting from applying robot model, a solution based on using Artificial Neural Network (ANN) is proposed here. The ...
Training Radial Basis Function Neural Networks for Classification via Class-Specific Clustering
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
In training radial basis function neural networks (RBFNNs), the locations of Gaussian neurons are commonly determined by clustering. Training inputs can be clustered on a fully unsupervised manner (input clustering), or ...
Active vibration control of flexible cantilever plates using piezoelectric materials and artificial neural networks
(
Academic Press
, 2016 , Article)
The study presented in this paper introduces a new intelligent methodology to mitigate the vibration response of flexible cantilever plates. The use of the piezoelectric sensor/actuator pairs for active control of plates ...
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
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Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ...
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
(
Academic Press
, 2017 , Article)
Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has ...
Revealing the hidden features in traffic prediction via entity embedding
(
Springer London
, 2019 , Article)
Models based on neural networks (NN) have been used widely and successfully in traffic prediction resulting in improved accuracy and efficiency in traffic flow, speed, passenger flow, and delay. Input data include continuous ...