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Modeling and analysis of artificial neural networks applied in operations research
(Elsevier B.V., 2001-01-01)
Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a ...
Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems
(Elsevier B.V., 2011-01-01)
This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. ...
Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems
(Elsevier B.V., 2011-01-01)
This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. ...
Load balancing method for KDN-based data center using neural network
(Universidad de LimaPE, 2019)
The growth of cloud application services delivered through data centers with varying
traffic demands unveils limitations of traditional load balancing methods. Aiming to attend
evolving scenarios and improve the overall ...
Path generation for a mobile robot using neural networksGeneración de trayectorias para un robot móvil empleando redes neuronales
(Pereira : Universidad Tecnológica de PereiraFacultad de Ciencias Básicas, 2011)
An efficient neural approach to economic load dispatch in power systems
(IEEE, 2001-01-01)
A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive ...
Seam Carving Detection Using Convolutional Neural Networks
(Ieee, 2018-01-01)
Deep Learning techniques have been widely used in the recent years, primarily because of their efficiency in several applications, such as engineering, medicine, and data security. Seam carving is a content-aware image ...
Simulator of mobile robots controlled by Artificial Neural Networks to learning courses in robotics
(Ieee, 2020-01-01)
A mobile robot simulator was developed in a computer graphics environment as a didactic tool able to assist the teaching and learning in disciplines that involve mobile robotics. It is also useful in validating control ...
A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the ...
A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the ...