Add to ORKGThe paper aims to assess the use of genetic algorithms for training neural networks used in secured Business Intelligence Mobile Applications. A comparison is made between classic back-propagation method and a genetic algorithm based training. The design of these algorithms is presented. A comparative study is realized for determining the better way of training neural networks, from the point of view of time and memory usage. The results show that genetic algorithms based training offer better performance and memory usage than back-propagation and they are fit to be implemented on mobile devices
Deep Learning networks are a new type of neural network that discovers important object features. Th...
In recent times, wireless access technology is becoming increasingly commonplace due to the ease of ...
This paper presents the tuning of the structure and parameters of a neural network using an improved...
Abstract – By making use of Genetic Algorithm, Optimization problems can be solved and the best fit ...
This paper attempts to investigate the methods of cryptography and strong authentication for mobile ...
Učenje neuronskih mreža spada u probleme optimizacije. Višeslojne unaprijedne statičke neuronske mre...
To analysis the speed of sending message in Healthcare standard 7 with the use of back propagation i...
This work deals with methods for finding optimal neural network architectures to learn par-ticular p...
Abstract. This work deals with methods for finding optimal neural network architectures to learn par...
Abstract- Artificial Neural Networks have a number of properties which make them psuitable to solve ...
This book provides a unified framework that describes how genetic learning can be used to design pat...
Genetic Algorithms have been gaining much interest since the early 1970\u27s and have intrigued peop...
This thesis deals with evolutionary and genetic algorithms and the possible ways of combining them. ...
Traditionally Genetic algorithms are thought of as brute force approaches, aimed to arrive at soluti...
The training of product neural networks using genetic algorithms is discussed. Two unusual neural ne...
Deep Learning networks are a new type of neural network that discovers important object features. Th...
In recent times, wireless access technology is becoming increasingly commonplace due to the ease of ...
This paper presents the tuning of the structure and parameters of a neural network using an improved...
Abstract – By making use of Genetic Algorithm, Optimization problems can be solved and the best fit ...
This paper attempts to investigate the methods of cryptography and strong authentication for mobile ...
Učenje neuronskih mreža spada u probleme optimizacije. Višeslojne unaprijedne statičke neuronske mre...
To analysis the speed of sending message in Healthcare standard 7 with the use of back propagation i...
This work deals with methods for finding optimal neural network architectures to learn par-ticular p...
Abstract. This work deals with methods for finding optimal neural network architectures to learn par...
Abstract- Artificial Neural Networks have a number of properties which make them psuitable to solve ...
This book provides a unified framework that describes how genetic learning can be used to design pat...
Genetic Algorithms have been gaining much interest since the early 1970\u27s and have intrigued peop...
This thesis deals with evolutionary and genetic algorithms and the possible ways of combining them. ...
Traditionally Genetic algorithms are thought of as brute force approaches, aimed to arrive at soluti...
The training of product neural networks using genetic algorithms is discussed. Two unusual neural ne...
Deep Learning networks are a new type of neural network that discovers important object features. Th...
In recent times, wireless access technology is becoming increasingly commonplace due to the ease of ...
This paper presents the tuning of the structure and parameters of a neural network using an improved...