Add to ORKGAbstract. In a companion paper, a constructive approach for designing feedfor-ward neural networks using genetic algorithms is proposed [7, 8]. The algorithm constructs networks with close to optimum size growing hidden layer units in a problem specific manner and has very good generalization properties. In this paper, in order to make the constructive design algorithm computationally effi-cient, a two stage speed up method is proposed: (1) parallel genetic search for hidden layer units construction; and (2) the dynamic pocket algorithm for learn-ing the hidden to output layer weights. The proposed parallel method achieves significant computational speed-up over the sequential method and is suitable for distributed implementation. In additi...
In this paper, the ability of genetic algorithms in designing artificial neural network (ANN) is inv...
It has been demonstrated that genetic algorithms (GAs) can help search the global (or near global) o...
Interest in algorithms which dynamically construct neural networks has been growing in recent years....
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
The parallel genetic algorithms implementation for neural networks models construction is discussed....
The parallel genetic algorithms implementation for neural networks models construction is discussed....
. For many applications feedforward neural networks have proved to be a valuable tool. Although the ...
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
For many applications feedforward neural networks have proved to be a valuable tool. Although the ba...
We present a general and systematic method for neural network design based on the genetic algorithm....
Genetic algorithms are computational techniques for search, optimization and machine learning that a...
Abstract:- This paper proposes an evolutionary design methodology of multilayer feedforward neural n...
In this paper, the ability of genetic algorithms in designing artificial neural network (ANN) is inv...
In this paper, the ability of genetic algorithms in designing artificial neural network (ANN) is inv...
It has been demonstrated that genetic algorithms (GAs) can help search the global (or near global) o...
Interest in algorithms which dynamically construct neural networks has been growing in recent years....
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
The parallel genetic algorithms implementation for neural networks models construction is discussed....
The parallel genetic algorithms implementation for neural networks models construction is discussed....
. For many applications feedforward neural networks have proved to be a valuable tool. Although the ...
Parallelizing neural networks is an active area of research. Current approaches surround the paralle...
For many applications feedforward neural networks have proved to be a valuable tool. Although the ba...
We present a general and systematic method for neural network design based on the genetic algorithm....
Genetic algorithms are computational techniques for search, optimization and machine learning that a...
Abstract:- This paper proposes an evolutionary design methodology of multilayer feedforward neural n...
In this paper, the ability of genetic algorithms in designing artificial neural network (ANN) is inv...
In this paper, the ability of genetic algorithms in designing artificial neural network (ANN) is inv...
It has been demonstrated that genetic algorithms (GAs) can help search the global (or near global) o...
Interest in algorithms which dynamically construct neural networks has been growing in recent years....