Add to ORKGAbstract|In our previous research, we have pro-posed new network structure with a®ordable neurons in hidden layer of the feedforward neural network to re°ect real brain mechanism. We named this proposed network \A®ordable Neural Network. " We consider that operation of a®ordable neurons are especially ef-fective on evolution of neural network in brain. In this study, we investigate the performance of a®ord-able neural network when the hidden layer is evolved using Genetic Algorithm. By computer simulations, we consider that the a®ordable neurons exert an im-portant in°uence on evolution process in the hidden layer of the network. 1
In this contribution we present a novel method, called Evolutionary Acquisition of Neural Topologies...
We propose a previously unrecognized kind of informational entity in the brain that is capable of ac...
In this contribution we present a novel method, called Evolutionary Acquisition of Neural Topologies...
In our previous research, we have proposed a new network structure with affordable neurons in hidden...
We propose a previously unrecognized kind of informational entity in the brain that is capable of ac...
We propose a previously unrecognized kind of informational entity in the brain that is capable of ac...
Hypotheses are presented of what could be specified by genes to enable the different functional arch...
This paper outlines a neural model, which has been designed to be flexible enough to assume most mat...
Genetic algorithms are computational techniques for search, optimization and machine learning that a...
Although artificial neural networks have taken their inspiration from natural neuro-logical systems ...
Abstract. The idea of using simulated evolution to create neural networks that learn faster and gene...
Neuroevolution, i.e. evolving artificial neural networks with genetic algorithms, has been highly ef...
Abstract—Biological neurons are extremely complex cells whose morphology grows and changes in respon...
In this report we present the results of a series of simulations in which neural networks undergo ch...
In this paper we investigate multi-layer perceptron networks in the task domain of Boolean functions...
In this contribution we present a novel method, called Evolutionary Acquisition of Neural Topologies...
We propose a previously unrecognized kind of informational entity in the brain that is capable of ac...
In this contribution we present a novel method, called Evolutionary Acquisition of Neural Topologies...
In our previous research, we have proposed a new network structure with affordable neurons in hidden...
We propose a previously unrecognized kind of informational entity in the brain that is capable of ac...
We propose a previously unrecognized kind of informational entity in the brain that is capable of ac...
Hypotheses are presented of what could be specified by genes to enable the different functional arch...
This paper outlines a neural model, which has been designed to be flexible enough to assume most mat...
Genetic algorithms are computational techniques for search, optimization and machine learning that a...
Although artificial neural networks have taken their inspiration from natural neuro-logical systems ...
Abstract. The idea of using simulated evolution to create neural networks that learn faster and gene...
Neuroevolution, i.e. evolving artificial neural networks with genetic algorithms, has been highly ef...
Abstract—Biological neurons are extremely complex cells whose morphology grows and changes in respon...
In this report we present the results of a series of simulations in which neural networks undergo ch...
In this paper we investigate multi-layer perceptron networks in the task domain of Boolean functions...
In this contribution we present a novel method, called Evolutionary Acquisition of Neural Topologies...
We propose a previously unrecognized kind of informational entity in the brain that is capable of ac...
In this contribution we present a novel method, called Evolutionary Acquisition of Neural Topologies...