Add to ORKGThis paper documents experiments performed using a GA to optimise the parameters of a dynamic neural tree model. Two fitness functions were created from two selected clustering measures, and a population of genotypes, specifying parameters of the model were evolved. This process mirrors genomic evolution and ontogeny. It is shown that the evolved parameter values improved performanceFinal Accepted Versio
The terms phenotypic and genotypic learning refer to naturally inspired adaptive algo-rithms, based ...
Neural networks and evolutionary computation have a rich intertwined history. They most commonly app...
Abstract- Artificial Neural Networks have a number of properties which make them psuitable to solve ...
Original article can be found at: http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=9314Evolutio...
Evolutionary computation has been around ever since the late 50s. This thesis aims at elaborate on g...
Artificial neural networks have been used to solve different problems, one being survival analysis o...
[[abstract]]This paper Proposes a novel adaptive genetic algorithm (GA) extrapolated by an ant colon...
Original article can be found at: http://www.sciencedirect.com/science/journal/15684946--Copyright E...
Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering2002-20...
The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithm...
International audienceThe Continuous Neural Field Theory introduces biologically-inspired competitio...
This thesis starts with a brief introduction to neural networks and the tuning of neural networks us...
Copyright Springer.The Stochastic Competitive Evolutionary Neural Tree (SCENT) is a new unsupervised...
The aim of this work is the genetic design of neural networks, which are able to classify within var...
We develop a tree-based genetic programming system, capable of modelling evolvability during evoluti...
The terms phenotypic and genotypic learning refer to naturally inspired adaptive algo-rithms, based ...
Neural networks and evolutionary computation have a rich intertwined history. They most commonly app...
Abstract- Artificial Neural Networks have a number of properties which make them psuitable to solve ...
Original article can be found at: http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=9314Evolutio...
Evolutionary computation has been around ever since the late 50s. This thesis aims at elaborate on g...
Artificial neural networks have been used to solve different problems, one being survival analysis o...
[[abstract]]This paper Proposes a novel adaptive genetic algorithm (GA) extrapolated by an ant colon...
Original article can be found at: http://www.sciencedirect.com/science/journal/15684946--Copyright E...
Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering2002-20...
The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithm...
International audienceThe Continuous Neural Field Theory introduces biologically-inspired competitio...
This thesis starts with a brief introduction to neural networks and the tuning of neural networks us...
Copyright Springer.The Stochastic Competitive Evolutionary Neural Tree (SCENT) is a new unsupervised...
The aim of this work is the genetic design of neural networks, which are able to classify within var...
We develop a tree-based genetic programming system, capable of modelling evolvability during evoluti...
The terms phenotypic and genotypic learning refer to naturally inspired adaptive algo-rithms, based ...
Neural networks and evolutionary computation have a rich intertwined history. They most commonly app...
Abstract- Artificial Neural Networks have a number of properties which make them psuitable to solve ...