Add to ORKGThis research is to develop a biologically inspired hybrid intelligent system - evolving neural networks - that can be used in data mining, especially in classification problems. This hybrid system employs computational intelligence methodologies, such as neural networks and genetic algorithms. --Abstract, page iii
This book provides a unified framework that describes how genetic learning can be used to design pat...
There are many ways of classifying data such as statistical methods and rule base systems. This thes...
Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms...
This research is to develop a biologically inspired hybrid intelligent system - evolving neural netw...
The primary aim of this research is to develop an intelligent system for online data mining for clas...
The ensemble of evolving neural networks, which employs neural networks and genetic algorithms, is d...
This paper series focusses on the intersection of neural networks and evolutionary computation. It i...
In this paper, we apply genetic algorithms to the automatic generation of neural networks as well as...
The aim of this work is the genetic design of neural networks, which are able to classify within var...
International audienceIn general, the topology of Artificial Neural Networks (ANNs) is human-enginee...
This thesis argues that natural complex systems can provide an inspiring example for creating softwa...
This study introduces a neuro-fuzzy-genetic data mining architecture, which discovers patterns and r...
This paper presents a comparative analysis of linear genetic programming and artificial neural netwo...
Learning and evolution are two fundamental forms of adaptation. There has been a great interest in c...
The evolutionary approach to arti®cial neural networks has been rapidly developing in recent years a...
This book provides a unified framework that describes how genetic learning can be used to design pat...
There are many ways of classifying data such as statistical methods and rule base systems. This thes...
Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms...
This research is to develop a biologically inspired hybrid intelligent system - evolving neural netw...
The primary aim of this research is to develop an intelligent system for online data mining for clas...
The ensemble of evolving neural networks, which employs neural networks and genetic algorithms, is d...
This paper series focusses on the intersection of neural networks and evolutionary computation. It i...
In this paper, we apply genetic algorithms to the automatic generation of neural networks as well as...
The aim of this work is the genetic design of neural networks, which are able to classify within var...
International audienceIn general, the topology of Artificial Neural Networks (ANNs) is human-enginee...
This thesis argues that natural complex systems can provide an inspiring example for creating softwa...
This study introduces a neuro-fuzzy-genetic data mining architecture, which discovers patterns and r...
This paper presents a comparative analysis of linear genetic programming and artificial neural netwo...
Learning and evolution are two fundamental forms of adaptation. There has been a great interest in c...
The evolutionary approach to arti®cial neural networks has been rapidly developing in recent years a...
This book provides a unified framework that describes how genetic learning can be used to design pat...
There are many ways of classifying data such as statistical methods and rule base systems. This thes...
Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms...