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» Modeling Neural Processes in Lindenmayer Systems
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AEI
1999
110views more  AEI 1999»
13 years 10 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 2 months ago
Stochastic training of a biologically plausible spino-neuromuscular system model
A primary goal of evolutionary robotics is to create systems that are as robust and adaptive as the human body. Moving toward this goal often involves training control systems tha...
Stanley Phillips Gotshall, Terence Soule
ESANN
2008
14 years 10 days ago
Word recognition and incremental learning based on neural associative memories and hidden Markov models
Abstract. An architecture for achieving word recognition and incremental learning of new words in a language processing system is presented. The architecture is based on neural ass...
Zöhre Kara Kayikci, Günther Palm
ISNN
2005
Springer
14 years 4 months ago
Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree
Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything)...
Yuehui Chen, Ajith Abraham, Ju Yang
APIN
1998
139views more  APIN 1998»
13 years 10 months ago
Evolutionary Learning of Modular Neural Networks with Genetic Programming
Evolutionary design of neural networks has shown a great potential as a powerful optimization tool. However, most evolutionary neural networks have not taken advantage of the fact ...
Sung-Bae Cho, Katsunori Shimohara