Tatt Hee Oong

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This paper presents a new evolutionary approach called the hybrid evolutionary artificial neural network (HEANN) for simultaneously evolving an artificial neural networks (ANNs) topology and weights. Evolutionary algorithms (EAs) with strong global search capabilities are likely to provide the most promising region. However, they are less efficient in(More)
This brief presents a new ordering algorithm for data presentation of fuzzy ARTMAP (FAM) ensembles. The proposed ordering algorithm manipulates the presentation order of the training data for each member of a FAM ensemble such that the categories created in each ensemble member are biased toward the vector of the chosen input feature. Diversity is created(More)
This paper presents a new neural network architecture called the Multilayer Fuzzy ARTMAP (ML-FAM) together with the neighborhood learning algorithm and <i>N</i>-best rule for fast learning and testing in solving pattern classification problem. An analysis to the Fuzzy ARTMAP learning algorithm is studied to identify the weakness of it. ML-FAM uses layered(More)
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