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1 - 3 of 3
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Input-dependent neural network trained by real-coded genetic algorithm and its industrial applications
Ling S., Leung F., Lam H. Soft Computing 11(11): 1033-1052, 2007. Type: Article
Neural networks (NNs) map input to output using neuron elements inspired by the human nervous system. Conventionally, the parameters of the networks are fixed after the training process, independent of the input data....
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Jan 11 2008 |
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 Stanford WebBase components and applications
Cho J., Garcia-Molina H., Haveliwala T., Lam W., Paepcke A., Raghavan S., Wesley G. ACM Transactions on Internet Technology 6(2): 153-186, 2006. Type: Article
Stanford WebBase, a Web search and retrieval tool, has been used by scores of research and teaching organizations, mostly for investigations into Web topology and linguistic content analysis. This paper describes the WebBase system, pr...
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Oct 10 2006 |
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Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks
Lähdesmäki H., Hautaniemi S., Shmulevich I., Yli-Harja O. Signal Processing 86(4): 814-834, 2006. Type: Article
Probabilistic Boolean networks (PBNs) and dynamic Bayesian networks (DBNs) are two state-of-the-art model classes for representing genetic network modeling. Investigating relationships between the models (more accurately, expressing a ...
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Aug 25 2006 |
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