The use of genetic algorithms and neural networks to approximate missing data in database

@article{Abdella2005TheUO,
  title={The use of genetic algorithms and neural networks to approximate missing data in database},
  author={Mussa Abdella and Tshilidzi Marwala},
  journal={IEEE 3rd International Conference on Computational Cybernetics, 2005. ICCC 2005.},
  year={2005},
  pages={207-212}
}
Missing data creates various problems in analysing and processing data in databases. In this paper we introduce a new method aimed at approximating missing data in a database using a combination of genetic algorithms and neural networks. The proposed method uses genetic algorithm to minimise an error function derived from an auto-associative neural network. Multi-layer perceptron (MLP) and radial basis function (RBF) networks are employed to train the neural networks. Our focus also lies on the… CONTINUE READING

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