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Neural networks have been widely used to solve financial distress problems because of their excellent performances of treating non-linear data with self-learning capability. However, the shortcoming of NNs is also significant due to the "black box" syndrome. Moreover, in many situations NNs more or less suffer from the slow convergence and occasionally(More)
To design a multi-population adaptive genetic BP algorithm, crossover probability and mutation probability are self-adjusted according to the standard deviation of population fitness in this paper. Then a hybrid model combining Fuzzy Neural Network and multi-population adaptive genetic BP algorithm—Adaptive Genetic Fuzzy Neural Network (AGFNN) is proposed(More)
  • Zhibin Xiong
  • 2008
Neural networks (NNs) have been widely used to predict financial distress because of their excellent performances of treating non-linear data with self-learning capability. However, common neural networks often suffer from long convergent processes and occasionally involve in a local optimal solution that more or less limited their applications in practice.(More)
  • Zhibin Xiong
  • 2008
Neural networks (NNs) have been widely used to predict financial distress because of their excellent performances of treating non-linear data with self-learning capability. However, the shortcoming of NNs is also significant due to a ldquoblack boxrdquo syndrome. Moreover, in many situations NNs more or less suffer from the slow convergence and occasionally(More)
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