A Particle Swarm Optimized Fuzzy Neural Network Fo
2016-08-23
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Since the excellent performances of treating non- obtained from PSO-FNN are much higher than the ones
linear data with self-learning capability, the neural networks obtained from NNs. To make this clearer, an illustrative (NNs) are wildly use in financial prediction problem. But the NNs example is also demonstrated in this study. More or less suffer from the slow convergence, "black-box" i.e., it is almost impossible to analysis them for how they work. The Fuzzy Neural Networks(FNN) allow to add rules to neural networks. This avoids the black-box but lacks of effective learning capability. To overcome these drawbacks, in this study a
linear data with self-learning capability, the neural networks obtained from NNs. To make this clearer, an illustrative (NNs) are wildly use in financial prediction problem. But the NNs example is also demonstrated in this study. More or less suffer from the slow convergence, "black-box" i.e., it is almost impossible to analysis them for how they work. The Fuzzy Neural Networks(FNN) allow to add rules to neural networks. This avoids the black-box but lacks of effective learning capability. To overcome these drawbacks, in this study a
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