| 粒子群优化在股指预测中的应用 |
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| 引用本文： | 田军,钟志明. 粒子群优化在股指预测中的应用[J]. 喀什师范学院学报, 2009, 30(3): 59-61 |
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| 作者姓名： | 田军 钟志明 |
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| 作者单位： | 1. 新疆医科大学,医学工程技术学院,乌鲁木齐,830011
2. 喀什师范学院,信息工程技术系,新疆,喀什,844007 |
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| 摘 要： | BP神经网络由于自身的缺陷，导致训练时间长且易于陷入局部极小点，易导致股指预测精度不高．将粒子群优化算法用于神经网络的学习训练，可改善它原有的缺陷，并用于对股指的预测．实验结果表明，与BP神经网络相比，基于粒子群优化的神经网络对股指的预测精度更高．
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| 关 键 词： | 粒子群优化 神经网络 股指预测 |
The Application of Particle Swarm Optimization to Stock Price Forecasting |
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| TIAN Jun,ZHONG Zhi-ming. The Application of Particle Swarm Optimization to Stock Price Forecasting[J]. Journal of Kashgar Teachers College, 2009, 30(3): 59-61 |
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| Authors: | TIAN Jun ZHONG Zhi-ming |
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| Affiliation: | TIAN Jun, ZHONG Zhi-ming( 1. College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, Xinjiang, China ; 2. Department of Information and Engineering, Kashgar Teachers College, Kashgar 844007, Xinjiang, China) |
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| Abstract: | BP neural network exists some shortcomings that it takes longer than normal to train and is inclined to trap in local minium. So it causes forecast precision of the stock index lower finally. In this paper, particle swarm optimization algorithm, which improves its existing defects and forecasts the stock index, is applied to the learning training of neural network, The experimental results show that this approach is more efficient than BP algorithm in prediction of the stock index. |
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| Keywords: | Particle swarm optimization Neural network Stock index forecast |
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