| 引用本文: | 罗 飞,毛宗源,莫鸿强,卢子广.Q学习对制糖结晶遗传神经网络收敛性的改进(英文)[J].控制理论与应用,2001,18(6):887~890.[点击复制] |
| LUO Fei,MAO Zong-yuan,MO Hong-qiang,LU Zi-guang.Improving the Convergence of the Genetic Neural Network in the Crystallizing of Sugar Using Q-Learning[J].Control Theory and Technology,2001,18(6):887~890.[点击复制] |
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| Q学习对制糖结晶遗传神经网络收敛性的改进(英文) |
| Improving the Convergence of the Genetic Neural Network in the Crystallizing of Sugar Using Q-Learning |
| 摘要点击 1549 全文点击 1821 投稿时间：2000-02-23 修订日期：2001-02-14 |
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| DOI编号 10.7641/j.issn.1000-8152.2001.6.016 |
| 2001,18(6):887-890 |
| 中文关键词 Q学习 遗传神经网络 收敛性 甘蔗制糖 |
| 英文关键词 Q learning genetic neural network convergence cane sugar |
| 基金项目 |
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| 中文摘要 |
| 采用多层前馈遗传神经网络模型对甘蔗制糖结晶速度进行学习和预测, 并针对该模型存在的计算量大, 收敛慢的问题, 采用具有强化作用的Q学习确定遗传算法的变异概率, 以提高学习的收敛速度, 仿真结果表明了该方法的有效性. |
| 英文摘要 |
| The crystallizing speed of cane sugar is learned and predicted by the model of feedforward neural network using genetic algorithms. To counter the problem in the model which needs a lot of calculations but has slow speed of convergence, we use Q learning with reinforcement to decide on the variation probability of genetic algorithms and to increase the convergence speed of learning. The results of the simulation show the effectiveness of the method. |
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