| 基于IPSO和BP神经网络的光学字符识别 |
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| 引用本文： | 张建军,杜莉. 基于IPSO和BP神经网络的光学字符识别[J]. 煤炭技术, 2010, 29(12) |
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| 作者姓名： | 张建军 杜莉 |
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| 基金项目： | 北京市属市管高等学校人才强教计划资助项目 |
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| 摘 要： | 随着信息系统的广泛应用,光学字符识别(Optical Character Recognition,OCR)技术取的了长足的进步。通过引入模拟退火算法、"交叉算子"和"变异算子",提出了一种改进粒子群优化算法(Improved Particle Swarm Optimization,IPSO)对神经网络的参数进行优化计算。试验证明,OCR方法具有很高的识别效率。
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| 关 键 词： | 改进的粒子群优化 BP神经网络 光学字符识别 |
Optical Character Recognition Based on IPSO Arithmetic and BP Neural Network |
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| ZHANG Jian-Jun,DU Li. Optical Character Recognition Based on IPSO Arithmetic and BP Neural Network[J]. Coal Technology, 2010, 29(12) |
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| Authors: | ZHANG Jian-Jun DU Li |
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| Abstract: | Optical character recognition technology got great development due to extensive application of information systems.SA,"intercross operator " and "aberrance operator" are combined to improve PSO's performance,a new IPSO(Improved Particle Swarm Optimization) is formed to optimize the parameters of BP neural network.Experiments shows the arithmetic has wonderful performance in OCR. |
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| Keywords: | improved particle swarm optimization BP neural networks optical character recognition |
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