| 基于人工蜂群算法与BP神经网络的水质评价模型 |
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| 引用本文： | 苏彩红,向娜,陈广义,王飞.基于人工蜂群算法与BP神经网络的水质评价模型[J].环境工程学报,2012,6(2):699-704. |
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| 作者姓名： | 苏彩红 向娜 陈广义 王飞 |
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| 作者单位： | 1. 佛山科学技术学院自动化系,佛山,528000
2. 华南理工大学自动化科学与工程学院,广州,510641 |
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| 基金项目： | 佛山市科技发展专项基金（2009033）；广东省2009度安全生产科技发展项目 |
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| 摘 要： | 针对BP网络水质评价模型的不足,引入人工蜂群(ABC)算法,将求解BP神经网络各层权值、阀值的过程转化为蜜蜂寻找最佳蜜源的过程,提出了一种新的结合人工蜂群算法的BP网络水质评价方法(ABC-BP)。并以2000—2006年渭河监测断面的10组实测数据作为测试样本对其水质进行了评价,实验结果表明该方法得到的水质评价结果准确,并具有很强的稳定性和鲁棒性。
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| 关 键 词： | 神经网络 人工蜂群(ABC)算法 水质评价 |
| 修稿时间： | 6/7/2011 12:00:00 AM |
Water quality evaluation model based on artificial bee colony algorithm and BP neural network |
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| Su Caihong,Xiang N,Chen Guangyi and Wang Fei.Water quality evaluation model based on artificial bee colony algorithm and BP neural network[J].Techniques and Equipment for Environmental Pollution Control,2012,6(2):699-704. |
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| Authors: | Su Caihong Xiang N Chen Guangyi and Wang Fei |
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| Institution: | 1 (1.Department of Electrical and Information Engineering,Foshan University,Foshan 528000,China; 2.Department of Automation Science and Engineering,South China University of Technology,Guangzhou 510641,China) |
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| Abstract: | Aimed at the shortage of BP neural network in water quality assessment model,the artificial bee colony(ABC) algorithm was introduced.Weight and threshold problem of BP neural network was transformed to the process of searching the best nectar for honey bees.An improved water quality evaluation method was put forward which combines artificial bee colony algorithm and BP neural network(ABC-BP).10 groups measured data of Weihe River in 2000—2006 year are used as the test samples and are evaluated.The experimental results indicate that the quality assessment values are accurate by using the proposed method,and the algorithm has strong stability and robustness. |
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| Keywords: | neural network artificial bee colony（ABC） algorithm water quality evaluation |
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