| 基于变异的紧凑遗传算法在农药检测中的应用 |
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| 引用本文： | 孟姣,佟国香.基于变异的紧凑遗传算法在农药检测中的应用[J].电子科技,2016,29(2):1. |
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| 作者姓名： | 孟姣 佟国香 |
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| 作者单位： | (1.上海理工大学 光电信息与计算机工程学院,上海 200093;2.上海市现代光学系统重点实验室,上海 200093) |
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| 基金项目： | 国家863计划基金资助项目(2006AA03Z348);教育部科学技术研究重点基金资助项目(2007033);上海市教育委员会科研创新重点基金资助项目(10ZZ94;12YZ094);上海自然科学基金资助项目(12ZR1420800) |
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| 摘 要： | 为了简化农药检测的预测模型,提高模型预测精度,采用红外光谱技术结合基于变异的紧凑遗传算法对波长变量进行筛选,一定程度上减少了无信息变量和干扰变量。通过不同算法选择的波长变量建立预测模型,mCGA得到的预测均方根偏差平均值是0.198,而与mCGA比较的紧凑遗传算法、简单遗传算法得到的预测均方根偏差平均值分别为0.241、0.289,mCGA具有最小误差。结果表明,采用mCGA进行变量选择,能有效提高模型收敛速度及模型准确度,实现农药含量快速高效的检测。
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| 关 键 词： | 农药检测 红外光谱 基于变异的紧凑遗传算法 变量选择 |
Mutation-based Compact Genetic Algorithm in Pesticide Detection |
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| MENG Jiao,TONG Guoxiang.Mutation-based Compact Genetic Algorithm in Pesticide Detection[J].Electronic Science and Technology,2016,29(2):1. |
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| Authors: | MENG Jiao TONG Guoxiang |
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| Affiliation: | (1.School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;
2.Shanghai Key Laboratory of Modern Optical Systems,Shanghai 200093,China) |
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| Abstract: | In order to simplify the forecasting model of pesticide detection,and to improve the prediction accuracy of the detection model,this study uses the infrared spectroscopy technology and the mutation-based compact genetic algorithm (mCGA) to achieve the wavelength variable selection,and to a certain extent,reduce the non-information variables and disturbance variables.Wavelength variables are selected to build prediction model with different algorithms.The root mean square average of the prediction obtained is 0.198 by using mCGA,smaller than those by the compact genetic algorithm (CGA) and by the simple genetic algorithm (SGA) which are 0.241 and 0.289,respectively.The results show that the variable selection by means of mCGA can improve the convergence rate and accuracy of the model,and enable the detection of pesticide quickly and efficiently. |
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| Keywords: | pesticide detection infrared spectroscopy mCGA variable selection |
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