[1]花晨芝,赵 凌,宋建军,等.粒子群算法选择特征波长在紫外光谱检测COD中的研究[J].西华师范大学学报(自然科学版),2019,40(01):81-85.[doi:10.16246/j.issn.1673-5072.2019.01.015]
 HUA Chenzhi,ZHAO Ling,SONG Jianjun,et al.Selection of Wavelength for UV-visible SpectroscopyBased on BLS Combined with PSO[J].Journal of China West Normal University(Natural Sciences),2019,40(01):81-85.[doi:10.16246/j.issn.1673-5072.2019.01.015]
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粒子群算法选择特征波长在紫外光谱检测COD中的研究

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《西华师范大学学报(自然科学版)》[ISSN:1673-5072/CN:51-1699/N]

卷:
40
期数:
2019年01期
页码:
81-85
栏目:
出版日期:
2019-03-20

文章信息/Info

Title:

Selection of Wavelength for UV-visible SpectroscopyBased on BLS Combined with PSO

作者:

花晨芝1赵  凌1宋建军2袁丽娟1

(1.四川师范大学 数学与软件科学学院, 成都  610068;2.成都文理学院 数学与统计学院, 成都  610401)

Author(s):

HUA Chenzhi1ZHAO Ling1SONG Jianjun2YUAN Lijuan1

(1.College of Mathematics and Software Science,Sichuan Normal University,Chengdu Sichuan 610068,China; 2.College of Machematic and Statistics,Chengdu College of Arts and Sciences,Chengdu Sichuan 610401,China)

关键词:

粒子群算法偏最小二乘化学需氧量特征波长紫外吸收法

Keywords:

Particle Swarm Optimizationpartial least-square regressionchemical oxygen demandcharacteristic wavelengthUV-visible spectroscopy

分类号:
TP212;X832
DOI:
10.16246/j.issn.1673-5072.2019.01.015
文献标志码:
A
摘要:

为简化紫外光谱测化学需氧量检测模型,提高模型的预测精度,将偏最小二乘算法与粒子群算法相结合,优化了对紫外光谱特征波长的选择。通过建模和实验分析表明:使用该方法对特征波长进行选取,偏最小二乘回归模型在均方误差意义下达到最优,平均相对误差在5%以内,而且预测精度明显优于未经粒子群算法选取波长的偏最小二乘回归模型。

Abstract:

To simplify the detection of chemical oxygen demand in UV-visible spectroscopy and improve the prediction accuracy of the model,a partial least squares method is combined with a particle swarm optimization to optimize the selection of characteristic wavelength of the ultraviolet spectrum.The experimental analysis shows that to select the characteristic wavelength by this method,the partial least-squares regression model is optimal in the sense of mean square error;the average relative error is within 5%;the prediction accuracy is obviously better than that without the particle swarm optimization.

相似文献/References:

[1]周洋,潘大志.求解0-1背包问题的贪心优化粒子群算法[J].西华师范大学学报(自然科学版),2018,39(03):319.[doi:10.16246/j.issn.1673-5072.2018.03.016]
 ZHOU Yang,PAN Dazhi.The Greedy Optimization strategy of Particle SwarmOptimization Algorithm for Solving 0-1 Knapsack Problem[J].Journal of China West Normal University(Natural Sciences),2018,39(01):319.[doi:10.16246/j.issn.1673-5072.2018.03.016]

备注/Memo

备注/Memo:

收稿日期:2018-07-31
基金项目:四川省教育厅科研项目重点项目 (13sa0137)
作者简介:花晨芝(1995—),女,四川南充人,硕士研究生,主要从事水质传感器的算法研究。E-mail:1170214640@qq.com
通信作者:赵  凌(1964—),女,辽宁本溪人,教授,硕士生导师,主要从事应用统计方面的研究。E-mail:514460911@qq.com

更新日期/Last Update: 2018-12-20