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Water quality early-warning model based on support vector machine optimized by rough set algorithm
LIU Shuang-yin, XU Long-qin, LI Dao-liang
Systems Engineering - Theory & Practice ›› 2015, Vol. 35 ›› Issue (6) : 1617-1624.
PDF(1135 KB)
PDF(1135 KB)
Water quality early-warning model based on support vector machine optimized by rough set algorithm
A new early warning model of water quality, combining rough set (RS) and support vector machine (SVM), is presented to improve the prediction precision affected by mass coupling factors, complex mode and information loss. Firstly, a core warning set based on 5 factors is obtained by using RS to deduct the redundant and disturbed properties from the initial set based on 14 factors. Consequently, the early warning model of water quality based on RS-SVM is built up by the core warning set. The experimental results show that our method improves the precision to more than 91% in any warning level by using the water quality data obtained from Yixing, Jiangsu province. Compared with the standard SVM and BP neural networks, the new model not only has effectiveness of calculation and prediction, but also provides warning results with practicality. This model demonstrates a new thought of early warning on intensive aquaculture water quality.
support vector machine / rough set / early-warning mode / attribute reduction {{custom_keyword}} /
[1] Koyuncugil A S, Ozgulbas N. Financial early warning system model and data mining application for risk detection[J]. Expert Systems with Applications, 2012, 39(6): 6238-6253.
[2] 王禾军, 邓飞其. 基于模糊最小二乘支持向量机的区域粮食安全性预警分析[J]. 农业工程学报, 2011, 27(5): 190-194.Wang Hejun, Deng Feiqi. Analysis on region grain security warning based on fuzzy least squares support vector machines[J]. Transactions of the Chinese Society of Agricultural Engineering, 2011, 27(5): 190-194.
[3] 宋戈, 连臣. 黑龙江省耕地资源安全预警分析及预警系统的构建[J]. 农业工程学报, 2012, 28(6): 247-252.Song Ge, Lian Chen. Analysis and system construction of safety early warning for cultivated land resources in Heilongjiang province[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(6): 247-252.
[4] Lopez V F, Medina S L, de Paz J F. Taranis: Neural networks and intelligent agents in the early warning against floods[J]. Expert Systems with Applications, 2012, 39(11): 10031-10037.
[5] Yao Z H, Fei M R, Qu B D. Evolving neural networks for forecasting and early warning red tide and blue-green alga disaster[J]. Dynamics of Continuous Discrete and Impulsive Systemsseries A-Mathematical Analysis, 2006(13): 241-247.
[6] 陈弘扬, 任华堂, 徐世英, 等.淮南市水厂取水口水质指标预警研究[J].北京大学学报(自然科学版), 2012, 48(3): 469-474.Chen Hongyang, Ren Huatang, Xu Shiying, et al. Water quality early warning research of water intakes in Huainan[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2012, 48(3): 469-474.
[7] 凌同华, 廖艳程, 张胜.岩体爆破震动损伤评估的多元判别分析模型[J].中南大学学报(自然科学版), 2010, 41(1): 322-327.Ling Tonghua, Liao Yancheng, Zhang Sheng. Safety criterion method of rock blasting vibration damnification based on multivariant discriminant analysis model[J]. Journal of Central South University (Science and Technology), 2010, 41(1): 322-327.
[8] 杨迎心, 冯志勇, 饶国政, 等.基于模糊综合评价构建物流运输预警模型[J].计算机应用, 2011, 31(10): 2844-2848.Yang Yingxin, Feng Zhiyong, Rao Guozheng, et al. Early-warning model of logistics transport based on fuzzy comprehensive evaluation[J]. Journal of Computer Applications, 2011, 31(10): 2844-2848.
[9] 张立军, 刘菊红, 刘丹.上市公司财务危机预警的Logistic回归分析[J].南昌大学学报(理科版), 2007, 31(3): 242-245.Zhang Lijun, Liu Juhong, Liu Dan. Financial crisis early warning of the listed company based on logistic regression analysis in China[J]. Journal of Nanchang University (Natural Science), 2007, 31(3): 242-245.
[10] 王伟, 沈振中, 李桃凡.遗传算法与自适应粒子群算法耦合的大坝安全预警评价模型[J].岩土工程学报, 2009, 31(8): 1242-1247.Wang Wei, Shen Zhenzhong, Li Taofan. Safety early warning evaluation model for dams based on coupled method of genetic algorithm and adapting particle swarm optimization algorithm[J]. Chinese Journal of Geotechnical Engineering, 2009, 31(8): 1242-1247.
[11] Vapnik V N. Statistical learning theory[M]. New York: John Wiley Sons, 1998.
[12] Ahn J J, Oh K J, Kim T Y, et al. Usefulness of support vector machine to develop an early warning system for financial crisis[J]. Expert Systems with Applications, 2011, 38(4): 2966-2973.
[13] Wan C F, Mita A. Early warning of hazard for pipelines by acoustic recognition using principal component analysis and one-class support vector machines[J]. Smart Structures and Systems, 2010, 6(4): 405-421.
[14] Walczak B, Massart D L. Rough sets theory[J]. Chemometrics and Intelligent Laboratory Systems, 1999, 47(1): 1-19.
[15] Zhang X Y, Zhou J Z, Guo J. Vibrant fault diagnosis for hydroelectric generator units with a new combination of rough sets and support vector machine[J]. Expert Systems with Applications, 2012, 39(3): 2621-2628.
[16] Li T S. Applying wavelets transform, rough set theory and support vector machine for copper clad laminate defects classification[J]. Expert Systems with Applications, 2009, 36(3): 5822-5829.
[17] Pawlak Z. Rough set[J]. International Journal of Computer and Information Sciences, 1982, 11: 341-356.
[18] Pawlak Z. Rough set approach to knowledge-based decision support[J]. European Journal of Operational Research, 1997, 99(1): 48-57.
[19] 张清华, 王国胤, 肖雨.粗糙集的近似集[J].软件学报, 2012, 23(7): 1745-1759.Zhang Qinghua, Wang Guoyin, Xiao Yu. Approximation sets of rough sets[J]. Journal of Software, 2012, 23(7): 1745-1759.
[20] 王国胤. Rough集理论与知识获取[M].西安: 西安交通大学出版社, 2001.Wang Guoyin. Rough set theory and knowledge discovery[M]. Xi'an: Xi'an Jiaotong University Press, 2001.
[21] Sahak R, Mansor W, Lee Y K, et al. Choice for a support vector machine kernel function for recognizing asphyxia from infantcries[C]// Industrial Electronics Applications, Kuala Lumpur: ISIEA, 2009: 675-678.
[22] GB3838-2002. 地表水环境质量标准[S]. 2004. GB3838-2002. Environment quality standard for surface water[S]. 2004.
[23] GB11607-89. 渔业水质标准[S]. 1989. GB11607-89. Water quality standard for fisheries[S]. 1989.
[24] NY 5052-2001. 无公害食品海水养殖用水水质[S]. 2001. NY 5052-2001. The pollution-free food —— Water quality of mariculture[S]. 2001.
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