基于多元时序分析的水华预测及因素分析方法

doi:10.3969/j.issn.0438-1157.2013.12.056

化工学报 ›› 2013, Vol. 64 ›› Issue (12): 4649-4655.DOI: 10.3969/j.issn.0438-1157.2013.12.056

基于多元时序分析的水华预测及因素分析方法

王立¹, 刘载文¹, 吴成瑞², 华伟³, 张雪³

1. 北京工商大学计算机与信息工程学院, 北京 100048;
2. 北京安恒测试技术有限公司, 北京 100048;
3. 苏州市自来水公司, 江苏苏州 215012

收稿日期:2013-08-13 修回日期:2013-08-23 出版日期:2013-12-05 发布日期:2013-12-05
通讯作者: 刘载文
作者简介:王立（1983- ），女，博士研究生，讲师。
基金资助:
北京市自然科学基金重点项目（8101003）；江苏省水利厅科技项目（2011014）；北京工商大学青年教师科研启动基金项目（QNJJ2012-21）。

Water bloom prediction and factor analysis based on multidimensional time series analysis

WANG Li¹, LIU Zaiwen¹, WU Chengrui², HUA Wei³, ZHANG Xue³

1. School of Computer & Information Engineering, Beijing Technology & Business University, Beijing 100048, China;
2. Anheng Group, Beijing 100048, China;
3. Suzhou City Water Company Limited, Suzhou 215012, Jiangsu, China

Received:2013-08-13 Revised:2013-08-23 Online:2013-12-05 Published:2013-12-05
Supported by:
supported by the Key Project of Beijing Natural Science Foundation (8101003) and Jiangsu Provincial Water Resources Department Science and Technology Project (2011014).

摘要/Abstract

摘要： 在水华防治工作中，水华预测一直都是一个难点，为了解决由于水华生成过程中多种特征因素间的交互影响建模困难，现有的水华预测方法预测结果还不够准确，以及不同影响因素与水华发生的相关性程度的判定等问题，采用多元时间序列分析技术，研究多特征因素的水华预测及因素分析方法，通过对水华生成过程中的特征因素时序建模分析，提出多重潜周期多元自回归模型，给出了基于多元周期平稳时序分析的水华预测以及因素分析结果。采用本文方法及传统方法分别对江苏太湖水华特征因素监测数据进行建模预测，结果表明，基于本文方法的水华特征因素预测结果与实测结果更相符、预测平均误差绝对值更小。

关键词: 预测, 模型, 参数估值, 水华, 时间序列, 因素分析

Abstract: In water bloom prevention and control,water bloom prediction is always a difficult problem. This paper proposes a new water bloom prediction method based on multiple characteristic factors time series analysis to take into account the integrated effect of multiple characteristic factors along with the periodicity and random effect of environmental variables,to solve the problem that existing bloom prediction is not accurate enough,and to analyze the correlation between influential factors and water bloom.A multidimensional hidden periodic-auto regression (MHPAR) model is put forward based on the characteristic factors time series.A water bloom prediction method and an influential factors analysis method are put forward by using multidimensional period stationary time series analysis.Comparing the proposed model with other traditional time series models,such as auto regression (AR) model,hidden periodic-auto regression (HPAR) model and multidimensional auto regression (MAR) model,it has been found that multidimensional hidden periodic-auto regression model is useful and accurate for establishing multiple characteristic factors time series of water bloom.

Key words: prediction, model, parameter estimation, water bloom, time series, factor analysis

中图分类号:

TQ019

王立, 刘载文, 吴成瑞, 华伟, 张雪. 基于多元时序分析的水华预测及因素分析方法[J]. 化工学报, 2013, 64(12): 4649-4655.

WANG Li, LIU Zaiwen, WU Chengrui, HUA Wei, ZHANG Xue. Water bloom prediction and factor analysis based on multidimensional time series analysis[J]. CIESC Journal, 2013, 64(12): 4649-4655.

参考文献 20

[1]	David A Carona, Marie-Eve Garneaua, Erica Seuberta. Harmful algae and their potential impacts on desalination operations off southern California[J].Water Research, 2010, 44 (2):385-416
[2]	Wang Xiaoyi (王小艺), Tang Lina (唐丽娜), Liu Zaiwen (刘载文).Formation mechanism of cyanobacteria bloom in urban lake reservoir[J].CIESC Journal (化工学报), 2012, 63 (5):1492-1497
[3]	Wang Xiaoyi (王小艺), Tang Lina (唐丽娜), Liu Zaiwen (刘载文).Research on the fuzzy petri net optimization modeling of water bloom formation process[J].Acta Electronica Sinica (电子学报), 2013, 41 (1):68-71
[4]	Hao Qiwen (郝启文), Wang Xiaoyi (王小艺), Xu Jiping (许继平).Information system for water quality monitoring of lakes and reservoirs and water-bloom early-warning[J].Computer Engineering (计算机工程), 2013, 39 (1):287-293
[5]	Dong Shuoqi (董硕琦), Liu Zaiwen (刘载文), Wang Xiaoyi (王小艺).Intelligent agent modeling and simulating of algal bloom formation mechanism[J].Journal of Jiangnan University:Natural Science Edition (江南大学学报), 2012, 11 (4):412-417
[6]	Wang Xiaoyi (王小艺), Zhao Xiaoping (赵晓平), Liu Zaiwen (刘载文).Comprehensive mechanism modeling on city lake cyanobacteria bloom formation[J].Acta Scientiae Circumstantiae (环境科学学报), 2012, 32 (7):1677-1683
[7]	Du Wenli (杜文莉), Guan Zhenqiang (官振强), Qian Feng (钱锋).Dynamic soft sensor series error modeling based on time compensation[J].CIESC Journal (化工学报), 2010, 61 (2):439-443
[8]	Ma Yong (马勇), Huang Dexian (黄德先), Jin Yihui (金以慧).Discussion about dynamic soft-sensing modeling[J].Journal of Chemical Industry and Engineering (China) (化工学报), 2005, 56 (8):1516-1519
[9]	Liu Zaiwen (刘载文), Wang Xiaoyi (王小艺), Cui Lifeng (崔莉凤).Computing method for unmeasurable process parameters[J].Journal of Tsinghua University (清华大学学报), 2007, 47 (S2):1742-1746
[10]	Shuhaibar B N, Riffat R.A process for harmful algal bloom location prediction using GIS and trend analysis for the terrestrial waters of Kuwait[J].Journal of Environmental Informatics, 2008, 12 (2):160-173
[11]	Chen Yunfeng, Yin Fucai, Lu Genfa.A catastrophe model for water bloom prediction:a case study of China's Lake Chaohu[J].Human and Ecological Risk Assessment, 2007, 13 (4):914-921
[12]	Liu Zaiwen (刘载文), Yang Bin (杨斌), Huang Zhenfang (黄振芳).Water-bloom short-time predicting system of Beijing based on neural network[J].Computer Engineering and Applications (计算机工程与应用), 2007, 43 (28):243-245
[13]	Liu Zaiwen (刘载文), Li Mengxun (李梦寻), Wang Xiaoyi (王小艺).The method of mid-term and short-term prediction for water bloom based on LSSVM and RBFNN[J].Computers and Applied Chemistry (计算机与应用化学), 2012, 29 (10):1189-1194
[14]	Zhu Shiping (朱世平), Liu Zaiwen (刘载文), Wang Xiaoyi (王小艺).Gray theory and neural network prediction for water bloom[J].Computer Engineering and Applications (计算机工程与应用), 2011, 47 (13):231-233
[15]	Liu Zaiwen (刘载文), Wu Qiaomei (吴巧媚), Wang Xiaoyi (王小艺).Algae growth modeling based on optimization theory and application to water-bloom prediction[J].Journal of Chemical Industry and Engineering (China) (化工学报), 2008, 59 (7):1869-1873
[16]	Victor Chan, William Meeker.Time series modeling of degradation due to outdoor weathering[J].Communications in Statistics—Theory and Methods, 2008, 37 (3):408-424
[17]	Wang Li (王立), Li Xiaoyang (李晓阳), Jiang Tongmin (姜同敏).Life prediction of product based on degradation amount distribution time series analysis[J].Journal of Beijing University of Aeronautics and Astronautics (北京航空航天大学学报), 2011, 37 (4):492-498
[18]	Wang Li, Zhang Huiyan, Xue Hong.Fault prognostics and reliability estimation of DC motor using time series analysis based on degradation data[J].Journal of Theoretical and Applied Information Technology, 2012, 45 (2):568-572
[19]	McGovern Amy, Rosendahl Derek H, Brown Rodger A. Identifying predictive multi-dimensional time series motifs:an application to severe weather prediction[J].Data Mining and Knowledge Discovery, 2011, 22 (1/2):232-258
[20]	Yang Shuzi (杨叔子), Wu Ya (吴雅), Xuan Jianping (轩建平).Time Series Analysis in Engineering Application (时间序列分析的工程应用)[M].Wuhan:Huazhong University of Science & Technology Press, 2007

基于多元时序分析的水华预测及因素分析方法

Water bloom prediction and factor analysis based on multidimensional time series analysis

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