蓝藻生长时变系统非线性动力学分析及水华预测方法

doi:10.11949/j.issn.0438-1157.20161622

化工学报 ›› 2017, Vol. 68 ›› Issue (3): 1065-1072.DOI: 10.11949/j.issn.0438-1157.20161622

蓝藻生长时变系统非线性动力学分析及水华预测方法

王立, 高崇, 王小艺, 刘载文

北京工商大学计算机与信息工程学院, 北京 100048

收稿日期:2016-11-16 修回日期:2016-11-17 出版日期:2017-03-05 发布日期:2017-03-05
通讯作者: 王立,wangli@th.btbu.edu.cn
基金资助:
国家自然科学基金项目（51179002）；北京市市属高校创新能力提升计划项目（PXM2014_014213_000033）；北京市教委科技计划重点项目（KZ201510011011）；北京市教委科技计划一般项目（SQKM201610011009）。

Nonlinear dynamics analysis and water bloom prediction of cyanobacteria growth time variation system

WANG Li, GAO Chong, WANG Xiaoyi, LIU Zaiwen

School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China

Received:2016-11-16 Revised:2016-11-17 Online:2017-03-05 Published:2017-03-05
Contact: 10.11949/j.issn.0438-1157.20161622
Supported by:
supported by the National Natural Science Foundation of China (51179002),the Innovation Ability Promotion Project of Beijing Municipal Colleges and Universities (PXM2014_014213_000033),the Major Project of Beijing Municipal Education Commission Science and Technology Development Plans (KZ201510011011) and the General Project of Beijing Municipal Education Commission Science and Technology Development Plans (SQKM201610011009).

摘要/Abstract

摘要：

为解决现有蓝藻生长动力学模型难以有效描述实际水体中蓝藻生长时变系统的非线性动力学特性，导致水华预测准确性不高的问题，构建蓝藻摄食和营养盐循环模型，并考虑水温、光照等主要影响因素随时间变化对蓝藻生长的影响，进一步建立蓝藻生长时变系统非线性动力学模型，对其常值参数采用遗传算法与数值算法结合的方法进行优化率定，对其时变参数采用多元时序方法进行建模预测，根据分岔理论及时变系统理论分析水华暴发行为的非线性动力学机理，实现对蓝藻生长时变系统的水华预测。通过太湖流域监测实例表明，与现有研究相比，引入时变参数的蓝藻生长动力学模型更能反映蓝藻生长时变系统下水华暴发行为的非线性动力学特性，其水华预测结果更为准确。

关键词: 蓝藻, 时变系统, 水华, 非线性动力学, 预测, 模型

Abstract:

In order to solve the problem that the actual description of the water bloom behavior is not entirely conform to reality and water bloom prediction is not accurate enough by existing algae growth dynamics model due to the neglect of model parameters change with time, this paper builds cyanobacteria feeding and nutrient cycling model, and proposes algae growth dynamics model with time-varying parameters based on time variation influences of water temperature and illumination on model parameters. The calibration method for constant parameters of the model is optimized based on genetic and numerical algorithm. And the model time-varying parameters is modeled and predicted by multivariate time series method. Nonlinear dynamic mechanism of cyanobacteria bloom behavior is analyzed by bifurcation theory and time varying system theory, and then a new method of cyanobacteria bloom prediction is put forward. The monitoring data analysis of the Taihu River Basin in Jiangsu shows that cyanobacterial growth dynamics model with time-varying parameters can reflect nonlinear dynamic characteristics of cyanobacteria bloom behavior in cyanobacteria growth time-varying system. The model is more consistent with the actual situation, and cyanobacteria bloom prediction result is more accurate.

Key words: cyanobacteria, time varying system, water bloom, nonlinear dynamics, prediction, model

中图分类号:

TQ019

王立, 高崇, 王小艺, 刘载文. 蓝藻生长时变系统非线性动力学分析及水华预测方法[J]. 化工学报, 2017, 68(3): 1065-1072.

WANG Li, GAO Chong, WANG Xiaoyi, LIU Zaiwen. Nonlinear dynamics analysis and water bloom prediction of cyanobacteria growth time variation system[J]. CIESC Journal, 2017, 68(3): 1065-1072.

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蓝藻生长时变系统非线性动力学分析及水华预测方法

Nonlinear dynamics analysis and water bloom prediction of cyanobacteria growth time variation system

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