Cyanobacterial bloom outbreak early warning method based on mutation theory and improved cuckoo algorithm

A technology of cyanobacteria bloom and catastrophe theory, applied in the field of prediction and early warning of cyanobacteria bloom, can solve the problems of slow convergence speed of intelligent algorithm, inability to fully reflect the suddenness of water bloom outbreak, and low prediction accuracy of the model, so as to speed up the optimization The effect of convergence speed

CN109858132AActive Publication Date: 2019-06-07BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2019-06-07

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Abstract

The invention provides a cyanobacterial bloom outbreak early warning method based on a mutation theory and an improved cuckoo algorithm, and belongs to the technical field of water environment prediction and early warning. The method comprises the steps of carrying out modeling on cyanobacteria growth nonlinear dynamics; optimizing and calibrating parameters in the cyanobacterial growth nonlinearkinetic model by utilizing an improved cuckoo algorithm and a Runge-Kutta method; converting the cyanobacteria growth nonlinear kinetic model into a cusp mutation theoretical model; determining a water bloom outbreak critical point according to a divergence set of the cusp mutation theoretical model; and finally, judging the outbreak of cyanobacterial bloom, and carrying out early warning. According to the invention, a method of combining a numerical method and an intelligent algorithm is adopted; and partial improvement is made on iterative optimization of an intelligent algorithm, the optimization convergence speed is increased, parameters are not simple isotropic random walk, the cyanobacteria growth nonlinear kinetic model is more universal and practical, bloom outbreak can be predicted in time, and a basis is provided for decision-making departments to formulate bloom prevention and control countermeasures.
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Description

technical field

[0001] The invention relates to a method for predicting and early warning of cyanobacteria bloom, which belongs to the technical field of water environment prediction and early warning. Specifically, according to the growth dynamics of cyanobacteria, the cusp catastrophe theory is used for mathematical modeling, and the improved cuckoo search algorithm is used for parameter calibration, so as to provide a new solution for water bloom prediction and early warning. Background technique

[0002] Water body water quality includes water body indicators such as physical factors, chemical elements and biological characteristics of water, and is an important reference factor for measuring the usability of water bodies to society. Eutrophication is a phenomenon in which the excessive content of plant nutrients such as nitrogen and phosphorus causes accelerated reproduction of primary producers such as cyanobacteria and other phytoplankton, which in turn causes water q...

Examples

Embodiment 1

[0102] Taking the data of a monitoring station of a natural lake in my country from 2009 to 2013 as an example, the method of the present invention is used to predict and warn of cyanobacteria blooms. The data mainly include chlorophyll concentration A(t), water temperature T(t), total phosphorus concentration TP(t), total nitrogen concentration TN(t) and other data.

[0103] Step 1, modeling nonlinear dynamics of cyanobacteria growth;

[0104] See formulas (1)-(3) in the detailed description.

[0105] Step 2, cyanobacteria growth nonlinear dynamics model parameter optimization rate determination;

[0106] In order to prevent the large difference between the data from affecting the final parameter optimization results, the measured data from 2009 to 2012 were grouped according to the data difference of nitrogen and phosphorus ratio, with 10 as a unit span. With the grouped data, the parameters in the formula (4) are calibrated using the parameter optimization calibration met...