Coastal water quality evaluation method based on two-classification support vector machines and particle swarm algorithm

A technology of support vector machine and particle swarm algorithm, applied in calculation, calculation model, computer parts, etc., can solve the problems of insufficient training samples, inability to guarantee generalization ability and prediction ability, insufficient calculation accuracy, etc., to achieve high efficiency, The effect of reducing blindness and inaccuracy and improving accuracy

Inactive Publication Date: 2013-01-30
CHANGZHOU UNIV
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Problems solved by technology

For the methods of comprehensive evaluation of seawater quality, early scholars at home and abroad mostly used methods such as comprehensive index method, fuzzy comprehensive evaluation method, fuzzy clustering method, etc., but these methods must presuppose some parameters of the model or subjective regulations: such as fuzzy comprehensive evaluation The weight of the water quality parameters should be given in the method; the membership function should be given in the fuzzy cluster analysis, etc., and the evaluation results are highly subjective.
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  • Coastal water quality evaluation method based on two-classification support vector machines and particle swarm algorithm
  • Coastal water quality evaluation method based on two-classification support vector machines and particle swarm algorithm
  • Coastal water quality evaluation method based on two-classification support vector machines and particle swarm algorithm

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[0026] In order to make the technical problems and technical solutions to be solved by the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0027] like figure 1 As shown, the present invention is based on two kinds of support vector machines and the offshore water quality evaluation method of particle swarm algorithm and comprises the following steps:

[0028] Step 1. Select offshore water quality evaluation factors as characteristic information, establish a sample data set, and normalize the characteristic information, complete the preprocessing of the characteristic information, and compose all the characteristic information into a characteristic vector.

[0029] Step 1 specifically includes the following two sub-steps: Step 1.1, selecting valid offshore water quality characteristic information. The selection of characteristic information is mainly based on the character...

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Abstract

The invention discloses a coastal water quality evaluation method based on two-classification support vector machines and a particle swarm algorithm. The coastal water quality evaluation method comprises the following steps of: S1, selecting a coastal water quality evaluation factor as feature information, constructing a sample data set, normalizing the feature information, preprocessing the feature information, and combining all feature information to form a feature vector; S2, determining a coastal water quality evaluation level, performing binary encoding on the coastal water quality evaluation level, and constructing a support vector machine network; S3, performing parameter optimization by the particle swarm algorithm, and obtaining an optimal vector parameter; S4, training each two-classification support vector machine in the support vector machine network according to the optimal vector parameter; and S5, inputting the trained support vector machine network into a sample set to be classified, obtaining a forecast result, and evaluating the level of coastal water quality. By the coastal water quality evaluation method, levels of various types of coastal water quality can be evaluated according to pollutant features of a selected coastal domain.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition and quality evaluation, and in particular relates to an evaluation method of offshore water quality based on a second-class support vector machine and a particle swarm algorithm. Background technique [0002] The ocean is an important water resource for the survival of the earth, but it is currently facing more and more serious water pollution problems. As an important content of environmental quality assessment, water environment quality assessment is one of the important means of environmental management. For the methods of comprehensive evaluation of seawater quality, early scholars at home and abroad mostly used methods such as comprehensive index method, fuzzy comprehensive evaluation method, fuzzy clustering method, etc., but these methods must presuppose some parameters of the model or subjective regulations: such as fuzzy comprehensive evaluation The weight of water quality pa...

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Application Information

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IPC IPC(8): G06K9/62G06N3/00
Inventor 倪彤光顾晓清张艳慧
Owner CHANGZHOU UNIV
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