Multi-dimensional cloud model-fuzzy support vector machine-based ecological risk evaluation method

A technology of fuzzy support vector and evaluation method, applied in computer parts, character and pattern recognition, instruments, etc., can solve problems such as difficulty in characterization

Active Publication Date: 2018-06-15
NANJING UNIV
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

From qualitative recognition to quantitative measurem

Method used

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  • Multi-dimensional cloud model-fuzzy support vector machine-based ecological risk evaluation method
  • Multi-dimensional cloud model-fuzzy support vector machine-based ecological risk evaluation method
  • Multi-dimensional cloud model-fuzzy support vector machine-based ecological risk evaluation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0070] Example: This example takes the ecological risk of persistent organic pollutants in the surface sediments of the tidal flats of the Yangtze River Estuary as a practical application

[0071] Taking the measured data of persistent organic pollutants in the tidal flat surface sediments of the Yangtze River Estuary as an example, DDTs, HCHs and PCBs were used as evaluation factors, and the multidimensional cloud model-fuzzy support vector machine method was used for ecological risk assessment.

[0072] (1) Measured data (ng / g)

[0073]

[0074]

[0075] n.d: not detected.

[0076] (2) Evaluation standard - marine sediment quality (GB18668-2002)

[0077]

[0078] (3) Range of evaluation indicators for each level of each evaluation factor

[0079]

[0080] (4) Cloud model parameters of each evaluation factor

[0081]

[0082] (5) Final evaluation result (C=10.2601, σ=3.9677)

[0083]

[0084]

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Abstract

The invention discloses a multi-dimensional cloud model-fuzzy support vector machine-based ecological risk evaluation method. The method comprises the following steps of: determining a plurality of evaluation factors and an evaluation standard, considering the plurality of evaluation factors as a plurality of attributes of a support vector machine sample, and dividing ecological risks into a plurality of grades according to the evaluation standard; determining model parameters according to a grading index; considering a super entropy as a product of a parameter k obeying normal distribution and an entropy; generating training samples, with a plurality of attributes, of each grade through a forward multi-dimensional normal cloud generator, and calculating certainty degrees of samples belonging to specific grades so as to generate a training sample set; carrying out model establishment and parameter optimization; selecting a Gaussian function as a kernel function; generating a pluralityof binary classifier by using a one-to-one method so as to form a multiclass classifier; carrying out parameter optimization by utilizing K-fold cross validation and a grid method so as to determine optimum parameters C and sigma; training samples by using the training sample set generated by the cloud generator and then establishing a model; and finally classifying measured data of a region by using the model, and judging an ecological risk grade of the region so as to realize comprehensive ecological risk evaluation under multiple factors.

Description

technical field [0001] The invention belongs to the ecological risk evaluation technology, in particular to an ecological risk evaluation method based on a multidimensional cloud model-fuzzy support vector machine. Background technique [0002] The rapid economic growth has brought more and more artificially synthesized compounds into the ecosystem, and the requirement of sustainable development urgently requires an effective method system to evaluate the risks of compounds in the environment. The concept of ecological risk assessment has been born only 20 years ago, and the relevant technical methods are still immature, and there are certain problems in application and practice. Therefore, it is urgent to improve the ecological risk assessment method and introduce new methods into the assessment system. need. [0003] Due to the nonlinear characteristics of the evaluation system, especially in multi-index decision-making problems, most evaluation models do not solve the no...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06K9/62
CPCG06Q10/0635G06F18/2411G06F18/214
Inventor 王栋倪玲玲吴剑锋王远坤吴吉春
Owner NANJING UNIV
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