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Method for predicting corrosion rate of buried pipelines based on APSO-optimized LSSVM

A corrosion rate, buried pipeline technology, applied in the field of buried pipeline corrosion rate prediction, can solve the problem of time-consuming calculation

Inactive Publication Date: 2018-06-26
FUZHOU UNIV
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Problems solved by technology

However, in the process of SVM modeling, it is necessary to solve the quadratic programming problem. When the number of training samples is large, the calculation is extremely time-consuming.

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  • Method for predicting corrosion rate of buried pipelines based on APSO-optimized LSSVM
  • Method for predicting corrosion rate of buried pipelines based on APSO-optimized LSSVM
  • Method for predicting corrosion rate of buried pipelines based on APSO-optimized LSSVM

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Embodiment Construction

[0061] Attached below figure 1 , the technical solution of the present invention is described in detail.

[0062] A method for predicting the corrosion rate of buried pipelines based on APSO-optimized LSSVM of the present invention, the method is applied in the corrosion rate prediction model of buried pipelines, the model structure is simplified, and the calculation speed of the model is accelerated. The method is implemented as follows:

[0063] Step S1, select water content, HCO 3 － Content, Cl － Content, SO 4 2－ The seven influencing factors of soil content, oxidation-reduction potential, pH value and soil resistivity are used as input variables;

[0064] Step S2, taking the buried gas pipeline as the research object, and obtaining sample data by testing the physical and chemical properties of the soil along the pipeline and detecting the pipeline;

[0065] Step S3, randomly select several sets of sample data as training samples, establish a buried pipeline corrosion...

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Abstract

The invention relates to a method for predicting a corrosion rate of buried pipelines based on an APSO-optimized LSSVM. The method is applied to the prediction of the corrosion rate of the buried pipelines based on an adaptive particle swarm optimization (APSO)-optimized least squares support vector machine (LSSVM). The method has a significant predictive effect on improving the corrosion rate ofthe buried pipelines. An LSSVM model has a faster learning speed in the modeling process. At the same time, the APSO is used for parameter optimization, which improves the prediction accuracy and generalization ability of the model. The availability in predicting the corrosion rate of the buried pipelines is very high.

Description

technical field [0001] The invention relates to a method for predicting corrosion rate of buried pipelines based on LSSVM optimized by APSO. Background technique [0002] Buried oil and gas pipelines will leak oil and gas due to corrosion and perforation after running for a certain period of time, which will interfere with the normal operation of the entire transmission system. Therefore, it is urgent to predict the corrosion rate of buried oil and gas pipelines in order to provide an important basis for its detection and maintenance . At present, the prediction methods for the corrosion rate of buried oil and gas pipelines mainly include gray theory, regression model, neural network model, etc. [0003] However, the neural network modeling process still has disadvantages such as large amount of calculation and low learning efficiency. The support vector machine (SVM) is a new modeling method proposed in recent years, which has the characteristics of high computational eff...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N17/00G06F17/50
CPCG01N17/00G06F30/367
Inventor 赵超陈肇泉王斌
Owner FUZHOU UNIV
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