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An AIGA-WLSSVM based buried pipeline corrosion rate prediction method

A buried pipeline, corrosion rate technology, applied in prediction, computational model, biological model and other directions, can solve the problem of time-consuming calculation of SVM model, and achieve the effect of improving prediction accuracy and strong robust performance

Inactive Publication Date: 2019-01-29
FUZHOU UNIV
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Problems solved by technology

However, when the number of training samples is large, the SVM model calculation will become time-consuming

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  • An AIGA-WLSSVM based buried pipeline corrosion rate prediction method
  • An AIGA-WLSSVM based buried pipeline corrosion rate prediction method
  • An AIGA-WLSSVM based buried pipeline corrosion rate prediction method

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Embodiment Construction

[0051] The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings.

[0052] The invention provides a method for predicting the corrosion rate of buried pipelines based on AIGA-WLSSVM, which effectively improves the calculation efficiency of the model, and adopts the AIGA method to optimize the model parameters, which further improves the prediction accuracy of the model. The method is implemented as follows:

[0053] In step S1, the pipeline is subject to many corrosion factors in the soil, and each factor interacts with each other, and has a complex nonlinear correlation. This chapter selects moisture content, HCO 3 － Content, Cl － Content, SO 4 2－Seven influencing factors such as content, redox potential, pH value and soil resistivity are used as input variables;

[0054] Step S2, taking the buried gas pipeline as the research object, and obtaining sample data by testing the physical and chemical proper...

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Abstract

The invention relates to an AIGA-WLSSVM based buried pipeline corrosion rate prediction method. By combining AIGA with WLSSVM algorithm, the prediction accuracy of the model is improved effectively. Through modeling and forecasting the actual corrosion data of buried pipelines, it is proved that the prediction model of corrosion rate of buried pipelines established by this method is effective andreliable, which also provides theoretical basis for overhaul and replacement of buried pipelines.

Description

technical field [0001] The invention relates to a corrosion rate prediction method for buried pipelines based on AIGA-WLSSVM. 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 transportation system. Therefore, it is urgent to predict the corrosion rate of buried oil and gas pipelines in order to provide an important basis for their 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 and so on. [0003] However, the neural network modeling process still has shortcomings such as large amount of calculation and low learning efficiency. Support vector machine (SVM) is a new modeling method proposed in recent years. It has the characteristics of high computational efficiency, simp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06F17/50G06N3/00
CPCG06N3/006G06Q10/04G06Q50/06G06F30/20
Inventor 赵超王斌陈肇泉
Owner FUZHOU UNIV