A Model of Predicting Corrosion Rate for Substation Grounding Grid Based on the Similarity and Support Vector Regression

Abstract:

In this paper, we proposed a training model to predict the corrosion rate for substation grounding grid based on the Similarity and Support Vector Regression (SSVR). In the proposed model, the effect of grounding grid corrosion rate was acted as a feature vector and processed by a dimensionless treatment. Then, the similarity between the feature vector of training terminal and index vector of actual site would be calculated. In the prediction of corrosion rate, the traditional Linear Average Method (LAM) to describe the nonlinear contribution has some fault defects. Therefore, we proposed the training model named SSVR. From the experimental results, the proposed SSVR can obtain better predicting performance than the traditional LAM.

• Periodical: Applied Mechanics and Materials (Volume 596)
• Pages: 271-275
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.596.271
• Online since: July 2014
• Authors: Jing Yi Du*, Juan Han, Yue Jiao Zhao, Wen Hui Liu
• Keywords: Grounding Grid Corrosion Rate, Support Vector Regression, Vector Similarity

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