Seismic Damage Prediction Method of Building Groups Based on a Two-stage Support Vector Machine
LIU Yanping
DONG Wei
HUANG Bishuang
LI Jin
YANG Fang
Abstract：In conventional seismic damage prediction of building groups, the researchers always make a simple analogy with existing data of damaged buildings. Due to the influence of special geological environment, particular earthquake scenarios, together with the errors in handiwork statistics, there are a certain amount of outliers in dataset. The random noise in the dataset will have a serious impact on prediction accuracy. Thus, this paper introduces a two-stage support vector machine method. In the first step, the authors add different weight values to normal data and outliers respectively. Then a weighted support vector machine is proposed to build the prediction model of building groups. By using a cross-validation approach, the paper empirically tests the proposed model on 640 buildings in Wenchuan earthquake. The results show that the proposed method can not only effectively detect the outliers, but also make a fast accurate prediction. It is capable to be applied to the actual seismic damage prediction of urban buildings.
Keywords：Building groupsSeismic damage predictionSupport vector machineCross-validation
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 107-113 )