首页|Dalian Minzu University Reports Findings in Machine Learning (Significant durati on prediction of seismic ground motions using machine learning algorithms)
Dalian Minzu University Reports Findings in Machine Learning (Significant durati on prediction of seismic ground motions using machine learning algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting from Liaoning, People's Republic of Chin a, by NewsRx journalists, research stated, "This study aims to predict the signi ficant duration (D5-75, D5-95) of seismic motion by employing machine learning a lgorithms. Based on three parameters (moment magnitude, fault distance, and aver age shear wave velocity), two additional parameters(fault top depth and epicente r mechanism parameters) were introduced in this study." The news correspondents obtained a quote from the research from Dalian Minzu Uni versity, "The XGBoost algorithm is utilized for characteristic parameter optimiz ation analysis to obtain the optimal combination of four parameters. We compare the prediction results of four machine learning algorithms (random forest, XGBoo st, BP neural network, and SVM) and develop a new method of significant duration prediction by constructing two fusion models (stacking and weighted averaging). The fusion model demonstrates an improvement in prediction accuracy and general ization ability of the significant duration when compared to single algorithm mo dels based on evaluation indicators and residual values." According to the news reporters, the research concluded: "The accuracy and ratio nality of the fusion model are validated through comparison with existing resear ch."
LiaoningPeople's Republic of ChinaAs iaAlgorithmsCyborgsEmerging TechnologiesMachine Learning
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