首页|New Findings from Institute of Disaster Prevention in the Area of Machine Learni ng Described (Gsbbo: a High-precision Method for Stress Tensor Inversion and Its Application At the Great Wall Station In Antarctica)
New Findings from Institute of Disaster Prevention in the Area of Machine Learni ng Described (Gsbbo: a High-precision Method for Stress Tensor Inversion and Its Application At the Great Wall Station In Antarctica)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning. According to news reporting originatingfrom Hebei, People’s Republic of China, by NewsRx correspondents, research stated, “The currentstress tensor inversion method based on the focal mechanism cannot solve problems such as the interferenceof too many outliers on the results and the slow speed and low acc uracy caused by the excessivecomputation of the inversion process; therefore, w e propose a new stress tensor inversion method, GSBBO(grid search, boxplot and Bayesian optimization), which combines machine learning algorithms to sieve outoutlier data and improve the inversion speed and accuracy. The method first scre ens the focal mechanismdata via a grid search and boxplot, and this process eli minates the bias of the outliers on the results.”
HebeiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningInstitute of Disaster Prevent ion
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