Full metadata record
DC FieldValueLanguage
dc.contributor.authorLin, Kuang Yien_US
dc.contributor.authorLin, Tzu Kangen_US
dc.contributor.authorLin, Yoen_US
dc.date.accessioned2020-05-05T00:01:31Z-
dc.date.available2020-05-05T00:01:31Z-
dc.date.issued2020-02-01en_US
dc.identifier.issn2092-7614en_US
dc.identifier.urihttp://dx.doi.org/10.12989/eas.2020.18.2.163en_US
dc.identifier.urihttp://hdl.handle.net/11536/153949-
dc.description.abstractFloor acceleration plays a major role in the seismic design of nonstructural components and equipment supported by structures. Large floor acceleration may cause structural damage to or even collapse of buildings. For precision instruments in high-tech factories, even small floor accelerations can cause considerable damage in this study. Six P-wave parameters, namely the peak measurement of acceleration, peak measurement of velocity, peak measurement of displacement, effective predominant period, integral of squared velocity, and cumulative absolute velocity, were estimated from the first 3 s of a vertical ground acceleration time history. Subsequently, a new predictive algorithm was developed, which utilizes the aforementioned parameters with the floor height and fundamental period of the structure as the new inputs of a support vector regression model. Representative earthquakes, which were recorded by the Structure Strong Earthquake Monitoring System of the Central Weather Bureau in Taiwan from 1992 to 2016, were used to construct the support vector regression model for predicting the peak floor acceleration (PFA) of each floor. The results indicated that the accuracy of the predicted PFA, which was defined as a PFA within a one-level difference from the measured PFA on Taiwan's seismic intensity scale, was 96.96%. The proposed system can be integrated into the existing earthquake early warning system to provide complete protection to life and the economy.en_US
dc.language.isoen_USen_US
dc.subjectSupport Vector Machine (SVM)en_US
dc.subjectSupport Vector Regression (SVR)en_US
dc.subjectp-wave featuresen_US
dc.subjectPeak Floor Acceleration (PFA)en_US
dc.subjectearthquake early warningen_US
dc.subjectseismic hazard mitigationen_US
dc.subjectreduced-scale modelen_US
dc.titleReal-time seismic structural response prediction system based on support vector machineen_US
dc.typeArticleen_US
dc.identifier.doi10.12989/eas.2020.18.2.163en_US
dc.identifier.journalEARTHQUAKES AND STRUCTURESen_US
dc.citation.volume18en_US
dc.citation.issue2en_US
dc.citation.spage163en_US
dc.citation.epage170en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000516806900002en_US
dc.citation.woscount0en_US
Appears in Collections:Articles