Strong Motion Data Based Regional Ground Motion Prediction Equations for North East India Based on Non-Linear Regression Models
R. Ramkrishnan, Sreevalsa Kolathayar, T. G. Sitharam
Abstract
Existing Ground Motion Prediction Equations (GMPE) in practice for North East India have been developed using limited or simulated datasets of recorded ground motions. The current study presents the development of a new GMPE based on a well-established model considering actual recorded ground motion data comprising of acceleration, magnitude, and hypocentral distances. A larger dataset with magnitudes ranging from 4.2 to 6.9 and up to 640 kms, with a total of 204 recordings is used in non-linear multiple-regression. The newly developed GMPE could predict ground acceleration realistically over larger ranges of distance and magnitudes, compared to existing GMPEs.
Topics & Concepts
Ground motionAccelerationMagnitude (astronomy)Linear regressionGeodesySpectral accelerationMotion (physics)RegressionGeologyPeak ground accelerationRangingRegression analysisSeismologyMathematicsStatisticsComputer sciencePhysicsArtificial intelligenceAstronomyClassical mechanicsSeismic Performance and AnalysisStructural Health Monitoring TechniquesSeismic Waves and Analysis