Abstract
A technique to predict the principal motions of earthquakes using preliminary tremors, has been developed. Taking adventage of the time lag between them, we can take suitable countermeasures against the principal motions that affect the urban structures; e.g. an escape from dangerous zone, stopping elevators and gas supply, and setting up AMD (Active Mass Damper) system. A structured neural network is used to construct the maximum acceleration prediction model, where inputs are fuzzified shaking direction data, power spectrum and maximum acceleration of preliminary tremors. The proposed model has been improved by handling some earthquakes in Ibaraki-ken southwest area that least fit the model as exceptions. Average square error of the improved model is reduced to third of one of the statistical model.
