Prediction Model of Earthquake with The Identification of Earthquake Source Polarity Mechanism through The Focal Classification Using ANFIS and PCA Technique

摘要

Incidence of earthquake disaster has caused casualties and material in considerable amounts. This research has purposes to predictability the return period of earthquake with the identification of the mechanism of earthquake which in case study area in Sumatra. To predict earthquakes which training data of the historical earthquake is using ANFIS technique. In this technique the historical data set compiled into intervals of earthquake occurrence daily average in a year. Output to be obtained is a model return period earthquake events daily average in a year. Return period earthquake occurrence models that have been learning by ANFIS, then performed the polarity recognition through image recognition techniques on the focal sphere using principal component analysis PCA method. The results, model predicted a return period earthquake events for the average monthly return period showed a correlation coefficient 0.014562.