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.
Skip Nav Destination
Article navigation
6 May 2016
THE 5TH INTERNATIONAL SYMPOSIUM ON EARTHHAZARD AND DISASTER MITIGATION: The Annual Symposium on Earthquake and Related Geohazard Research for Disaster Risk Reduction
19–20 October 2015
Bandung, Indonesia
Research Article|
May 06 2016
Prediction model of earthquake with the identification of earthquake source polarity mechanism through the focal classification using ANFIS and PCA technique
Setyonegoro W.
Setyonegoro W.
a)
1
Research and Development Center
of BMKG Jl. Angkasa I no.2 kemayoran Jakarta Pusat 10720, Indonesia
Search for other works by this author on:
a)
Corresponding author: [email protected]
AIP Conf. Proc. 1730, 020005 (2016)
Citation
Setyonegoro W.; Prediction model of earthquake with the identification of earthquake source polarity mechanism through the focal classification using ANFIS and PCA technique. AIP Conf. Proc. 6 May 2016; 1730 (1): 020005. https://doi.org/10.1063/1.4947373
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
57
Views
Citing articles via
Inkjet- and flextrail-printing of silicon polymer-based inks for local passivating contacts
Zohreh Kiaee, Andreas Lösel, et al.
Design of a 100 MW solar power plant on wetland in Bangladesh
Apu Kowsar, Sumon Chandra Debnath, et al.
Production and characterization of corncob biochar for agricultural use
Praphatsorn Rattanaphaiboon, Nigran Homdoung, et al.
Related Content
Geothermal power plant performance estimation using ANFIS-PCA and ANFIS-GA
AIP Conf. Proc. (September 2024)
Flood Forecasting in River System Using ANFIS
AIP Conference Proceedings (October 2010)
ANFIS for building cooling load estimation
AIP Conference Proceedings (November 2021)
Inflow modeling of Okhla barrage using ANFIS and KNN models
AIP Conference Proceedings (November 2022)
ANFIS APPROACH FOR SSSC CONTROLLER DESIGN FOR THE IMPROVEMENT OF TRANSIENT STABILITY PERFORMANCE
AIP Conference Proceedings (June 2011)