DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-6,Issue-8 ( Aug, 2019 ) | |||||||||
Paper Title |
Systems-Approach and MHGN based Earthquake Forecasting | |||||||||
Author Name |
Benny Benyamin Nasution, Rahmat Widia Sembiring, Muhammad Syahruddin, Nursiah Mustari, Abdul Rahman Dalimunthe, Nisfan Bahri, Berta Br Ginting | |||||||||
Affilition |
Computer Engineering and Informatics Department, PoliteknikNegeri Medan, Medan 20155, Indonesia 3Electrical Engineering Department, PoliteknikNegeri Medan, Medan 20155, Indonesia Business Administration Department, PoliteknikNegeri Medan, Medan 20155, Indonesia Accounting and Banking Department, PoliteknikNegeri Medan, Medan 20155, Indonesia 7Mechanical Engineering Department, PoliteknikNegeri Medan, Medan 20155, Indonesia | |||||||||
Pages |
39-44 | |||||||||
Abstract |
A number of earthquake forecastings have been attemped. Lots of technologies have been introduced, but the results are not yet useful. More and more earthquakes have caused a lot of casualties. The attempt to achieve a stable technology is therefore still very demanding, because of the increasing number of earthquake incidences lately and the casualties accordigly. Due to the fact that it is not trivial working on complex—with numerous parameters—and big data, the research on finding sounding earthquake forecast systemshave taken a very long time. It is very difficult to establish a sophisticated system that can be used to forecast an earthquake effectively, but the concept of multidimensional Hierarchical Graph Neuron (mHGN) has opened up a new opportunity to forecast earthquakenot only effectively but also in real-time manner. In order to increase its accuracy, the systems approach has been evaluated and considered. From the previous research, the 91% of mHGN accuracy in recognizing almost 11% distorted or incomplete patterns is a strrong indication that the accuracy of mHGN in forecasting earthquake will also be adequate. Keywords - GN, HGN, MHGN, SLHGN, Pattern Recognition, Earthquake Forecasting, Systems Approach. | |||||||||
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