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Data Clustering and Zonationof Earthquake Building Damage Hazard Area Using FKCN and Kriging Algorithm

  • Edy Irwansyah
  • Sri Hartati
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 27)

Abstract

The objective of this research is to construct the zonation of earthquake building damage hazard area using fuzzy kohonen clustering network (FKCN) algorithm for data clustering and kriging algorithm for data interpolation. Data used consists of the earth data in the form of peak ground acceleration (PGA), lithology and topographic zones and Iris plant database for algorithm validation. This research is comprised into three steps which are data normalization, data clustering and data interpolation using FKCN and kriging algorithm and the construction of zonation. Clusterization produces three classes of building damage hazard data. The first class is consisting of medium PGA,dominantby high compaction lithology in the topography of inland area. The second class with low PGA, dominant low compaction lithology in the lowland topographic zone and the third class with high PGA, dominant by un-very low compactionlithology in swamp topographic zone. Banda Aceh cityas location sample is divided into three building damage hazard zone which is high hazard zone, medium hazard zone and low hazard zone for building damage which is located towards inland area.

Keywords

Clusterization damage hazard earthquake FKCN algorithm 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceBina Nusantara UniversityJakartaIndonesia
  2. 2.Deptartment of Computer Science and ElectronicUniversitas Gadjah MadaYogyakartaIndonesia

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