Journals / Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik / 2014 / Cilt: 15 - Sayı: 2

AFET YÖNETİMİ İÇİN BETİMLEME MANTIĞI TABANLI DEPREM HASAR TAHMİNİ

DESCRIPTION LOGIC BASED EARTHQUAKE DAMAGE ESTIMATION FOR DISASTER MANAGEMENT

Pages
93–103
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Other features ofthis study include the use of parliament triple store to store and query disaster ontology, and the provisionof damage assessment maps to enable disaster managers to reduce their response time.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Earthquake damage estimation within the first few hours of devastating earthquake is critical fromthe point of decision-making and post-disaster planning.
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Key Findings & Data:For this reason, it isvery challenging to derive accurate damage and loss estimation solely based on the source parameter ofthe earthquake.
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Conclusion & Impact:Other features ofthis study include the use of parliament triple store to store and query disaster ontology, and the provisionof damage assessment maps to enable disaster managers to reduce their response time.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Earthquake damage estimation within the first few hours of devastating earthquake is critical fromthe point of decision-making and post-disaster planning. With recent developments in earthquakeengineering, earthquake damage estimation can be effectively determined using strong ground motionnetwork. However, a number of densely populated cities in earthquake risk zones do not have access tosuch costly and advanced systems. In this paper, we propose a system for estimating earthquake damagein the early post-disaster period, using a limited number of data sources, such as up-to-date earthquakesource parameter, population, building quality, roads and bridge locations. This information, however,is distributed, and therefore poses semantic heterogeneity problems in data sharing. For this reason, it isvery challenging to derive accurate damage and loss estimation solely based on the source parameter ofthe earthquake. To solve this problem, in the proposed system, ontologies are used to ensure semanticinteroperability, and description logic (DL) rules are defined for damage estimation. Other features ofthis study include the use of parliament triple store to store and query disaster ontology, and the provisionof damage assessment maps to enable disaster managers to reduce their response time.

Özet

Yıkıcı bir depremin ilk birkaç saatinde deprem hasar tahmini yapılabilmesi afet sonrası planlamave karar verme açısından çok kritik öneme sahiptir. Deprem mühendisliğindeki gelişme ile deprem hasartahmini kuvvetli yer hareketi ağı kullanılarak etkin bir şekilde yapılabilmektedir. Buna rağmen birçokdeprem riski taşıyan bölgelerdeki yoğun nüfusa sahip olan şehirlerde bunun gibi gelişmiş ve maliyetlisistemler bulunmamaktadır. Bu çalışmada deprem sonrası süreçte güncel köprü, yol, bina kalitesi, nüfusve deprem parametreleri gibi kısıtlı veri kaynakları kullanılarak deprem hasarını tahminlemeyiamaçlayan bir sistem önerilmektedir. Bununla birlikte bu bilgiler dağıtık ve veri paylaşımı açısındananlamsal heterojenliğe sahiptir. Bu sebeple sadece deprem parametrelerine dayanarak hasarın vekayıpların tahmininin doğru yapılması zorlu bir görevdir. Bu problemi çözebilmek için hasar tahminiiçin betimleme dili kuralları tanımlandı ve ontolojiler kullanılarak anlamsal heterojenliği sağlamasıamaçlanmıştır. Bu çalışmanın diğer özellikleri ise afet ontolojisinin sorgulanması ve saklanması içinparliament triple store kullanılmıştır ve afet yöneticilerinin afete müdahale süresinin kısaltmak için hasardeğerlendirme haritaları üretilmiştir.

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Cite This Article

TECİM, V., AYDIN, C. (2022). AFET YÖNETİMİ İÇİN BETİMLEME MANTIĞI TABANLI DEPREM HASAR TAHMİNİ. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik, Cilt: 15 - Sayı: 2, 93–103. https://ajindex.com/articles/438378

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