İş Zekâsı (BI) Teknikleri Kullanılarak Dünya Çapındaki Önemli Deprem Verilerinin Analizi

Abstract

Depremler, büyük yıkıma ve can kayıplarına yol açabilen, en sarsıcı doğal olaylar arasında yer alır. Bu etkileri anlamak ve azaltmak, gelişmiş analiz araçlarının kullanılmasını gerektirir. Uygulanabilir stratejilerden biri, kapsamlı tarihsel deprem kayıtları ile gerçek zamanlı sismik verileri birlikte inceleyebilen iş zekâsı (BI) yöntemlerinin kullanılmasıdır. Bu verilerin sunduğu gizli kalıpların incelenmesiyle, araştırmacılar yaklaşmakta olan depremlere işaret edebilecek erken sinyalleri potansiyel olarak ortaya çıkarabilir. Bu çalışmada amaç, 1843 ile Nisan 2025 yılları arasında kaydedilen ve Richter ölçeğinde beşin üzerindeki büyük sismik olaylara odaklanan deprem verilerini kapsamlı biçimde analiz etmek için BI tekniklerini uygulamaktır. Bu hedef doğrultusunda, geçmiş deprem olaylarının sistematik bir şekilde incelenmesini mümkün kılan kapsamlı bir sismik veri tabanı oluşturulmuştur. Veri madenciliği yöntemlerinden yararlanılarak jeolojik özellikler ile tektonik hareketler arasındaki karmaşık ilişkiler araştırılmıştır. Bu yöntemler arasında, benzer depremleri gruplandırarak daha büyük sismik olayların potansiyel öncüllerini sınıflandırmaya yardımcı olan kümeleme teknikleri yer almaktadır. Ayrıca, sınıflandırma yaklaşımları depremleri düşük riskli, orta riskli ve yüksek riskli olarak kategorize ederken; regresyon analizleri büyüklük, derinlik ve coğrafi konum gibi belirli deprem özelliklerini tahmin etmektedir. Bunun yanı sıra, zaman serisi analizi yöntemi dünya genelinde gelecekte meydana gelebilecek önemli depremlerin öngörülmesinde kullanılmıştır. Bu tür öngörüler, yalnızca sismik aktivite kalıplarının anlaşılması için değil, mevcut tahmin sistemlerinin iyileştirilmesi açısından da büyük önem taşımaktadır. Küresel ölçekte büyük deprem verilerinin analizi, gelişimi, etkisi ve tekrar eden konumlarını yansıtmak amacıyla Power BI kullanılmış; 1843’ten Nisan 2025’e kadar olan veriler derlenerek incelenmiştir. Sonuç olarak, bu çalışmanın amacı deprem analiz araçlarını geliştirmek ve iyileştirmek; böylece daha doğru tahminler yapılmasını ve dünya genelinde hazırlık stratejilerinin güçlendirilmesini sağlamaktır.

Keywords

• Önemli depremler
• İş zekası
• Veri madenciliği
• Sismik veri analizi

Worldwide Significant Earthquakes Data Analytics Using Business Intelligence Techniques

Abstract

Earthquakes are among the most upsetting natural events, capable of causing enormous destruction and loss of human lives. Understanding and mitigating their impacts requires sophisticated analysis tools. One viable strategy entails applying business intelligence (BI), which can effectively examine extensive historical earthquake records alongside with real-time seismic data. By exploring patterns hidden within this information, researchers can potentially uncover early signals indicating an impending earthquake. In this paper, the aim is to apply BI techniques to comprehensivly analyse earthquake data collected between 1843 and April 2025, focusing on significant seismic events with magnitudes greater than five on the Richter scale. To achieve this, a comprehensive seismic data warehouse was established to enable systematic analysis of past earthquake occurrences. Through the request for data mining methods, this research investigates the complex relationships between geological features and tectonic movements. These methods include clustering techniques that group similar earthquakes to help classify potential precursors to larger seismic events. Additionally, classification approaches categorize earthquakes by their severity low-risk, medium-risk, and high-risk while regression analysis forecasts specific earthquake features such as magnitude, depth, and geographical location. Moreover, the research employes time-series analytical method to forecast future occurrences of significant earthquakes worldwide. Such predictive insights are vital not only for understanding seismic activity patterns but also for improving existing forecasting systems. PowerBI is used for data analytics and visualization to facilitate the analysis of global large-scale earthquake data, reflecting their evolution, impact, and recurring locations; data from 1843 to April 2025 were compiled and examined. Ultimaly, the goal of this work is to refine and advance earthquake analysis tools, thereby enabling more accurate predictions and enhanced preparedness strategies worldwide.

Keywords

• Significant Earthquakes
• Business Intelligence
• Data Mining
• Seismic Data Analytics

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