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Journals / Düzce Üniversitesi Bilim ve Teknoloji Dergisi / 2019 / Cilt: 7 - Sayı: 1

Drought Estimation of Çanakkale with Data Mining

Veri Madenciliği ile Çanakkale İli Kuraklık Tahmini

Tahsin BAYKAL
E. Dilek TAYLAN
Özlem TERZİ
Onur ÖZCANOĞLU
Pages
124–135
Publication Date
2022-10-12
DOI
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AI Summary & Key Takeaways

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

Examining the model results, it is observed that data mining technique is effective in drought estimation.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Drought estimation is important considering the harmful effects of the climate change in recent years.
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Key Findings & Data:Standardized precipitation index (SPI) values for 3, 6, 9, 12 and 24 months are calculated using the precipitation data of Çanakkale, Gökçeada and Bozcaada stations.
💡
Conclusion & Impact:Examining the model results, it is observed that data mining technique is effective in drought estimation.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Çanakkale · Kuraklık · Veri madenciliği

Abstract

Drought estimation is important considering the harmful effects of the climate change in recent years. In this study, various models are developed with data mining technique for the drought estimation of Çanakkale, Turkey. Standardized precipitation index (SPI) values for 3, 6, 9, 12 and 24 months are calculated using the precipitation data of Çanakkale, Gökçeada and Bozcaada stations. The calculated SPI values of Gökçeada and Bozcaada are used as input parameters in developing data mining models with different algorithms. Examining the model results, it is observed that data mining technique is effective in drought estimation.

Özet

Son yıllardaki iklim değişikliğinin zararlı etkileri göz önüne alındığında kuraklık tahmini oldukça önemlidir. Bu çalışmada, Çanakkale iline ait kuraklık tahmini için veri madenciliği ile modeller geliştirilmiştir. Çanakkale, Gökçeada ve Bozcaada yağış istasyonlarına ait yağış verileri ile 3, 6, 9, 12 ve 24 aylık standart yağış indeksi (SYİ) değerleri hesaplanmıştır. Hesaplanan Gökçeada ve Bozcaada’nın SYİ değerleri veri madenciliği modellerinde girdi olarak kullanılmıştır ve farklı algoritmalar ile modeller geliştirilmiştir. Model sonuçları, hesaplanan SYİ değerleri ile karşılaştırıldığında, veri madenciliği yönteminin kuraklık tahmininde iyi sonuçlar verdiği gözlemlemiştir.

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Cite This Article

BAYKAL, T., TAYLAN, E. D., TERZİ, Ö., ÖZCANOĞLU, O. (2022). Drought Estimation of Çanakkale with Data Mining. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, Cilt: 7 - Sayı: 1, 124–135. https://ajindex.com/articles/494268

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