Transformatör modelleri ile zaman serisi analizi tabanlı toprak sıcaklığı tahmini

Öz

Toprak sıcaklığı; buzulların enerji dengesi, kütle dengesi, ekolojik istikrar ve tarımsal verimlilik üzerinde belirleyici bir değişken olup, karmaşık ve doğrusal olmayan etkileşimler nedeniyle doğru biçimde tahmin edilmesi güçtür. Mevcut yöntemler bu karmaşıklıkları yeterince temsil edemediğinden, daha gelişmiş modellere ihtiyaç duyulmaktadır. Bu çalışma, toprak sıcaklığı tahmini için transformatör tabanlı yeni bir çerçeve önermektedir. Transformatör mimarilerinin uzun vadeli bağımlılıkları ve zamansal örüntüleri yakalama konusundaki üstün yeteneklerinden yararlanılarak çevresel veriler üzerinde yüksek doğruluklu bir tahmin modeli geliştirilmiştir. Modelin geliştirilmesi ve değerlendirilmesi için altı farklı FLUXNET istasyonundan elde edilen veriler kullanılmıştır. Karşılaştırmalı analizler; ağaç tabanlı yöntemler, klasik derin öğrenme mimarileri ve beş gelişmiş transformatör modeli (Vanilla Transformer, Informer, Autoformer, Reformer ve ETSformer) ile gerçekleştirilmiştir. Sonuçlar, transformatör tabanlı modellerin tahmin doğruluğu bakımından geleneksel yaklaşımlara kıyasla belirgin üstünlük sağladığını göstermektedir. Ayrıca önerilen yöntemin farklı çevresel koşullarda tutarlı, sağlam ve genelleştirilebilir performans sergilediği doğrulanmıştır. Bulgular, transformatör modellerinin çevresel tahmin problemlerinde, özellikle toprak sıcaklığı öngörüsünde, yüksek potansiyele sahip olduğunu ortaya koymakta hem bilimsel anlayışa katkı sağlamakta hem de ölçeklenebilir, güvenilir ve pratik uygulamalara uygun bir araç sunmaktadır.

Anahtar Kelimeler

• Derin öğrenme
• FLUXNET
• Toprak sıcaklığı tahmini
• Transformatör modeller
• Zaman serisi kestirimi

Kaynakça

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