İklim Değişikliği Araştırmalarında Yapay Zekâ ve Makine Öğrenmesi Uygulamaları: Bibliyometrik Bir Analiz

Öz

İklim değişikliği günümüzün en acil sorunlarından biri olarak kabul edilmektedir. Artan riskler ve olumsuz etkiler, derin sosyal, ekonomik ve kalkınmasal sonuçlar doğurmaktadır. Bu etkilerin ele alınması ve azaltılması, teknolojik yeniliği temel bir gereklilik haline getirmiştir. Gelişen yaklaşımlar arasında, çevrimiçi verileri kullanarak zamanında ve bağlama özgü bilgiler sağlayan yapay zekâ (YZ) ve makine öğrenimi (MÖ), potansiyel çözümler üretme kapasiteleriyle öne çıkmaktadır. Çevresel etkileri değerlendirmek ve tahminlerde bulunmak için temel araçlar haline gelen YZ ve MÖ odaklı modeller, iklim adaptasyon kapasitesini artırmaktadır. İklim değişkenlerindeki karmaşık, ayrılması zor dinamiklerin analizini kolaylaştırır ve sağlam etki değerlendirmelerini destekler. Veri kümelerini entegre ederek, bu teknolojiler uzun vadeli iklim senaryolarının daha hassas tahminlerini mümkün kılar. Bu çalışmanın temel amacı, YZ ve MÖ tekniklerinin özelliklerini ve doğal sistemlerde önemli kayıplara neden olan bir tehdit olan iklim değişikliğinin ele alınmasındaki potansiyel rollerini incelemektir. Bu çalışma, yapay zekâ ve makine öğrenmesinin iklim değişikliğiyle mücadeledeki rolünü bibliyometrik analiz yoluyla incelemekte ve bu alandaki akademik yayınların zaman içindeki gelişimine odaklanmaktadır. Araştırma sonuçları, yapay zekâ ve makine öğreniminin iklim değişikliğiyle mücadelede hem avantajlar hem de dezavantajlar sunabileceğini ortaya koymaktadır. Faydaları çok daha önemli olsa da fayda ve riskler arasındaki dengeyi kurmak çok önemlidir.

Anahtar Kelimeler

• Küresel ısınma literatürü
• çevresel izleme
• sera gazı emisyonları
• öngörücü modelleme
• yayın eğilimleri

Artificial Intelligence and Machine Learning Applications in Climate Change Research: A Bibliometric Analysis

Öz

Climate change is considered one of today's most pressing problems. Increasing risks and negative impacts have profound social, economic, and developmental implications. Addressing and mitigating these impacts has made technological innovation a fundamental necessity. Among emerging approaches, artificial intelligence (AI) and machine learning (ML), which provide timely and context-specific insights using online data, stand out for their capacity to generate potential solutions. AI- and ML-based models, which have become fundamental tools for assessing environmental impacts and making predictive forecasts, are enhancing climate adaptation capacity. They facilitate the analysis of complex, hard-to-separate dynamics in climate variables and support robust impact assessments. By integrating datasets, these technologies enable more precise predictions of extended climate scenarios. The primary objective of this study is to investigate the characteristics of AI and ML techniques and their potential role in addressing climate change, a threat that causes significant losses in natural systems. The study examines the role of AI and ML in combating climate change through bibliometric analysis, focusing on the evolution of academic publications in the field over time. The findings reveal that AI and ML can offer both advantages and disadvantages in combating climate change. While their benefits are far more significant, weighing the balance between benefits and risks is crucial.

Anahtar Kelimeler

• Global warming literature
• environmental monitoring
• greenhouse gas emissions
• predictive modelling
• publication trends

Kaynakça

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