Mapping the Research Landscape and Predicting Future Growth: A Bibliometric and Time Series Study of Artificial Intelligence/Machine Learning Applications in Mechatronics Engineering Using Web of Science Data

Öz

This study examines the impact of Artificial Intelligence (AI) and Machine Learning (ML) technologies on the fields of Mechatronics Engineering, Robotics, and Automation. Through a comprehensive bibliometric analysis of publications indexed in the Web of Science (WoS) database, the historical development, key research trends, and prominent themes of this interdisciplinary domain are revealed. Additionally, six different time series forecasting methods—ARIMA, ETS, Theta, Holt-Winters, Polynomial Regression, and Naive Model—are employed to predict the number of scientific publications for the year 2025. The analysis results indicate a growing influence of AI/ML in the field of mechatronics and a clear upward trend in publication volume. This study offers a unique perspective on the research directions in the field by quantitatively illustrating how AI and ML interact with mechatronics engineering.

Anahtar Kelimeler

• Mechatronics
• Artificial Intelligence Applications
• Bibliometric Analysis
• Time Series Analysis
• Publication Trends

Mekatronik Mühendisliğinde Yapay Zekâ ve Makine Öğrenmesi Uygulamalarında Web of Science Tabanlı Bibliyometrik ve Zaman Serisi Analizi: Araştırma Eğilimlerinin Belirlenmesi ve Gelecek Yayın Sayısının Tahmini

Öz

Bu çalışma, Yapay Zekâ (YZ) ve Makine Öğrenmesi (ML) teknolojilerinin Mekatronik Mühendisliği, Robotik ve Otomasyon alanlarındaki etkisini incelemektedir. Web of Science (WoS) veri tabanındaki yayınlar üzerinden yapılan kapsamlı bir bibliyometrik analiz ile bu interdisipliner alanın tarihsel gelişimi, temel araştırma eğilimleri ve öne çıkan temaları ortaya konmuştur. Ayrıca, ARIMA, ETS, Theta, Holt-Winters, Polynomial Regression ve Naive Model gibi altı farklı zaman serisi tahmin yöntemi kullanılarak 2025 yılına ait bilimsel yayın sayıları öngörülmüştür. Analiz sonuçları, YZ/ML’nin mekatronik alanındaki yükselen etkisini ve bu alanlarda belirgin bir yayın artış trendini göstermektedir. Bu çalışma, YZ ve ML'nin mekatronik mühendisliğiyle nasıl etkileşim içinde olduğunu nicel verilerle destekleyerek alandaki araştırma yönelimlerine dair farklı bakış açısı sunmaktadır.

Anahtar Kelimeler

• Mekatronik
• Yapay Zekâ Uygulamaları
• Bibliyometrik Analiz
• Zaman Serisi Analizi
• Yayın Eğilimleri

Kaynakça

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