TY  - JOUR
T1  - 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
TT  - 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
AU  - Oral, Okan
AU  - Karahan, Tülbiya
AU  - Çakır, Mustafa
AU  - Yılmaz, Mesut
PY  - 2025
DA  - August
Y2  - 2025
DO  - 10.18185/erzifbed.1696490
JF  - Erzincan University Journal of Science and Technology
PB  - Erzincan Binali Yıldırım Üniversitesi
WT  - DergiPark
SN  - 2149-4584
SP  - 659
EP  - 678
VL  - 18
IS  - 2
LA  - en
AB  - 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.
KW  - Mechatronics
KW  - Artificial Intelligence Applications
KW  - Bibliometric Analysis
KW  - Time Series Analysis
KW  - Publication Trends
N2  - 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.
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UR  - https://doi.org/10.18185/erzifbed.1696490
L1  - https://dergipark.org.tr/tr/download/article-file/4857387
ER  -