TY - JOUR T1 - Su Dalga Enerjisi Üretimi ve Yapay Zekâ: Asya, Avrupa ve Türkiye’nin Potansiyeli TT - Wave Energy Production and Artificial Intelligence: The Potential of Asia, Europe and Türkiye AU - Kaymaz, Selma AU - Bayraktar, Tuğrul AU - Sel, Çağrı PY - 2024 DA - August Y2 - 2024 DO - 10.53433/yyufbed.1445985 JF - Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi JO - YYU JINAS PB - Van Yuzuncu Yıl University WT - DergiPark SN - 1300-5413 SP - 798 EP - 822 VL - 29 IS - 2 LA - tr AB - Son yıllarda, sürdürülebilir bir dünya için yenilenemeyen enerji kaynaklarının kullanımının azaltılması gerekliliği giderek daha belirgin hale gelmektedir. Fosil yakıt tüketiminden, daha temiz bir enerjiye geçiş döneminde, yenilenebilir enerji kaynakları hızla gelişme göstermektedir. Bu gelişmeler ışığında su enerjisi teknolojilerine odak artmaktadır. Enerji potansiyeli için gerekli şartlar karşılandığı sürece; su kaynaklı enerji üretim projelerinin uygulanması ülkelerin refahına katkı sağlama potansiyeli taşımaktadır. Yenilenebilir enerji üretiminde rekabete konu olan su kaynaklı enerji üretimi için; literatürde kıtalar arası enerjinin incelendiği, su potansiyelinin ölçüldüğü, santraller için uygun yer seçiminin yapıldığı, dalga – iklim ilişkisinin incelendiği, okyanus enerjisi teknolojileri konularını içeren çalışmalarda geleneksel teknikler yanı sıra yapay zekâ tekniklerine de yer verilmektedir. Deneysel modelleme saha ölçüm tekniklerinin yüksek maliyetli olduğu, sayısal yöntemlerin parametre ve girdi hazırlık sürecinin zahmetli olması sebebiyle çeşitli yapay zekâ yöntemleri, su kaynaklı enerji üretimi teknolojisinde yoğun şekilde kullanılmaktadır. Yapay sinir ağları da bu alanda karşılaşılan problemlerin çözümünde kullanılan tekniklerden birisi olarak yer almaktadır. Bu derlemede, Asya ve Avrupa kıtasında su kaynaklı enerji üretimi hakkında yapılmış mevcut çalışmalardan bahsedilmekte, Türkiye’nin su enerjisi potansiyelini, mevcut literatür incelenerek ortaya konulmaktadır. Ayrıca yapay zekâ tekniklerinden yapay sinir ağı metodunun su enerjisi teknolojilerinde ne şekilde ve hangi ölçüde kullanıldığı ve kullanılan yöntemlerle ilgili literatüre yer verilmiştir. KW - Asya KW - Avrupa KW - Gelgit enerjisi KW - Su dalga enerjisi KW - Türkiye KW - Yapay sinir ağları N2 - In recent years, there has been a growing need to reduce our reliance on non-renewable energy sources for a more sustainable world. The use of renewable energy sources is increasing as we move towards cleaner energy options and away from fossil fuels. Wave energy technology is gaining particular attention for generating energy sustainably. Under optimal conditions, wave energy projects have the potential to contribute significantly to a country's well-being. In addition to traditional methods, artificial intelligence techniques are widely used in wave energy technology due to the high costs and labor-intensive nature of experimental field measurements and the preparation of parameters and inputs for numerical methods. One such technique involves artificial neural networks to solve problems in this field. This study examines existing research on water-based energy production in Asia and Europe, evaluates Türkiye’s wave energy potential based on the available literature, and discusses the application of artificial neural networks in wave energy technology and the methods employed in the literature. CR - Abdalla, S., & Özhan, E. (1999, Nisan). Wind and wave climate of the mediterranean and the black sea. Proceedings of the International MEDCOAST Conference, Antalya. CR - Ahmed, A. A. M., Jui, S. J. J., AL-Musaylh, M. S., Raj, N., Saha, R., Deo, R. C., & Saha, S. K. (2024). 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