Research Article
LİNEER OLMAYAN SİSTEMLERİN KİMLİKLENDİRİLMESİ İÇİN KELEBEK OPTİMİZASYON ALGORİTMASI KULLANILARAK İLERİ BESLEMELİ YAPAY SİNİR AĞININ EĞİTİMİ
Abstract
Bu çalışma, lineer olmayan sistemlerin kimliklendirilmesi için ileri beslemeli yapay sinir ağının (İB-YSA) eğitiminde kelebek optimizasyon algoritmasının (KOA) performansını değerlendirmektedir. Bu kapsamda, yapay sinir ağının (YSA) ağırlıkları KOA ile belirlenmiştir. Bununla birlikte, İB-YSA’nın eğitiminde popülasyon büyüklüğü ve ağ yapısının etkisi detaylıca incelenmiştir. Algoritmanın çözüm kalitesi ve yakınsama hızı açısından performansı değerlendirilmiştir. Uygulamalarda lineer olmayan 4 sistem kullanılmıştır. Hata değeri olarak ortalama karesel hata seçilmiştir. Tüm sistemler için elde edilen sonuçlar değerlendirildiğinde, lineer olmayan sistemlerin kimliklendirilmesinde KOA tabanlı İB-YSA eğitim sürecinin etkili olduğu gözlemlenmiştir.
References
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Year 2022,
, 273 - 284, 03.09.2022
Abstract
References
- Abd Elaziz, M., Dahou, A., Abualigah, L., Yu, L., Alshinwan, M., Khasawneh, A. M., & Lu, S. (2021). Advanced metaheuristic optimization techniques in applications of deep neural networks: a review. Neural Computing and Applications, 33(21), 14079-14099.
- Abiodun, O. I., Jantan, A., Omolara, A. E., Dada, K. V., Mohamed, N. A., & Arshad, H. (2018). State-of-the-art in artificial neural network applications: A survey. Heliyon, 4(11), e00938.
- Akay, B., Karaboga, D., & Akay, R. (2021). A comprehensive survey on optimizing deep learning models by metaheuristics. Artificial Intelligence Review, 1-66.
- Alawode, B. O., Salman, U. T., & Khalid, M. (2021). A Flexible Operation and Sizing of Battery Energy Storage System Based on Butterfly Optimization Algorithm. Electronics, 11(1), 109.
- Arora, S., & Singh, S. (2017). Node localization in wireless sensor networks using butterfly optimization algorithm. Arabian Journal for Science and Engineering, 42(8), 3325-3335.
- Arora, S., & Singh, S. (2019). Butterfly optimization algorithm: a novel approach for global optimization. Soft Computing, 23(3), 715-734.
- Assiri, A. S. (2021). On the performance improvement of Butterfly Optimization approaches for global optimization and Feature Selection. PloS one, 16(1), e0242612.
- Blair, R. B., & Launer, A. E. (1997). Butterfly diversity and human land use: Species assemblages along an urban grandient. Biological conservation, 80(1), 113-125.
- Hemeida, A. M., Hassan, S. A., Mohamed, A.-A. A., Alkhalaf, S., Mahmoud, M. M., Senjyu, T., & El-Din, A. B. (2020). Nature-inspired algorithms for feed-forward neural network classifiers: a survey of one decade of research. Ain Shams Engineering Journal, 11(3), 659-675.
- Irmak, B., & Gülcü, Ş. Training of the Feed-Forward Artificial Neural Networks using Butterfly Optimization Algorithm. MANAS Journal of Engineering, 9(2), 160-168.
- Karaboga, D., & Kaya, E. (2019). Training ANFIS by using an adaptive and hybrid artificial bee colony algorithm (aABC) for the identification of nonlinear static systems. Arabian Journal for Science and Engineering, 44(4), 3531-3547.
- Kaya, E., & Kaya, C. B. (2021). A novel neural network training algorithm for the identification of nonlinear static systems: Artificial bee colony algorithm based on effective scout bee stage. Symmetry, 13(3), 419.
- Li, Y., Ghoreishi, S.-m., & Issakhov, A. (2021). Improving the Accuracy of Network Intrusion Detection System in Medical IoT Systems through Butterfly Optimization Algorithm. Wireless Personal Communications, 1-19.
- Mahboob, A. S., & Moghaddam, M. R. O. (2020). An Anomaly-based Intrusion Detection System Using Butterfly Optimization Algorithm. 2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS).
- Maheshwari, P., Sharma, A. K., & Verma, K. (2021). Energy efficient cluster based routing protocol for WSN using butterfly optimization algorithm and ant colony optimization. Ad Hoc Networks, 110, 102317.
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- Zhi, Y., Weiqing, W., Haiyun, W., & Khodaei, H. (2020). Improved butterfly optimization algorithm for CCHP driven by PEMFC. Applied Thermal Engineering, 173, 114766.
There are 17 citations in total.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Computer Software |
| Journal Section | Computer Engineering |
| Authors | |
| Publication Date | September 3, 2022 |
| Submission Date | April 24, 2022 |
| Published in Issue | Year 2022 |