The effect on the wind power performance of different normalization methods by using multilayer feed-forward backpropagation neural network
Yazarlar (3)
Prof. Dr. Şakir TAŞDEMİR Selçuk Üniversitesi, Türkiye
Prof. Dr. Bülent Yanıktepe Osmaniye Korkut Ata Üniversitesi, Türkiye
Abdurrahman Burak Güher Osmaniye Korkut Ata Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale)
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| Dergi Adı | International Journal of Energy Applications and Technologies | ||
| Dergi ISSN | 2548-060X | ||
| Dergi Tarandığı Indeksler | Science Library Index, Academic Keys, Eurisian Scientific Jornal Index, ResearchBib, COSMOS IF, CiteFactor, Infobase Index | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2018 |
| Cilt / Sayı / Sayfa | 5 / 3 / 131–139 | DOI | 10.31593/ijeat.464210 |
| Makale Linki | http://dergipark.gov.tr/download/article-file/596395 | ||
| UAK Araştırma Alanları |
Yapay Zeka
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| Özet |
| Artificial Neural Networks is the most used machine learning approach today. It is a very successful method in terms of accuracy and reliability. It is widely used in classification and estimation calculations. In order to achieve the desired performance a model created with ANN, a series of processes such as selection of network structure, learning algorithms, input and output values adjustment and transfer functions determination needs to be implemented in a sensitive manner. Multilayer Feedforward Backpropagation Network, which is used most frequently in supervised learning approaches, was considered in this study. The effect on the prediction performance of the developed model was investigated by using different statistical normalization methods on the data to be used in the network. For this purpose, 4-input 1-output artificial neural networks model were operated with wind-based data taken from Osmaniye Korkut Ata University measuring station. Wind speed, Wind Direction, Humidity and Density data are defined as input values while wind power was defined as output value. Input and output data are calculated with different normalization methods and more than one network models are designed with calculated values. As a result, the study showed that artificial neural networks model which is established by sigmoid normalization method has the best performance value. |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 10 |