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Article Citation - WoS: 7Citation - Scopus: 10Comparison of Three Different Learning Methods of Multilayer Perceptron Neural Network for Wind Speed Forecasting(Gazi Univ, 2021) Bulut, Mehmet; Tora, Hakan; Buaisha, Dr.magdiIn the world, electric power is the highest need for high prosperity and comfortable living standards. The security of energy supply is an essential concept in national energy management. Therefore, ensuring the security of electricity supply requires accurate estimates of electricity demand. The share of electricity generation from renewables is significantly growing in the world. This kind of energy types are dependent on weather conditions as the wind and solar energies. There are two vital requirements to locate and measure specific systems to utilize wind power: modelling and forecasting of the wind velocity. To this end, using only 4 years of measured meteorological data, the present research attempts to estimate the related speed of wind within the Libyan Mediterranean coast with the help of ANN (artificial neural networking) with three different learning algorithms, which are Levenberg-Marquardt, Bayesian Regularization and Scaled Conjugate Gradient. Conclusions reached in this study show that wind speed can be estimated within acceptable limits using a limited set of meteorological data. In the results obtained, it was seen that the SCG algorithm gave better results in tests in this study with less data.Article Yalıtık Sözcüklü Bir Türkçe Konuşma Tanıma Sisteminin Yapay Veri Artırımı ile Tasarımı ve Gerçekleştirimi(2020) Uslu, İbrahim Baran; Tora, Hakan; Sümer, Emre; Türker, MustafaBu çalışmada toplamda doksan iki adet sesli komuttan oluşan bir yalıtık sözcüklü Türkçe konuşmatanıma sistemi tasarlanmış ve gerçekleştirilmiştir. Sistem, destek vektör makinesi (SVM) tabanlı olup,eğitimde kullanılan veri kümesi kaydedilen konuşmaların yapay olarak çeşitlendirilip artırılmasıyla eldeedilmiştir. Farklı yapay veri oranlarının tanıma başarımı üzerindeki etkisi incelenmiştir. Akustik öznitelikolarak, mel frekansı kepstral katsayıları (MFCC) kullanılmıştır. Ayrıca, ses aktivitesi tespitinin ve MFCCkatsayılarının tanıma başarımına etkileri de irdelenmiştir. Sonuçta doksan iki yalıtık komut için ortalama%92.6’lık doğrulukla çalışan bir konuşma tanıma sistemi geliştirilmiştirArticle Implementation of Turkish Text-To Synthesis on a Voice Synthesizer Card With Prosodic Features(2017) Tora, Hakan; Uslu, İbrahim Baran; Karamehmet, TimurThis study is on hardware implementation of the Turkish text-to-speech (TTS) synthesis with a voice synthesizer card. Here, a fully functional TTS system, capable of synthesizing every Turkish text, including abbreviations, numbers, etc. is designed and implemented. The system is additionally enriched by applying some prosodic attributes for more intelligible and natural speech production. A set of rules required for proper pronunciation and stress patterns are precisely defined in a lexicon utilized for synthesizing Turkish speech. Performance of the developed system is assessed by the Mean Opinion Score (MOS) test. An average score of 3.29 out of 5 is achieved.It indicates that the proposed synthesizer can be successfully integrated to many practical Turkish TTS applications.
