Şeyda Ertekin Bolelli

E-mail
sertekin@metu.edu.tr
Department
Department of Computer Engineering
Scopus Author ID
Web of Science Researcher ID
Penetration rate prediction in heterogeneous formations: A geomechanical approach through machine learning
Kor, Korhan; Ertekin Bolelli, Şeyda; Yamanlar, Şenol; Altun, Gürşat (2021-12-01)
© 2021 Elsevier B.V.Bourgoyne and Young Method (BYM) is one of the most widely used rate of penetration (ROP) prediction methods. Drilling data, in this method, must be taken from uniform-lithology sections (homogeneous fo...
Linking COVID-19 perception with socioeconomic conditions using Twitter data
Ertekin Bolelli, Şeyda; Sert, Egemen; Okan, Oral; Ozbilen, Alper; Ozdemir, Suat (2021-07-01)
We, as humans, are constantly in relation with our environment. Sudden changes in our living media may alter the way we perceive ourselves and our environment in various ways. Coronavirus (COVID-19) outbreak is a great exa...
1. AI-based Air-to-Surface Mission Planning for Opportunity Targets using Predictive LAR Approach
Ertekin Bolelli, Şeyda; Ozdemir, Rasit (2021-06-11)
Feature Dimensionality Reduction with Variational Autoencoders in Deep Bayesian Active Learning
Ertekin Bolelli, Şeyda; Çöl, Pınar Ezgi (2021-06-09)
Data annotation for training of supervised learning algorithms has been a very costly procedure. The aim of deep active learning methodologies is to acquire the highest performance in supervised deep learning models by ann...
Solar Power Prediction with an Hour-based Ensemble Machine Learning Method
Ertekin Bolelli, Şeyda (2020-03-01)
In recent years, the share of solar power in total energy production has gained a rapid increase. Therefore, prediction of solar power production has become increasingly important for energy regulations. In this study we p...
METU Smart Campus Project (iEAST)
Ertekin Bolelli, Şeyda; Keysan, Ozan; Göl, Murat; Bayazıt, Göksenin Hande; Yıldız, Tunahan; Marr, Andrea; Ganji, Mehdi; Teimourzadeh, Saeed; Tör, Osman Bülent; Özkavaf, Sıla (2020-01-01)
With the rise of urbanization, cities around the world have embraced applications and benefits of leveraging advanced technologies to deliver a range of services while promoting efficient, environmentally friendly, and sus...
Türkiye”de Yapay Zekanın Gelişim için görüş ve Öneriler
ADALI, EŞREF; AFYONLUOĞLU, MUSTAFA; GÜVENİR, HALİL ALTAY; ERGİN, OĞUZ; Ertekin Bolelli, Şeyda; KARAKAYA, ZİYA; KOLAT, AYDIN; ÖZBAYOĞLU, AHMET MURAT; TUNCER, T TOLGA; VAROL, ASAF; Yarman Vural, Fatoş Tunay; YAZICI, ALİ (Türkiye Bilişim Derneği (TBD), 2020-01-01)
A feature-based hybrid ARIMA-ANN model for univariate time series forecasting
Buyuksahin, Umit Cavus; Ertekin Bolelli, Şeyda (2020-01-01)
High prediction accuracies at time series modeling and forecasting is of the utmost importance for a variety of application domains. Many methods have been proposed in the literature to improve time series forecasting accu...
Forecasting of Product Quality Through Anomaly Detection
Dinç, Mehmet; Ertekin Bolelli, Şeyda; Özkan, Hadi; Meydanlı, Can; Atalay, Mehmet Volkan (2020)
Forecasting of product quality by means of anomaly detection is crucial in real-world applications such as manufacturing systems. In manufacturing systems, the quality is assured through tests performed on sample units ran...
Forecasting of Product Quality Through Anomaly Detection
Dinc, Mehmet; Ertekin Bolelli, Şeyda; Ozkan, Hadi; Meydanli, Can; Atalay, Mehmet Volkan (2019-10-23)
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