Browsing by Author "Khodabakhsh, Athar"
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Digital oil refinery: utilizing real-time analytics and cloud computing over industrial sensor data
Khodabakhsh, Athar (2018-12-14)This thesis addresses big data challenges seen in large-scale, mission-critical industrial plants such as oil refineries. These plants are equipped with heavy machinery (boilers, engines, turbines, etc.) that are continuously ... -
Forecasting multivariate time-series data using LSTM and mini-batches
Khodabakhsh, Athar; Arı, İsmail; Bakır, M.; Alagoz, S. M. (Springer, 2020)Multivariate time-series data forecasting is a challenging task due to nonlinear interdependencies in complex industrial systems. It is crucial to model these dependencies automatically using the ability of neural networks ... -
Multivariate sensor data analysis for oil refineries and multi-mode identification of system behavior in real-time
Khodabakhsh, Athar; Arı, İsmail; Bakır, M.; Ercan, Ali Özer (IEEE, 2018)Large-scale oil refineries are equipped with mission-critical heavy machinery (boilers, engines, turbines, and so on) and are continuously monitored by thousands of sensors for process efficiency, environmental safety, and ... -
Rafinerilerdeki büyük veri problemlerine gerçek-zamanlı veri uzlaştırma çözümleri
Bakır, M.; Aydoğan, B.; Aydın, M.; Khodabakhsh, Athar; Arı, İsmail; Ercan, Ali Özer (IEEE, 2014)Rafineriler tonlarca ham petrolün, her gün faklı kimyasal işlemden geçirilerek benzine ve diğer yan ürünlere dönüştürüldüğü dev endüstriyel tesislerdir. Bu makalede sensör-tabanlı petrol rafinelerine özel endüstriyel büyük ... -
Stream analytics and adaptive windows for operational mode identification of time-varying industrial systems
Khodabakhsh, Athar; Arı, İsmail; Bakır, M.; Alagoz, S. M. (IEEE, 2018-09-07)It is necessary to develop accurate, yet simple and efficient models that can be used with high-speed industrial data streams. In this paper, we develop a mode identification technique using stream analytics and show that ...
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