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Multivariate sensor data analysis for oil refineries and multi-mode identification of system behavior in real-time
(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
(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
(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 ...
Forecasting multivariate time-series data using LSTM and mini-batches
(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 ...
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