A comprehensive survey on rare event prediction
Rare event prediction involves identifying and forecasting events with a low probability using
machine learning (ML) and data analysis. Due to the imbalanced data distributions, where …
machine learning (ML) and data analysis. Due to the imbalanced data distributions, where …
Digital transformation: a review on artificial intelligence techniques in drilling and production applications
AL D'Almeida, NCR Bergiante… - … International Journal of …, 2022 - Springer
The use of digital and artificial intelligence technologies has expanded and influenced
business models and the opening of opportunities for the generation of value in several …
business models and the opening of opportunities for the generation of value in several …
Time-series classification in smart manufacturing systems: An experimental evaluation of state-of-the-art machine learning algorithms
Manufacturing is transformed towards smart manufacturing, entering a new data-driven era
fueled by digital technologies. The resulting Smart Manufacturing Systems (SMS) gather …
fueled by digital technologies. The resulting Smart Manufacturing Systems (SMS) gather …
Edge intelligence for data handling and predictive maintenance in IIOT
The use of IoT has become pervasive and IoT devices are common in many domains.
Industrial IoT (IIoT) utilises IoT devices and sensors to monitor machines and environments …
Industrial IoT (IIoT) utilises IoT devices and sensors to monitor machines and environments …
Fault detection and classification in oil wells and production/service lines using random forest
This papers deals with the automatic detection and classification of faulty events during the
practical operation of oil and gas wells and lines. The events considered here are part of the …
practical operation of oil and gas wells and lines. The events considered here are part of the …
Open benchmarks for assessment of process monitoring and fault diagnosis techniques: A review and critical analysis
The present paper brings together openly available datasets and simulators for testing of
process monitoring and fault diagnosis techniques. Some general characteristics of these …
process monitoring and fault diagnosis techniques. Some general characteristics of these …
Anomaly detection using explainable random forest for the prediction of undesirable events in oil wells
The worldwide demand for oil has been rising rapidly for many decades, being the first
indicator of economic development. Oil is extracted from underneath reservoirs found below …
indicator of economic development. Oil is extracted from underneath reservoirs found below …
An automated machine learning approach for real-time fault detection and diagnosis
This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time
Fault Detection and Diagnosis (RT-FDD). The approach's particular characteristics are: it …
Fault Detection and Diagnosis (RT-FDD). The approach's particular characteristics are: it …
Improving performance of one-class classifiers applied to anomaly detection in oil wells
The prompt detection and diagnosis of anomalies in oil wells are fundamental to reduce
production losses, maintenance costs and to avoid environmental damage. In this paper, a …
production losses, maintenance costs and to avoid environmental damage. In this paper, a …
[HTML][HTML] Design and implementation of an autonomous systems training environment framework for control algorithm evaluation in autonomous plant operation
The shortage of trained plant operators who can control complex systems in the process and
energy industry is leading to an increasing need for more autonomy of such plants. In future …
energy industry is leading to an increasing need for more autonomy of such plants. In future …