… This work proposes a semi-supervised machine learning … Although pipelines have the
lowest accident rates compared to … to the oil industry. CONCAWE associated the failures in the …

… semi-supervised learning by using a real-world case. The accuracy of the hybrid model is
verified in comparison with other traditional machine learning … the fault detection of pipeline …

… accident data and a large amount of fault-free data, which cannot be directly trained by machine
learning. … pretreatment process, which comprises hazard identification, risk analysis, and …

… available data and basic deep learning models to improve … Many works treat pipeline
inspection signals as images and … pipeline accidents by 25%, thus improving the safety of the …

… of the gas and oil industry. Modern data-driven fault … a semi-supervised machine learning
method based on multivariate time series data for leak detection of natural gas pipelines. Thus, …

… in detection or estimation by the machine learning algorithms. … oil and gas industry has had
its share of disastrous accidents … There is also semi-supervised learning, which results when …

… a semi-supervised machine learning … a subsea oil pipeline for fault detection using a machine
learning (ML) program It intended to enhance the process monitoring capability of crude oil …

… pipeline system leakage detection method based on semi-supervised anomaly identification
… Leakage accidents of low-pressure gas systems in buildings often directly threaten the lives …

… of such pipeline accidents that … detecting defects in pipelines can be classified into different
categories, including supervised, semi-supervised, unsupervised, or reinforcement learning, …

… around the track lines. This … detection based on deep learning can be divided into two
categories, ie, the classification methods based on deep neural networks and the target detection …