AIMC Topic: Petroleum

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An analysis of crude oil prices in the last decade (2011-2020): With deep learning approach.

PloS one Mar 9, 2023
Crude Oil is one of the most important commodities in this world. We have studied the effects of Crude Oil inventories on crude oil prices over the last ten years (2011 to 2020). We tried to figure out how the Crude Oil price variance responds to inv...
Deep Learning Petroleum Neural Networks, Computer Machine Learning
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A Deep Spiking Neural Network Anomaly Detection Method.

Computational intelligence and neuroscience Sep 21, 2022
Cyber-attacks on specialized industrial control systems are increasing in frequency and sophistication, which means stronger countermeasures need to be implemented, requiring the designers of the equipment in question to re-evaluate and redefine thei...
Humans Neural Networks, Computer Computers Commerce Brain Petroleum
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Improved CEEMDAN, GA, and SVR Model for Oil Price Forecasting.

Journal of environmental and public health Jun 27, 2022
Accurate prediction of crude oil prices (COPs) is a challenge for academia and industry. Therefore, the present research developed a new CEEMDAN-GA-SVR hybrid model to predict COPs, incorporating complete ensemble empirical mode decomposition with ad...
Forecasting Petroleum Support Vector Machine
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A Combined Semi-Supervised Deep Learning Method for Oil Leak Detection in Pipelines Using IIoT at the Edge.

Sensors (Basel, Switzerland) May 28, 2022
Pipelines are integral components for storing and transporting liquid and gaseous petroleum products. Despite being durable structures, ruptures can still occur, resulting not only in financial losses and energy waste but, most importantly, in immeas...
Deep Learning Supervised Machine Learning Humans Petroleum Neural Networks, Computer
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Use of gamma radiation and artificial neural network techniques to monitor characteristics of polyduct transport of petroleum by-products.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine May 4, 2022
This study presents a methodology based on the dual-mode gamma densitometry technique in combination with artificial neural networks to simultaneously determine type and quantity of four different fluids (Gasoline, Glycerol, Kerosene and Fuel Oil) to...
Petroleum Photons Gamma Rays Neural Networks, Computer
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A novel deep learning method for marine oil spill detection from satellite synthetic aperture radar imagery.

Marine pollution bulletin Apr 29, 2022
Oil spill discharges from operational maritime activities like ships, oil rigs and other structures, leaking pipelines, as well as natural hydrocarbon seepage pose serious threats to marine ecosystems and fisheries. Satellite synthetic aperture radar...
Petroleum Petroleum Pollution Radar Ecosystem Deep Learning Environmental Monitoring Water Pollutants, Chemical
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A Neural Network-Based Model for Predicting Saybolt Color of Petroleum Products.

Sensors (Basel, Switzerland) Apr 6, 2022
Saybolt color is a standard measurement scale used to determine the quality of petroleum products and the appropriate refinement process. However, the current color measurement methods are mostly laboratory-based, thereby consuming much time and bein...
Neurons Linear Models Neural Networks, Computer Algorithms Petroleum
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Forecasting the realized variance of oil-price returns: a disaggregated analysis of the role of uncertainty and geopolitical risk.

Environmental science and pollution research international Mar 7, 2022
We contribute to the empirical literature on the predictability of oil-market volatility by comparing the predictive role of aggregate versus several disaggregated metrics of policy-related and equity-market uncertainties of the USA and geopolitical ...
Uncertainty Petroleum Forecasting Machine Learning
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Concentration-Emission Matrix (CEM) Spectroscopy Combined with GA-SVM: An Analytical Method to Recognize Oil Species in Marine.

Molecules (Basel, Switzerland) Nov 4, 2020
The establishment and development of a set of methods of oil accurate recognition in a different environment are of great significance to the effective management of oil spill pollution. In this work, the concentration-emission matrix (CEM) is formed...
Petroleum Pollution Seawater Petroleum Principal Component Analysis Support Vector Machine Water Pollutants, Chemical Spectroscopy, Near-Infrared
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Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils.

Ecotoxicology and environmental safety Mar 9, 2020
Environment pollutants, especially those from total petroleum hydrocarbons (TPH), have a highly complex chemical, biological and physical impact on soils. Here we study this influence via modelling the TPH acute phytotoxicity effects on eleven sample...
Hordeum Models, Theoretical Petroleum Artificial Intelligence Soil Pollutants Neural Networks, Computer Islands Soil Hydrocarbons Soil Microbiology Russia
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