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Natural Gas

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Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

PloS one
Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybri...

Forecasting annual natural gas consumption via the application of a novel hybrid model.

Environmental science and pollution research international
Accurate prediction of natural gas consumption (NGC) can offer effective information for energy planning and policy-making. In this study, a novel hybrid forecasting model based on support vector machine (SVM) and improved artificial fish swarm algor...

Deep Learning Approach for Detection of Underground Natural Gas Micro-Leakage Using Infrared Thermal Images.

Sensors (Basel, Switzerland)
The leakage of underground natural gas has a negative impact on the environment and safety. Trace amounts of gas leak concentration cannot reach the threshold for direct detection. The low concentration of natural gas can cause changes in surface veg...

Shale gas geological "sweet spot" parameter prediction method and its application based on convolutional neural network.

Scientific reports
Parameters such as gas content (GAS), porosity (PHI) and total organic carbon (TOC) are key parameters that reveal the shale gas geological "sweet spot" of reservoirs. However, the lack of a three-dimensional high-precision prediction method is not c...

Predicting the monthly consumption and production of natural gas in the USA by using a new hybrid forecasting model based on two-layer decomposition.

Environmental science and pollution research international
As an efficient, economical, and clean energy, natural gas plays an important role in the development of the new energy revolution. Accurate prediction of natural gas consumption and production can adjust energy deployment in advance, which can ensur...

Probabilistic real-time natural gas jet fire consequence modeling of offshore platforms by hybrid deep learning approach.

Marine pollution bulletin
Natural gas jet fire induced by igniting blowouts has the potential to cause critical structure damage and great casualties of offshore platforms. Real-time natural gas jet fire plume prediction is essential to support the emergency planning to mitig...

Early Detection of Pipeline Natural Gas Leakage from Hyperspectral Imaging by Vegetation Indicators and Deep Neural Networks.

Environmental science & technology
The timely detection of underground natural gas (NG) leaks in pipeline transmission systems presents a promising opportunity for reducing the potential greenhouse gas (GHG) emission. However, existing techniques face notable limitations for prompt de...

Fuzzy set-based decision support system for hydrogen sulfide removal technology selection in natural gas processing: a sustainability and efficiency perspective.

Environmental monitoring and assessment
Removing hydrogen sulfide (HS) toxic and corrosive gas from the natural gas processing and utilization industry is a challenging problem for managers of these industries. This problem involves different economic, environmental, and health issues. Var...

An ML-Enhanced Laser-Based Methane Slip Sensor Using Wavelength Modulation Spectroscopy.

ACS sensors
Natural gas (NG) is a promising alternative to diesel for sustainable transport, potentially reducing GHG and air quality emissions significantly. However, the GHG benefits hinge on managing methane slip, the unburned methane in the exhaust of NG eng...