首页|New Findings from Xi’an Jiaotong University Describe Advances in Machine Learnin g (Precise Prediction of Methane-ethane Adsorption In Shale Nanopores Using Mult i-component Models and Machine Learning)
New Findings from Xi’an Jiaotong University Describe Advances in Machine Learnin g (Precise Prediction of Methane-ethane Adsorption In Shale Nanopores Using Mult i-component Models and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating in Shaanxi, Peop le’s Republic of China, by NewsRx editors, the research stated, “Methane and eth ane are the primary hydrocarbon components of shale gas, predominantly adsorbed within shale as a binary mixture. Accurately predicting the adsorption capacity of methane-ethane binary mixtures is crucial for estimating shale gas reserves.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Natural Science Foundation of China (NSFC), Innovat ive Talent Promotion Plan of Shaanxi Province-Scientific and Technological Innov ation Team, Zhuhai Innovation and Entrepreneurship Team Project, Key Technologie s and Industrialization of Solar Powered Multi-Energy Conversion and Complementa ry Integrated Electricity, Heating and Hydrogen Energy System.
ShaanxiPeople’s Republic of ChinaAsi aAlkanesCyborgsEmerging TechnologiesEthaneMachine LearningMethaneX i’an Jiaotong University
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