首页|Recent Research from Guangdong Ocean University Highlight Findings in Support Ve ctor Machines (Application of Support Vector Machines and Genetic Algorithms To Fluid Identification In Offshore Granitic Subduction Hill Reservoirs)
Recent Research from Guangdong Ocean University Highlight Findings in Support Ve ctor Machines (Application of Support Vector Machines and Genetic Algorithms To Fluid Identification In Offshore Granitic Subduction Hill Reservoirs)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – A new study on Support Vector Machines is now ava ilable. According to news reporting out ofZhanjiang, People’s Republic of China , by NewsRx editors, research stated, “YL8 area granite submarineis located in the Songnan low uplift of Qiongdongnan Basin, submarine reservoir fracture devel opment,non-homogeneous strong. Geophysical logging and gas logging do not show a clear pattern of response tothe fluid properties of submarine reservoirs, and it is difficult to use logging information to linearly classifygranite submari ne reservoir fluids in two dimensions.”
ZhanjiangPeople’s Republic of ChinaA siaAlgorithmsEmerging TechnologiesGenetic AlgorithmGenetic AlgorithmsG eneticsMachine LearningMathematicsSupport Vector MachinesVector MachinesGuangdong Ocean University