首页|Research from University of Texas Arlington Reveals New Findings on Machine Lear ning (Estimation of Suspended Sediment Concentration along the Lower Brazos Rive r Using Satellite Imagery and Machine Learning)
Research from University of Texas Arlington Reveals New Findings on Machine Lear ning (Estimation of Suspended Sediment Concentration along the Lower Brazos Rive r Using Satellite Imagery and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news reporting from Arlington, Texas, b y NewsRx journalists, research stated, "This article focuses on developing model s that estimate suspended sediment concentrations (SSCs) for the Lower Brazos Ri ver, Texas, U.S." The news correspondents obtained a quote from the research from University of Te xas Arlington: "Historical samples of SSCs from gauge stations and satellite ima gery from Landsat Missions and Sentinel Mission 2 were utilized to develop model s to estimate SSCs for the Lower Brazos River. The models used in this study to accomplish this goal include support vector machines (SVMs), artificial neural n etworks (ANNs), extreme learning machines (ELMs), and exponential relationships. In addition, flow measurements were used to develop rating curves to estimate S SCs for the Brazos River as a baseline comparison of the models that used satell ite imagery to estimate SSCs. The models were evaluated using a Taylor Diagram a nalysis on the test data set developed for the Brazos River data."
University of Texas ArlingtonArlingtonTexasUnited StatesNorth and Central AmericaCyborgsEmerging Technologie sMachine Learning
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