首页|Researcher from National Research Council of Canada Provides Details of New Stud ies and Findings in the Area of Machine Learning (Estimation of instantaneous pe ak flows in Canadian rivers: an evaluation of conventional, nonlinear regression , ...)
Researcher from National Research Council of Canada Provides Details of New Stud ies and Findings in the Area of Machine Learning (Estimation of instantaneous pe ak flows in Canadian rivers: an evaluation of conventional, nonlinear regression , ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting out of Ottawa, Can ada, by NewsRx editors, research stated, “Instantaneous peak flows (IPFs) are of ten required to derive design values for sizing various hydraulic structures, su ch as culverts, bridges, and small dams/levees, in addition to informing several water resources management-related activities.” Our news journalists obtained a quote from the research from National Research C ouncil of Canada: “Compared to mean daily flows (MDFs), which represent averaged flows over a period of 24 h, information on IPFs is often missing or unavailabl e in instrumental records. In this study, conventional methods for estimating IP Fs from MDFs are evaluated and new methods based on the nonlinear regression fra mework and machine learning architectures are proposed and evaluated using strea mflow records from all Canadian hydrometric stations with natural and regulated flow regimes. Based on a robust model selection criterion, it was found that mul tiple methods are suitable for estimating IPFs from MDFs, which precludes the id ea of a single universal method. The performance of machine learning-based metho ds was also found reasonable compared to conventional and regression-based metho ds.”
National Research Council of CanadaOtt awaCanadaNorth and Central AmericaCyborgsEmerging TechnologiesMachine Learning
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