首页|Findings from Federal Waterways Engineering and Research Institute in Machine Le arning Reported (Using statistical and machine learning approaches to describe e stuarine tidal dynamics)
Findings from Federal Waterways Engineering and Research Institute in Machine Le arning Reported (Using statistical and machine learning approaches to describe e stuarine tidal dynamics)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on artificial in telligence have been published. According to news reporting originating from Ham burg, Germany, by NewsRx correspondents, research stated, "Estuaries are ecologi cally valuable regions where tidal forces move large volumes of water. To unders tand the ongoing physical processes in such dynamic systems, a series of estuari ne monitoring stations is required." Our news reporters obtained a quote from the research from Federal Waterways Eng ineering and Research Institute: "Based on the measurements, estuarine dynamics can be described by key values, so-called tidal characteristics. The reconstruct ion and prediction of tidal characteristics by suitable approaches is essential to discover natural or anthropogenic changes. Therefore, it is of interest to in ter- and extrapolate measured values in time and to investigate the spatial rela tionship between different stations. Normally, such system analyses are performe d by deterministic numerical models. However, to facilitate long-term investigat ions also, statistical and machine learning approaches are good options. For a W eser estuary case study, we implemented three approaches (linear, non-linear, an d artificial neural network regression) with the same database to enable the pre diction of tidal extrema."
Federal Waterways Engineering and Resear ch InstituteHamburgGermanyEuropeCyborgsEmerging TechnologiesMachine Learning
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