首页|New Study Findings from Shandong University Illuminate Research in Support Vecto r Machines (Underwater Sound Speed Field Forecasting Based on the Least Square S upport Vector Machine)
New Study Findings from Shandong University Illuminate Research in Support Vecto r Machines (Underwater Sound Speed Field Forecasting Based on the Least Square S upport Vector Machine)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on . According to news reporting from Weihai, People's Republic of China, by NewsRx j ournalists, research stated, "Underwater sound speed is one of the most signific ant factors that affects high-accuracy underwater acoustic positioning and navig ation." Financial supporters for this research include National Natural Science Foundati on of China; Shandong Provincial Natural Science Foundation; China Post-doctoral Science Foundation; Open Foundation of The State Key Laboratory of Geo-informat ion Engineering. Our news editors obtained a quote from the research from Shandong University: "D ue to its complex temporal variation, the forecasting of the underwater sound sp eed field (SSF) becomes a challenging task. Taking advantage of machine learning methods, we propose a new method for SSF forecasting based on the least square support vector machine (LSSVM) and a multi-parameter model, aiming to enhance th e forecasting accuracy of underwater SSF with hourly resolution. We first use a matching extension method to standardize profile data and train the LSSVM with t he parameters of observation time, temperature, salinity, and depth. We then emp loy radial basis function kernels to construct the forecasting model of SSF."
Shandong UniversityWeihaiPeople's Re public of ChinaAsiaEmerging TechnologiesMachine LearningSupport Vector M achinesVector Machines
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