首页|Researchers from Guangzhou University Detail Findings in MachineLearning (A Stu dy On Global Oceanic Chlorophyll-a ConcentrationInversion Model for Modis Using Machine Learning Algorithms)
Researchers from Guangzhou University Detail Findings in MachineLearning (A Stu dy On Global Oceanic Chlorophyll-a ConcentrationInversion Model for Modis Using Machine Learning Algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Fresh data on Machine Learning are presented in a new report. According to news reportingoriginating in Guangzhou, People’s Repu blic of China, by NewsRx journalists, research stated, “Machinelearning (ML) al gorithms can accurately extract quantitative patterns from datasets without requ iring priorknowledge, playing an increasingly crucial role in tasks such as inf ormation extraction from remotely senseddata. This study employs several ML alg orithms, including Back Propagation Network (BPN), SupportVector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), to developglobal oceanic chlorophyll-a (Chl-a) concentration inversion models for MODIS/Aqua (MOD ISA).”Funders for this research include National Key Research & Developm ent Program of China, NationalNatural Science Foundation of China (NSFC), Basic and Applied Basic Research Project of Guangzhou,Special Projects in Key Fields of Universities in Guangdong Province.
GuangzhouPeople’s Republic of ChinaA siaAlgorithmsBiological FactorsChlorophyllChlorophyllidesCyborgsEmer ging TechnologiesMachine LearningMetalloporphyrinsPorphyrinsRemote Sensi ngSupport Vector MachinesGuangzhou University
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