首页|Researchers from Prince of Songkla University Describe Findings in Support Vecto r Machines (Temporal Analysis and Future Prediction of Billion Tree Tsunami Fore sts: a Case Study of Garhichandan Pakistan)
Researchers from Prince of Songkla University Describe Findings in Support Vecto r Machines (Temporal Analysis and Future Prediction of Billion Tree Tsunami Fore sts: a Case Study of Garhichandan Pakistan)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning - Support Vector Machines. Accordingto news originating from Hat Yai, Thailand, by NewsRx correspondents, research stated, “This articleinvestigates the temporal analysis of billion tree tsunami forests in Garhi Chandan area of Pakistan basedon three supervised methods, namely random forest algorithm (RFA) , principal component analysis (PCA)combined RFA and support vector machine (SV M). As a first step, the Sentinel-2 and Landsat-8 datafusion is performed to en hance the spatial resolution of the data to 10 m. The overlapping features in the data may compromise the classification accuracy, thus, to overcome this limita tion, PCA is utilized.”
Hat YaiThailandAsiaMachine Learnin gSupport Vector MachinesPrince of Songkla University
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