首页|Researchers from Department of Geography Detail Findings in Machine Learning (Li nkages Between Gully Erosion Susceptibility and Hydrological Connectivity In Tro pical Sub-humid River Basin: Application of Machine Learning Algorithms and ...)
Researchers from Department of Geography Detail Findings in Machine Learning (Li nkages Between Gully Erosion Susceptibility and Hydrological Connectivity In Tro pical Sub-humid River Basin: Application of Machine Learning Algorithms and ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Current study results on Machine Learning have be en published. According to news originatingfrom Kolkata, India, by NewsRx corre spondents, research stated, “Hydrological connectivity from upslopeto downslope of valley floor and main channel, triggered the gully initiation and associated land degradationcontinue occurring off-site erosion as considered most effecti ve drivers on potential sediment detachment.Present study attempted to identify the linkage between gullies erosion susceptibility (GES) and hydrologicalconne ctivity pathway in sub-tropical humid river basin Kangsabati (KRB) using four ma chine-learningalgorithms (MLALs) such as Random Forest (RF), Support Vector Mac hine (SVM), Extreme GradientBoosting (XGB), Artificial Neural Network (ANN) for GES mapping, and connectivity index (IC) forhydrological connectivity mapping. ”
KolkataIndiaAsiaAlgorithmsCyborg sEmerging TechnologiesMachine LearningDepartment of Geography
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