首页|Reports from University of Delhi Add New Study Findings to Research in Machine L earning [Landslide susceptibility analysis in the Bhilangana Basin (India) using GIS-based machine learning methods]

Reports from University of Delhi Add New Study Findings to Research in Machine L earning [Landslide susceptibility analysis in the Bhilangana Basin (India) using GIS-based machine learning methods]

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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on artificial intelligenc e is the subject of a new report. According tonews reporting out of Delhi, Indi a, by NewsRx editors, research stated, “Landslides are frequent naturalhazards in mountainous regions, and harshly upset people’s lives and livelihoods.”Our news correspondents obtained a quote from the research from University of De lhi: “In the presentstudy, we have carried out an analysis of seven GIS-based m achine-learning techniques; and asses theirperformance for landslide susceptibi lity mapping (LSM) in the Bhilangana Basin, Garhwal Himalaya. Alandslide invent ory consisting of 423 polygons was prepared using repeated field investigations, and multidatedsatellite images for the periods between 2000 and 2022. The lan dslide dataset was classified intotwo groups: training (70%) and t est dataset (30%), and 12 predictive variables were used for the LSM. The methods used to produce LSM are boosted regression tree (BRT), Fisher dis criminant analysis(FDA), generalized linear model (GLM), multivariate adaptive regression splines (MARS), model-architectanalysis (MDA), random forest (RF) an d support vector machine (SVM). The sensitivity and performanceof these models to predict landslide susceptible areas were carried out using the area under the curve (AUC)method. The RF model (AUC = 0.988) has given the highest precision indicating the best performance.”

University of DelhiDelhiIndiaAsiaCyborgsEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(MAY.6)