首页|Researcher from Queensland University of Technology Publishes New Studies and Fi ndings in the Area of Machine Learning (Mapping Urban Floods via Spectral Indice s and Machine Learning Algorithms)
Researcher from Queensland University of Technology Publishes New Studies and Fi ndings in the Area of Machine Learning (Mapping Urban Floods via Spectral Indice s and Machine Learning Algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on artificial intelligence is the su bject of a new report. According to news reporting out of Brisbane, Australia, b y NewsRx editors, research stated, "Throughout history, natural disasters have c aused severe damage to people and properties worldwide." The news journalists obtained a quote from the research from Queensland Universi ty of Technology: "Flooding is one of the most disastrous types of natural disas ters. A key feature of flood assessment has been making use of the information d erived from remote-sensing imagery from optical sensors on satellites using spec tral indices. Here, a study was conducted about a recent spectral index, the Nor malised Difference Inundation Index, and a new ensemble spectral index, the Conc atenated Normalised Difference Water Index, and two mature spectral indices: Nor malised Difference Water Index and the differential Normalised Difference Water Index with four different machine learning algorithms: Decision Tree, Random For est, Naive Bayes, and K-Nearest Neighbours applied to the PlanetScope satellite imagery about the Brisbane February 2022 flood which is in urban environment. St atistical analysis was applied to evaluate the results. Overall, the four algori thms provided no significant difference in terms of accuracy and F1 score."
Queensland University of TechnologyBri sbaneAustraliaAustralia and New ZealandAlgorithmsCyborgsEmerging Techn ologiesMachine Learning