SHALLOW LANDSLIDE SUSCEPTIBILITY MODELING USING THE DATA MINING MODELS ARTIFICIAL NEURAL NETWORK AND BOOSTED TREE

Shallow Landslide Susceptibility Modeling Using the Data Mining Models Artificial Neural Network and Boosted Tree

The main purpose of this paper is to present some potential applications of sophisticated data mining techniques, such as artificial neural network (ANN) and boosted tree (BT), for landslide susceptibility modeling in the Yongin area, Korea.Initially, landslide inventory was detected from visual interpretation using digital aerial photographic maps

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A containerised approach for multiform robotic applications

As the area of robotics achieves promising results, there is an increasing Heritage Banners need to scale robotic software architectures towards real-world domains.Traditionally, robotic architectures are integrated using common frameworks, such as ROS.Therefore, systems with a uniform structure are produced, making it difficult to integrate third

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Components of quantitative resistance in barley plants to Fusarium head blight infection determined using three in vitro assays

Quantitative resistance in barley to four Fusarium head blight (FHB) species was investigated in vitro.Nine components involved in three assays (detached leaf, modified Petridish and seedling tests) were compared on two widely grown Syrian barley cultivars: Arabi Aswad (AS) and Arabi Abiad (AB).On AB, inoculation with FHB species resulted in a sign

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