Titlebook: Data Mining for Geoinformatics; Methods and Applicat Guido Cervone,Jessica Lin,Nigel Waters Book 2014 Springer Science+Business Media New Y

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Book 2014the exploratory visualization of collective, mobile objects such as the flocking behavior of wild chickens.This book is designed for researchers and advanced-level students focused on computer science, earth science and geography as a reference or secondary text book. Practitioners working in the ar

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Variables and Symbolic Messagesy appropriate configurations for ITS and to evaluate different mining methods for data analysis. The framework consists of a traffic simulation software, a data stream management system, utilizes data stream mining algorithms, and provides a flexible ontology-based component for data quality monitor

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Variables and Symbolic Messagesd segments shows how different roads are affected by heavy snowfall, by snow plowing, and by snow removal. Combining geospatial visualization with knowledge discovery algorithms is a potential approach in this area. An example would be clustering the road segments based on similarity of the impact s

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of wild chickens.This book is designed for researchers and advanced-level students focused on computer science, earth science and geography as a reference or secondary text book. Practitioners working in the ar978-1-4899-8574-3978-1-4614-7669-6

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Evaluation of Real-Time Traffic Applications Based on Data Stream Mining,y appropriate configurations for ITS and to evaluate different mining methods for data analysis. The framework consists of a traffic simulation software, a data stream management system, utilizes data stream mining algorithms, and provides a flexible ontology-based component for data quality monitor

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Geospatial Visual Analytics of Traffic and Weather Data for Better Winter Road Management,d segments shows how different roads are affected by heavy snowfall, by snow plowing, and by snow removal. Combining geospatial visualization with knowledge discovery algorithms is a potential approach in this area. An example would be clustering the road segments based on similarity of the impact s

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Computation in Hyperspectral Imagery (HSI) Data Analysis: Role and Opportunities,ough HSI data sets are stacks of images and may be viewed as images by analysts, harnessing the full power of HSI requires working primarily in the spectral domain. Algorithms with a broad range of sophistication and complexity are required to sift through the immense quantity of spectral signatures