<p><i>Data Mining for Bioinformatics Applications</i> provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. </p><p>The text uses an example-
Data Mining for Geoinformatics: Methods and Applications
β Scribed by Mark Salvador, Ron Resmini (auth.), Guido Cervone, Jessica Lin, Nigel Waters (eds.)
- Publisher
- Springer-Verlag New York
- Year
- 2014
- Tongue
- English
- Leaves
- 175
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The rate at which geospatial data is being generated exceeds our computational capabilities to extract patterns for the understanding of a dynamically changing world. Geoinformatics and data mining focuses on the development and implementation of computational algorithms to solve these problems. This unique volume contains a collection of chapters on state-of-the-art data mining techniques applied to geoinformatic problems of high complexity and important societal value. Data Mining for Geoinformatics addresses current concerns and developments relating to spatio-temporal data mining issues in remotely-sensed data, problems in meteorological data such as tornado formation, estimation of radiation from the Fukushima nuclear power plant, simulations of traffic data using OpenStreetMap, real time traffic applications of data stream mining, visual analytics of traffic and weather data and the 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 areas of data mining and geoscience will also find this book to be a valuable reference.
β¦ Table of Contents
Front Matter....Pages i-xi
Computation in Hyperspectral Imagery (HSI) Data Analysis: Role and Opportunities....Pages 1-27
Toward Understanding Tornado Formation Through Spatiotemporal Data Mining....Pages 29-47
Source Term Estimation for the 2011 Fukushima Nuclear Accident....Pages 49-64
GIS-Based Traffic Simulation Using OSM....Pages 65-82
Evaluation of Real-Time Traffic Applications Based on Data Stream Mining....Pages 83-103
Geospatial Visual Analytics of Traffic and Weather Data for Better Winter Road Management....Pages 105-126
Exploratory Visualization of Collective Mobile Objects Data Using Temporal Granularity and Spatial Similarity....Pages 127-154
Back Matter....Pages 155-166
β¦ Subjects
Data Mining and Knowledge Discovery; Database Management; Geographical Information Systems/Cartography; Artificial Intelligence (incl. Robotics); Earth Sciences, general
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