Surveillance Technologies and Early Warning Systems: Data by Ali Serhan Koyuncugil, Nermin Ozgulbas PDF

By Ali Serhan Koyuncugil, Nermin Ozgulbas

ISBN-10: 1616928654

ISBN-13: 9781616928650

ISBN-10: 1616928670

ISBN-13: 9781616928674

The smooth international is fraught with threat, from ordinary mess ups and terrorist assaults, to monetary crises and pandemics. Assessing and making plans for those hazards might be performed with a traditional human-based technique yet this usually calls for quite a lot of time and resources.

Surveillance applied sciences and Early caution structures: info Mining functions for chance Detection hasn't ever been extra very important, because the study this publication offers an alternative choice to traditional surveillance and probability evaluate. This ebook is a multidisciplinary expedition created from facts mining, early caution platforms, details applied sciences and hazard administration and explores the intersection of those parts in difficult domains.  It deals the power to use the main sleek suggestions to age previous difficulties taking into consideration elevated effectiveness within the reaction to destiny, eminent, and current risk.

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Extra resources for Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection

Example text

Annals of the New York Academy of Sciences, 1020, 10–21. 003 Overview of Knowledge Discovery in Databases Process and Data Mining Kim, T. , Oh, K. , & Hwang, C. (2004). Usefulness of artificial neural networks for early warning system of economic crisis. Expert Systems with Applications, 26, 583–590.

It can be modeled by using a linear or nonlinear mathematical model. Usually simple methods help us to detect (estimate) trends. One of them is the free-hand method which is a subjective approach. More objective methods include smoothing techniques and least squares method. Detecting components other than trend requires more elaborate technique to be used. For example, autocorrelation function can be utilized for detecting seasonal patterns that may emerge at a particular time of year. Transformations can contribute pattern detection by reducing the number of dimensions or stabilizing the variance.

Usually simple methods help us to detect (estimate) trends. One of them is the free-hand method which is a subjective approach. More objective methods include smoothing techniques and least squares method. Detecting components other than trend requires more elaborate technique to be used. For example, autocorrelation function can be utilized for detecting seasonal patterns that may emerge at a particular time of year. Transformations can contribute pattern detection by reducing the number of dimensions or stabilizing the variance.

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Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection by Ali Serhan Koyuncugil, Nermin Ozgulbas


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