[下载]Ph.D. dissertation: Time Series Data Mining: Identifying Temporal Patterns f

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Ph.D. dissertation: Time Series Data Mining: Identifying Temporal Patterns for Characterization and Prediction of Time Series EventsRichard J. Povinelli

Department of Electrical and Computer Engineering, Marquette University Milwaukee, Wisconsin

Abstract: A new framework for analyzing time series data called Time Series Data Mining (TSDM) is introduced. This framework adapts and innovates data mining concepts to analyzing time series data. In particular, it creates a set of methods that reveal hidden temporal patterns that are characteristic and predictive of time series events. Traditional time series analysis methods are limited by the requirement of stationarity of the time series and normality and independence of the residuals. Because they attempt to characterize and predict all time series observations, traditional time series analysis methods are unable to identify complex (nonperiodic, nonlinear, irregular, and chaotic) characteristics. TSDM methods overcome limitations of traditional time series analysis techniques. A brief historical review of related fields, including a discussion of the theoretical underpinnings for the TSDM framework, is made. The TSDM framework, concepts, and methods are explained in detail and applied to real-world time series from the engineering and financial domains.

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2005-4-19 11:15:00 上传

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关键词：dissertation Time Series Identifying Data Mining Identifyin Mining Series Prediction dissertation Events

it's too dear!

到这里下载免费的http://povinelli.eece.mu.edu/publications/papers/dissertation.pdf

谢谢！免费不错

thanks for provding free paper,

elzyyzl 发表于 2008-5-4 16:32
到这里下载免费的http://povinelli.eece.mu.edu/publications/papers/dissertation.pdf

感谢告知～