Introductory Chapter: Time Series Analysis (TSA) for Anomaly Detection in IoT

  • Mohamudally N
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Abstract

Time Series Analysis (TSA) and Applications offers a dense content of current research and development in the field of data science. The book presents time series from a multidisciplinary approach that covers a wide range of sectors ranging from biostatistics to renewable energy forecasting. Contrary to previous literatures on time, serious readers will discover the potential of TSA in areas other than finance or weather forecasting. The choice of the algorithmic transform for different scenarios, which is a key determinant in the application of TSA, can be understood through the diverse domain applications. Readers looking for deep understanding and practicability of TSA will be delighted. Early career researchers too will appreciate the technicalities and refined mathematical complexities surrounding TSA. Our wish is that this book adds to the body of TSA knowledge and opens up avenues for those who are looking forward to applying TSA in their own context.

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APA

Mohamudally, N. (2018). Introductory Chapter: Time Series Analysis (TSA) for Anomaly Detection in IoT. In Time Series Analysis and Applications. InTech. https://doi.org/10.5772/intechopen.72669

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