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Advances in Innovative Computing Paradigms

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Applied Time Series Analysis and Innovative Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 59))

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Abstract

In this chapter, it is the brief introduction to the innovative computing paradigms, the advances in the technology and the outline of the recent works of the innovative computing projects. There are different techniques to extract information from various kinds of datasets. In Section 3.1, it is about the research advances in computing algorithms and databases, covering topics like knowledge extraction, data mining algorithms, quantum computing, and DNA computing. In Section 3.2, the focus is on the advances in integration of hardware, systems and networks. Topics like innovative hardware system, graphics processing units, visual exploration, network interoperability, and code optimization are discussed. Section 3.3 is about the advances in Internet and grid computing. Updates about distributed computation, large-scale collaborations over the Internet, pooling of computer resources, and knowledge metadata systems are presented. The advances in visualization, design and communication are described in Section 3.4. Section 3.5 is about the advances of innovative computing for time series problems, like retrieval, automatic classification, clustering, and automatic monitoring of time series. In the last section, it is illustrated how to build an innovative computing algorithm for some simulated time series. Then, in the next three chapters, innovative computer algorithms are built for some real time series data in business, biology and physics.

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  1. International Association of Engineers, Unit 1, 1/F, 37–39 Hung To Road, Hong Kong, China

    Sio-Iong Ao

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Ao, SI. (2010). Advances in Innovative Computing Paradigms. In: Applied Time Series Analysis and Innovative Computing. Lecture Notes in Electrical Engineering, vol 59. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8768-3_3

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