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A framework for state-based time-series analysis and prediction

A framework for state-based time-series analysis and prediction

Ma, Jixin (2008) A framework for state-based time-series analysis and prediction. International Journal of Computer & Information Science, 9 (1). pp. 21-28. ISSN 1525-9293

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Abstract

Time-series analysis and prediction play an important role in state-based systems that involve dealing with varying situations in terms of states of the world evolving with time. Generally speaking, the world in the discourse persists in a given state until something occurs to it into another state. This paper introduces a framework for prediction and analysis based on time-series of states. It takes a time theory that addresses both points and intervals as primitive time elements as the temporal basis. A state of the world under consideration is defined as a set of time-varying propositions with Boolean truth-values that are dependent on time, including properties, facts, actions, events and processes, etc. A time-series of states is then formalized as a list of states that are temporally ordered one after another. The framework supports explicit expression of both absolute and relative temporal knowledge. A formal schema for expressing general time-series of states to be incomplete in various ways, while the concept of complete time-series of states is also formally defined. As applications of the formalism in time-series analysis and prediction, we present two illustrating examples.

Item Type: Article
Additional Information: [1] First published: January 2008. [2] Published as: International Journal of Computer & Information Science, (2008), Vol. 9 (1) pp. 21-28. [3] The International Journal of Computer & Information Science (IJCIS) is a quarterly publication of the International Association for Computer and Information Science (ACIS). [4] This paper is an edited version of a paper previously presented at the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), entitled "State-based Time-Series Analysis and Prediction", held 30 July – 1 August 2007, in Qingdao, China. (DOI Bookmark for Proceedings: http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.363).
Uncontrolled Keywords: state-based systems, temporal reasoning, time-series analysis and prediction
Subjects: Q Science > Q Science (General)
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Science
Related URLs:
Last Modified: 14 Oct 2016 09:03
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/1332

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