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A Service-Oriented Architecture Based Macroeconomic Analysis & Forecasting System

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Book cover Frontiers of WWW Research and Development - APWeb 2006 (APWeb 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3841))

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Abstract

Macroeconomic analysis & forecasting system (MAFS) simulates and forecasts economy macroeconomic cycle trend by analyzing the macroeconomic data using various models. Currently, as a system, which should integrate multi-model and multi-data-source, MAFS has two bottlenecks in its development and application, i.e. models’ update, reuse and system integration, and data update and integration. This paper proposes a Service-Oriented-Architecture (SOA)-based Macroeconomic Analysis & Forecasting System, named SMAFS to solve the problems. In SMAFS, certain econometric models and data are encapsulated with the form of Web Services, which are distributed in network space and can be reorganized into seamless integrated system through the standard programming and data interfaces. By this architecture, the system’s abilities of software reusing and cross-platform are highly enhanced. The architecture, functionality and implementing methods of the system are presented and discussed. The workflow of SMAFS is presented and the design of Web Services of this system is described. A case example is demonstrated and proves that the SMAFS can highly enhance the effectiveness of data collecting and processing.

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© 2006 Springer-Verlag Berlin Heidelberg

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Han, D., Huang, H., Cao, H., Cui, C., Jia, C. (2006). A Service-Oriented Architecture Based Macroeconomic Analysis & Forecasting System. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds) Frontiers of WWW Research and Development - APWeb 2006. APWeb 2006. Lecture Notes in Computer Science, vol 3841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11610113_118

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  • DOI: https://doi.org/10.1007/11610113_118

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31142-3

  • Online ISBN: 978-3-540-32437-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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