Abstract
Work breakdown structures are the basis of project management. But there are few researches on the methods or tools to design work breakdown structures effectively. In this paper, a framework which employs neural networks to plan the work breakdown structures has been introduced. The main concepts, including domain tree structure(DTS), domain work breakdown structure(DWBS) and relational work breakdown structure(RWBS), have used to form the outputs of the model. The nature of projects, which have been represented by a limited set of attributes, are considered as the main inputs of the model. Since the work breakdown structure is a hierarchical structure, DWBS has been broken into levels to reduce the complexity of reasoning and calculation. In addition, to make sure the result WBS is optimized and can be mapped into other WBSs effectively, Axiomatic Design Theory was used to verify the RWBSs at each level.
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© 2009 Springer-Verlag Berlin Heidelberg
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Bai, Y., Zhao, Y., Chen, Y., Chen, L. (2009). Designing Domain Work Breakdown Structure (DWBS) Using Neural Networks. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_127
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DOI: https://doi.org/10.1007/978-3-642-01513-7_127
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01512-0
Online ISBN: 978-3-642-01513-7
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