294
Views
6
CrossRef citations to date
0
Altmetric
Original Articles

Integrated buffer monitoring and control based on grey neural network

&
Pages 516-529 | Received 12 Jan 2017, Accepted 20 Feb 2018, Published online: 25 Apr 2018
 

Abstract

Classic buffer monitoring methods only consider the buffer consumption amount, while the subsequent trend information of buffer consumption is ignored. In this paper, we propose an integrated buffer monitoring method. First, the prediction model based on grey neural network is established, and the follow-up buffer consumption is predicted quantitatively according to the past and present performance data at the project monitoring points. Second, considering the relationship between the buffered consumed and the follow-up buffer consumption, a buffer integrated monitoring system is formed based on the integrated quantitative analysis on the buffer consumed and the subsequent trend information at each monitoring point. Finally, the Monte Carlo simulation experiment is carried out to validate the model system. The results show that, as opposed to the classic buffer monitoring methods, the proposed method can control the progress of the project comprehensively and reduce the fluctuation of project duration, thus achieving the double optimisation of project duration and cost under the premise of guaranteeing the completion probability.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 277.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.