基于神经网络的复杂项目主动管理方法

V. Morozov, O. Kalnichenko, M. Proskurin
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引用次数: 3

摘要

本文在考虑项目的两个关键参数——时间和成本偏差的基础上,提出了在复杂IT项目中使用两种主动变更管理方法的研究结果。利用深度训练神经网络对项目外部和内部环境变化影响下的项目状态进行预测估计。这种方法允许在项目实施期间的任何时间预测项目活动结果的变化水平。对项目参数变化影响的建模结果进行评估时,要考虑到项目的环境特征,包括时间和项目工作中的资源分配、成本分配等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methods of Proactive Management of Complex Projects Based on Neural Networks
In this paper, the results of research into the use of two methods of proactive change management in complex IT projects are presented based on the consideration of deviations in two key parameters of projects - in time and cost. Forecast estimates of the status of projects as a result of impacts of changes in the external and internal environment of projects are modeled using neural networks of deep training. This approach allows to predict the level of changes in the results of the project activity at any time during the implementation of projects. The evaluation of the results of modeling the effects of changes on project parameters is carried out taking into account the context characteristics of projects, including resource allocations both in time and in project work, cost allocations, etc.
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