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通过应用误差反向传播(Back Propagation,BP)神经网络数学模型,利用神经网络充分逼近任意复杂的非线性系统;可学习与适应严重不确定性系统的动态特性和具有很强的鲁棒性和容错性的优点,预测一定投入的项目各自的项目进度结果。实际应用中,根据进度目标和环境条件,有效控制工程进度,这对于完成部队整体计划,节约成本和管理效益最高化具有重要意义。
By applying BP (Back Propagation) neural network mathematic model, neural network can be used to approximate any complex nonlinear system sufficiently. It can learn and adapt to the dynamic characteristics of severe uncertain system and has strong robustness. Fault tolerance, predict the project results of each project that must be invested. In practical application, the progress of the project is effectively controlled according to the progress target and the environmental conditions, which is of great significance for completing the overall plan of the army, saving costs and maximizing management efficiency.