最后，通过应用实例展示了利用集成神经网络进行产品完工期预测的全过程。
Finally, a case study was given to illustrate the whole steps to predict the product due date by using neural network ensemble.
通过仿真分析，可以对施工机械的机型、数量以及作业参数作出最佳选择，并且预测出施工的最短工期和最低施工费用。
By simulating analysis, the optimal parameters, Numbers and type of construction machinery can be obtained, and the smallest cost and shortest period of construction projects can be predicted.
该方法能改进传统挣值法在预测工期、成本方面产生的偏差，并且与传统挣值方法相比，增加了更多的原因分析信息。
It corrects the deviation derived from traditional earned value method when forecasting the duration and cost, and it supplies more analysis information than traditional earned value method.
提出了如果需要达到最优化压缩的目的，需要预测整个项目的最优总工期的问题，为第四章的研究提出了要求。
Besides, it lodges that, to reach the aim of optimizing compress, there needs to forecast the best total time for an entire project, bringing forward a request for study of chapter four.
首先描述六种项目状态下项目进度预测问题，系统阐述计划价值率法、挣得工期法和挣得进度法的进度预测方法。
Firstly, the schedule performance prediction problem in the six statues is described. The plan valued rate method, earned duration method and the earned schedule method are then introduced.
利用直接费用、间接费用与总费用的关系，预测出总费用最低时对应的工期，从而给出了工期一费用的最优决策。
Making use of the relations among the direct cost, the indirect cost and the total cost, we get the best time limit for the project with results of the optimal T-C decision-making.
在有限元法计算结果的基础上，用神经网络方法对洞室施工期应力及变形进行预测。
The stresses and deformations of rocks during tunnel excavation are predicted using an ANN approach based on results of FEM simulation.
在有限元法计算结果的基础上，用神经网络方法对洞室施工期应力及变形进行预测。
The stresses and deformations of rocks during tunnel excavation are predicted using an ANN approach based on results of FEM simulation.
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