With simulation assistance , the proposed model has been verified with measurement results.
经由电脑模拟与实际量测结果比对后,可验证该模型的准确性.
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A branch - and bound method is developed to solve the proposed model.
设计了基于分枝定界法的算法来求解该模型.
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Furthermore, the proposed model provides better predictive validity than the benchmark models.
而且, 该模型比基准模型提供了更好的预测有效性.
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Our proposed model is verified through experimental study.
用实验研究验证了提出的模型.
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The validity of the proposed model and the approach was verified by experiments.
微动疲劳寿命的预测结果与试验结果的对比表明用本文提出的预测方法是有效的.
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The results show the accordance between the proposed model and the real problem.
结果表明,本文的研究与实际情况相吻合.
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The proposed model can be used to guide the measurement to meet the required measurement accuracy.
本文提出的随机不确定度预测模型可以用于指导ADCP流量测验作业以保证测验精度满足要求.
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Therefore, our proposed model and particle swarm optimization algorithm is validity and feasibility for signal timing.
这表明运用粒子群优化算法解决交叉口配时问题是有效和可行的.
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Comparisions between measured and predicted stress - strain show that the proposed model can give better results.
模型预测值与实测值的应力应变关系比较表明,本文提出的模型是合理的.
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The result shows that the proposed model and algorithm is effective and feasible.
算例仿真与分析的结果表明该文的方法有效、可行.
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The proposed model may also be used to analyze practical reactive load distribution on non - uniform feeders.
该模型适应不均匀馈电线上实际的无功负荷分配.
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