基于GM (1, N)和MLP神经网络组合模型的民用飞机研制成本估算

Yin Songming, Xie Naiming, H. Chuanzhen
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引用次数: 4

摘要

对民用飞机研制成本进行科学的预测和估算,不仅有利于加强对成本的控制,也是保证项目成功的关键。考虑到民机成本影响因素复杂,且样本数据稀缺,采用组合模型。首先,在收集成本影响特征序列的基础上,构建多因素GM(1,N)模型进行民机研发成本预测;其次,采用MLP神经网络算法对预测成本进行优化修正;充分利用数据量少的灰色GM(1,N)模型,有效利用MLP神经网络的仿真优势。最后,以国内外多架民机为例对组合预测模型进行了验证,结果表明,组合预测方法具有满意且稳定的预测精度,可有效地用于民机研制成本估算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development cost estimation of civil aircraft based on combination model of GM (1, N) and MLP neural network
Scientific prediction and estimation for the development cost of civil aircraft, not only conducive to strengthening the control of cost, is also the key to ensure the success of the project. Considering the complex influence factors of civil aircraft cost with the scarce sample data, a combination model is adopted. Firstly, constructing a multi factor GM(1,N) model to predict the development cost of civil aircraft based on the collection of cost affecting characteristic sequence. Secondly, MLP neural network algorithm is used to optimize and revise the forecasting cost. Making full use of the grey GM(1,N) model with few data and the effective use of simulation advantages of MLP neural network. Finally, a number of domestic and foreign civil aircrafts as an example to verify the combination model, the results show that the combination forecasting method has satisfactory and stable prediction accuracy, and it can effectively be used to estimate the civil aircraft development cost.
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