基于LSTM模型的船舶材料成本滚动预测
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Rolling Forecasting of Ship Material Cost Based on LSTM Model
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    摘要:

    船舶建造周期长、材料成本占比大,易受大宗商品价格指数和汇率等多个因素的影响,造成实际完工成本与报价估算存在较大误差的情况。采用灰色关联分析(Grey Correlation Analysis,GCA)方法识别材料成本的影响因素,基于长短期记忆网络(Long Short-Term Memory,LSTM)模型构建船舶材料成本滚动预测模型,并使用某造船企业53艘64 000 t散货船63个月的材料成本数据和对应的影响因素数据进行试验分析。结果表明,预测数据与实际数据误差在可接受范围内,可证明所选择方法和构建模型的有效性。研究结果对船舶建造过程的成本实时预测和控制具有现实意义。

    Abstract:

    The ship construction period is long, the material cost proportion is large, and it is easily influenced by many factors such as commodity price index and exchange rate, resulting in a large error between the actual completion cost and the quotation estimation. The influencing factors of material cost are identified with Grey Correlation Analysis (GCA) method, a rolling forecasting model of ship material cost is constructed based on Long Short-Term Memory (LSTM) model. The test analysis is conducted with the material cost data of 53 64 000 t bulk carriers in 63 months from a shipbuilding enterprise and the corresponding influencing factors. The results show that the error between the forecasting data and the actual data is within the acceptable range, which can prove the validity of the selected method and the constructed model. The research results are of practical significance for the real-time cost forecasting and control of ship construction process.

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潘燕华,李公卿,王平.基于LSTM模型的船舶材料成本滚动预测[J].造船技术,2024,(03):71-77

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  • 在线发布日期: 2024-06-25
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