舰船装备维修费预测的数据预处理技术研究

Data Pre-Processing Techniques for Maintenance Cost Prediction of Ship Equipment

  • 摘要: 在预测舰船装备维修费时,收集足够多的、准确的费用数据是关键。根据舰船装备维修费的影响因素,将舰船装备维修费预测的相关原始数据分为基础数据、使用数据、维修数据和宏观经济数据,确定了相应的数据收集渠道。分析了收集到的原始数据可能存在噪声、缺失或异常数据、冲击扰动数据、不一致数据的问题,针对性地提供了相应的数据预处理技术,经过处理后的数据可以为舰船装备维修费预测提供良好基础,进一步提高预测的有效性。

     

    Abstract: To collect data precisely and adequately is key concern to the maintenance cost prediction of ship equipment.This paper incorporates pre-processing techniques to deal with the cost prediction-related data.As a wide r ange of data will affect the prediction,data are to be categorized into different groups,such as basic data,operational data,maintenance data and macroeconomic data.However,by what means data acquisition can be achieve d efficiently should be confirmed.The original data from different sources will likely to be of noise,default or abnormity and discrepancy.Various pre-processes are needed to handle these data respectively.The pre-proc essed data may provide a good basis for the maintenance cost prediction and improving the efficiency.

     

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