摘要
目前研究的舰船维修费用预测模型预测准确率较低,导致成本开销过大。为了解决上述问题,研究了基于云平台的舰船维修费用预测模型。将舰船维修费用的关联性数据利用云平台存储在预测模型中,采用大数据聚类方法对舰船维修费用进行预测,提高舰船维修费用的预测和调节能力,减少舰船维修工程的不必要开销,提升预测舰船维修费用的准确性和舰船维修速度,对舰船维修费用约束指标参量进行分析,提高舰船维修费用的控制能力,优化舰船维修费用预测模型。实验结果表明,云平台的舰船维修费用预测模型能够有效提高预测准确率,减少成本。
At present, the forecast model of ship maintenance cost is low in accuracy, which leads to the excessive cost.In order to solve the above problems, the prediction model of ship maintenance cost based on cloud platform is studied. In order to improve the ability of forecasting and adjusting the cost of ship maintenance, reduce the unnecessary cost of ship maintenance, improve the accuracy of forecasting the cost of ship maintenance and speed of ship maintenance, analyze the constraint parameters of ship maintenance cost, improve the control ability of ship maintenance cost and optimize the forecasting model of ship maintenance cost. The experimental results show that the prediction model of ship maintenance cost based on cloud platform can effectively improve the prediction accuracy and reduce the cost.
作者
程鹏
CHENG Peng(Changzhi Vocational and Technical College,Changzhi 046000,China)
出处
《舰船科学技术》
北大核心
2021年第12期46-48,共3页
Ship Science and Technology
基金
长治职业技术学院课题
关键词
云平台
舰船维修
维修费用
预测模型
cloud platform
ship maintenance
maintenance cost
predictive model
