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Offshore facility's fire risk estimation method using machine learning

机译:使用机器学习的海上设施的火灾风险估算方法

摘要

The method for predicting fire risk of offshore facilities using machine learning according to an embodiment of the present invention includes receiving design data of existing offshore facilities, which is design data of previously designed offshore facilities, and data characteristics from the inputted design data of existing offshore facilities. Extracting, generating a fire risk of the previously designed marine facility as a data label, generating the data characteristic and the data label as a data set, the generated data set as a training data set and verification data Separating into three, performing a machine learning analysis through the training sets to obtain a functional equation functionalizing the correlation between the data characteristic and the data label, and determining the fire risk of the offshore facility through the obtained functional equation. Generating a prediction model for prediction, verifying the generated prediction model using the verification data set, and inputting new offshore facility design data into the generated prediction model to determine the fire risk of the new offshore facility And predicting.
机译:根据本发明的实施例的用于预测近海设施的火灾风险的方法包括接收现有的离岸设施的设计数据,该设计数据是先前设计的离岸设施的设计数据,以及来自现有近海的输入设计数据的数据特征设施。提取,生成先前设计的海上设施的火灾风险作为数据标签,生成数据特征和数据标签作为数据集,生成的数据集作为训练数据集和验证数据分成三个,执行机器学习通过训练集进行分析,以获得功能化数据特性与数据标签之间的相关性的功能等式,并通过所获得的功能方程确定海上设施的火灾风险。生成预测的预测模型,使用验证数据集验证生成的预测模型,并将新的海上设施设计数据输入生成的预测模型,以确定新的海上设施和预测的火灾风险。

著录项

  • 公开/公告号KR20210050657A

    专利类型

  • 公开/公告日2021-05-10

    原文格式PDF

  • 申请/专利权人 삼성중공업 주식회사;

    申请/专利号KR1020190134991

  • 发明设计人 이윤한;황윤지;

    申请日2019-10-29

  • 分类号G06F30;G06N20;G06Q50/26;

  • 国家 KR

  • 入库时间 2022-08-24 18:47:24

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