基于改进项约束关联规则的船舶涂装工艺知识获取
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江苏杰瑞科技集团有限责任公司

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Knowledge Acquisition of Ship Coating Process based on Improved Item Constraint Association Rules
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JARI

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    摘要:

    为了提高船舶涂装工艺知识获取的效率及有效性,提出一种基于改进项约束关联规则的知识获取方法。首先,根据先导项约束和后继项约束条件筛选目标数据集,用于有针对性地获取涂装工艺知识;然后,利用带约束的关联规则算法挖掘涂装工艺事务数据库中的规则并进行筛选,得到满足项约束条件的关联规则;最后,从获得的规则中提取涂装工艺知识并存入知识库。现场测试结果表明,该方法在缩短算法计算时间的同时提高了算法的性能,所提改进项约束关联规则算法优于传统算法。

    Abstract:

    In order to improve the knowledge acquisition efficiency and effectiveness of ship coating process, a knowledge acquisition method based on improved item constraint association rules is proposed. First, the target data set is filtered according to the antecedent constraint and the consequent constraint to obtain the coating process knowledge in a targeted manner. Then, the constrained association rules algorithm is used to mine the rules in the coating process transaction database and filter them to obtain the association rules that satisfy the constraint conditions. Finally, the coating process knowledge is extracted from the obtained rules and stored in the knowledge base. The field test results show that the proposed method improves the performance of the algorithm while shortening the computation time. The improved item constraint association rules algorithm is superior to the traditional algorithm.

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  • 收稿日期:2020-11-13
  • 最后修改日期:2020-11-19
  • 录用日期:2020-12-10
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