Data mining based on clustering and association rule analysis for knowledge discovery in multiobjective topology optimization
作者：
Highlights：
• A data mining method for topology optimization is proposed.
• The method sequentially applies clustering and association rule analysis.
• A distance measure for pairs of configurations is defined.
• Confidence and lift indexes in multiobjective topology optimizations are defined.
• The method is applied in 3- and 4-objective design problems in 2 and 3 dimensions.
摘要
•A data mining method for topology optimization is proposed.•The method sequentially applies clustering and association rule analysis.•A distance measure for pairs of configurations is defined.•Confidence and lift indexes in multiobjective topology optimizations are defined.•The method is applied in 3- and 4-objective design problems in 2 and 3 dimensions.
论文关键词：Data mining,Optimum design,Clustering,Association analysis,Topology optimization
论文评审过程：Received 11 December 2017, Revised 9 October 2018, Accepted 26 October 2018, Available online 26 October 2018, Version of Record 6 November 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.10.047
