**⊙ Design Knowledge Mining and Big Data Analysis**

** During the design process using Evolutionary Algorithms, tremendous design data are obtained. From these data, it is possible to extract invaluable knowledge about the design problem. Recently, the process of t is called ‘Data Ming’ or ‘Big Data Analysis’.**

** For example, there are 1024 hull forms which are obtained through the low drag hull form design. (obj1, obj2 and obj3 are wave drag coefficient at Fn = 0.22, 0.27 and 0.305, respectively). Each gray circle in Fig. 1 corresponds to each hull form. **

Figure 1 Design Exploration Results

To analyze these data, we applied ANOVA (Analysis of Variance) and Self-Organizing Map (SOM). The result of ANOVA and SOM are shown in Fig. 2.

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**(a) ANOVA **

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** (b) SOM**

**Figure 2 Data Mining with ANOVA and SOM**

** Based on the information obtained from the data mining, the following design knowledge can be acquired.**

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**(1) A narrower waterline in the bow region (small DV10 and DV11) is a necessary condition for a non-dominated solution.**

**(2) A wider section shape (large DV4, DV7, DV8, and DV12) is preferable for low-speed performance, while a narrower section shape (small DV4, DV7, DV8, and DV12) is necessary for high-speed performance.**

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