Abstract
This paper aims to reveal design strategies of a sounding hybrid rocket to efficiently perform extinction-reignition. On previous studies, we have derived design candidates which each is a solution optimized on a design optimization problem for the sounding hybrid rocket. To extract design strategies from the design candidates, this paper applies an evolutionary mining system to design candidates, considered as a knowledge discovery task. Specifically, we introduce an evolutionary rule-based data mining system for analyzing a set of Pareto optimal solutions. Our system acquires rules indicating local design information and also we intuitively discover anomalous design strategies.
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