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Kentaro Murakami

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Open access 2026

GA-Based Binary Sparse Data-Driven Identification and Nonlinear Model Predictive Control of Diesel Engine Air-Path System

Binary-STLSQ-MT successfully identified models using the library that include higher order terms, for which conventional STLSQ tends to suffer from numerical instability or divergence, and achieved a higher coefficient of determination than the conventional approach.

Kentaro Murakami, S. Yahagi, Ansei Yonezawa et al. · 0 citations

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