首页|Yokohama National University Researcher Reports Recent Findings in Computational Intelligence (3D Ship Hull Design Direct Optimization Using Generative Adversar ial Network)
Yokohama National University Researcher Reports Recent Findings in Computational Intelligence (3D Ship Hull Design Direct Optimization Using Generative Adversar ial Network)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in computa tional intelligence. According to news reporting from Kanagawa, Japan, by NewsRx journalists, research stated, “The direct optimization of ship hull designs usi ng deep learning algorithms is increasingly expected, as it proposes optimizatio n directions for designers almost instantaneously, without relying on complex, t ime-consuming, and expensive hydrodynamic simulations.” Funders for this research include Japan Marine United Corporation. The news journalists obtained a quote from the research from Yokohama National U niversity: “In this study, we proposed a GAN-based 3D ship hull design optimizat ion method. We eliminated the dependence on hydrodynamic simulations by training a separate model to predict ship performance indicators. Instead of a standard discriminator, we applied a relativistic average discriminator to obtain better feedback regarding the anomalous designs. We add two new loss functions for the generator: one restricts design variability, and the other sets improvement targ ets using feedback from the performance estimation model.”
Yokohama National UniversityKanagawaJapanAsiaComputational IntelligenceMachine Learning
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