首页|Studies from Tianjin University Provide New Data on Machine Learning (Efficient Productivity-Aware Control Parameter Optimization in Cutter Suction Dredger Cons truction Using Machine Learning with Parallel Global Search)
Studies from Tianjin University Provide New Data on Machine Learning (Efficient Productivity-Aware Control Parameter Optimization in Cutter Suction Dredger Cons truction Using Machine Learning with Parallel Global Search)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news originating from Tianjin, People’s Re public of China, by NewsRx correspondents, research stated, “This paper proposes an efficient productivity-aware optimization framework that utilizes hybrid mac hine learning with parallel global search to timely and appropriately adjust the critical control parameters (CCPs) of a cutter suction dredger (CSD) during con struction.”
Tianjin UniversityTianjinPeople’s Re public of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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