首页|University of British Columbia Reports Findings in Machine Learning (Application of hybridized ensemble learning and equilibrium optimization in estimating damp ing ratios of municipal solid waste)
University of British Columbia Reports Findings in Machine Learning (Application of hybridized ensemble learning and equilibrium optimization in estimating damp ing ratios of municipal solid waste)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to news reporting out of Kelowna, Canada, by Ne wsRx editors, research stated, “The dynamic analysis of municipalsolid waste (M SW) is essential for optimizing landfills and advancing sustainable development goals.Assessing damping ratio (D), a critical dynamic parameter, under laborato ry conditions is costly andtime-consuming, requiring specialized equipment and expertise.”
KelownaCanadaNorth and Central Ameri caCyborgsEmerging TechnologiesMachine Learning
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