首页|Data on Machine Learning Reported by Researchers at University of Georgia (Accel eration of Superpave Mix Design: Solving Multiobjective Optimization Problems U sing Machine Learning and the Non-dominated Sorting Genetic Algorithm-ii)
Data on Machine Learning Reported by Researchers at University of Georgia (Accel eration of Superpave Mix Design: Solving Multiobjective Optimization Problems U sing Machine Learning and the Non-dominated Sorting Genetic Algorithm-ii)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on Machine Learning have be en published. According to news reporting from Athens, Georgia, by NewsRx journa lists, research stated, "The traditional asphalt mix design requires the prepara tion of many samples to test, which consumes much time and labor. Moreover, sele cting aggregate gradation and asphalt content based on individual experience unt il a mixture's properties meet a specification is a trial-and-error procedure." Financial support for this research came from Center for Integrated Asset Manage ment for Multimodal Transportation Infrastructure Systems (CIAMTIS), a US Depart ment of Transportation University Transportation Center, United States.
AthensGeorgiaUnited StatesNorth an d Central AmericaAlgorithmsCyborgsEmerging TechnologiesGenetic Algorithm sGeneticsMachine LearningUniversity of Georgia
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