首页|Findings from University of Adelaide Provide New Insights into Machine Learning (Developing an Experiment-based Strong Machine Learning Model for Performance Pr ediction and Full Analysis of Maisotsenko Dewpoint Evaporative Air Cooler)
Findings from University of Adelaide Provide New Insights into Machine Learning (Developing an Experiment-based Strong Machine Learning Model for Performance Pr ediction and Full Analysis of Maisotsenko Dewpoint Evaporative Air Cooler)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting out of Adelaide, Australia, by NewsRx editors, research stated, “Among all direct and indirectwater-based evaporative air coolers, Maisotsenko indirect evaporative cooler (MIEC) is the o nly one whichcan supply sub wet-bulb air temperature while adding no moisture t o the product air. For any given MIEC,four thermal/fluid parameters including d ry channel flow rate, wet-to-dry-side air flow ratio, ambient airtemperature an d ambient relative humidity impact the performance of the MIEC.”
AdelaideAustraliaAustralia and New Z ealandCyborgsEmerging TechnologiesMachine LearningUniversity of Adelaide
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