首页|Central South University Reports Findings in Machine Learning (Enhancing thermal comfort prediction in high-speed trains through machine learning and physiologi cal signals integration)
Central South University Reports Findings in Machine Learning (Enhancing thermal comfort prediction in high-speed trains through machine learning and physiologi cal signals integration)
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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 newsreporting out of Changsha, People’s Rep ublic of China, by NewsRx editors, research stated, “Heating,Ventilation, and A ir Conditioning (HVAC) systems in high-speed trains (HST) are responsible for consuming approximately 70% of non-operational energy sources, yet t hey frequently fail to ensure provideadequate thermal comfort for the majority of passengers. Recent advancements in portable wearable sensorshave opened up n ew possibilities for real-time detection of occupant thermal comfort status and timelyfeedback to the HVAC system.”
ChangshaPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine Learning