研究人员使用人工智能识别了八个州冬季停电风险较高的电力家庭. Researchers used AI to identify electric homes at high risk of winter outages across eight states.

史蒂文斯理工学院的研究人员使用人工智能在没有实体检查的情况下, 识别了8个州的易受伤害的电力和太阳能房屋. Researchers from Stevens Institute of Technology used AI to identify vulnerable electric and solar homes across eight states without physical inspections. 他们的研究在《智能城市和社会杂志》上发表,发现完全电动的住宅比使用混合能源的家庭更可能遭受冬季断电。 Their study, published in the Journal of Smart Cities and Society, found fully electric homes are nearly three times more likely to suffer winter outages than those using mixed energy sources. 机器学习模式可以精确地确定有风险的家庭,精确度超过95%,在恶劣天气期间帮助公用事业和应急人员确定援助对象。 The machine-learning models can pinpoint at-risk homes with over 95% accuracy, aiding utilities and emergency responders in targeting assistance during severe weather.