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趙梓吟
智慧建築+
智慧建築+
智慧建築+
By
趙梓吟
國立交通大學研究助理
・
Hsinchu City, Taiwan 300
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[負責項目] 資料清理、機器學習演算法之設計與實踐、案場程式部署 [合作公司] 台積電 [專案目標] 大型辦公室因受動態且複雜因素影響(如:日照、人流等),通常難以透過簡單中央空調設定就維持於恆定的溫度。我們旨在透過機器學習模型動態調整中央空調之設定,使大型辦公室內溫度準確維持於使用者設定之溫度,以利台積電環控的舒適度控制策略執行。 [專案績效] 1. 本系統僅需三日(720筆資料)即可佈署,並可於控制時動態學習達到效能提升。 2. 節省約10%空調箱用電量,60%訓練人力。 3. 控制誤差約為+-攝氏0.25度。 [專案進度] 完成,建置於台積電台中15A廠、新竹12P7廠辦公區。目前正規劃擴大安裝。 [論文發表] 此專案之簡化版本論文於2019年被IEEE SMC研討會接受為口頭發表論文[1]。 [獲頒專利] TW Patent I746087 [榮獲獎項] 2018年第11屆內政部「創意狂想,巢向未來」智慧化居住空間創意競賽巢向未來組(案場實作組)銀獎 [1] T. -Y. Chao, M. -H. Nguyen, C. -C. Huang, C. -C. Liang and C. -W. Chung, "Online Self-learning for Smart HVAC Control," 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019, pp. 4324-4330, doi: 10.1109/SMC.2019.8914027.
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趙梓吟
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Published: Jan 3rd 2020
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強化學習
空調控制
智慧大樓
機器學習
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