近年來人們逐漸重視居家生活品質，智慧家庭這個名詞已被討論得相當頻繁，使得許多商業研究紛紛投入於此，而智慧型家電控制這塊領域也是最近最熱門的研究之一。由於人無時無刻都會感受到溫度，因此空調控制就顯得相當重要。
對於使用者而言，在不同季節、不同時間啟動空調時，想要的溫度都不同。然而每次啟動空調時，都必須要手動輸入溫度，實在過於繁瑣；甚至有時候使用者並不知道什麼樣的溫度對他們是舒適的。為了改善此問題，本論文提出一個以自我學習方式對溫控設施設定舒適溫度的方法，紀錄使用者平時的習慣後進行分析，自動設定最舒適的溫度。此方法具有持續學習與修正的特性，可以讓溫控設施隨著時間越來越精準的掌握使用者的習慣，在最後的實驗結果中驗證了本方法的效果是符合期待的。

In recent years , people gradually pay attention to the quality of home life,Smart Home have been frequently discussed in the last decade , the universality and using rate of the mobile devices have been increased , which leads many commercial investing in it. The intelligent control of home appliance is one of the most popular tepies in relative fields. Because people will feel the temperature all the time, so the air-conditioning control becomes very important.
For users, in different seasons, different time to start air-conditioned, the desired temperature are different. But when users start air conditioning, they must enter the temperature manually, it is too cumbersome. And sometimes users does not know what the temperature is comfortable for them. In order to improve this problem, this thesis proposed a self-learning method to determine comfortable temperature for temperature control appliance by recording and analysing the value set by user.
The method by learning and correcting again and again, temperature control appliance could recognize the user's habits more and more precisely as the time goes by. The simulation results in the end of this thesis has shown the effect of method is according with our expectation.

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