智慧屋的模擬模型與建構，能協助智慧屋的發展，並規劃實體智慧屋的建制。本研究將探討模擬的智慧屋溫度控制器，能依照虛擬居住者的體溫與環境溫度調整最適溫度。本模擬模型架構主要包含虛擬居住者、感應器、模糊認知圖概念的室溫控制模型等三大部份，感應器將傳回虛擬居住者於智慧屋中的位置與體溫，並利用模糊認知圖概念的室溫控制器計算最適溫度。本研究嘗試利用基因演算法求得溫度控制器的模糊認知圖的因果關係矩陣。實驗部份採用不同的虛擬居住者數量與相關設定，作模糊認知圖概念的室溫控制模型準確度比較，並用因子設計方式探討影響室溫控制模型的因子。

The purpose of this research is to develop a temperature prediction model that simplifies complex temperature control in the smart house. The contemporary research of temperature prediction and control needs many decision variables and physical parameters. In this study, we develop a temperature prediction and control model based on fuzzy cognitive map (FCM) without less physical parameters requirement. In addition, this study constructs a genetic algorithm for finding the connection matrix of FCM. The proposed model successfully conducts temperature prediction and control. Finally, we have investigated the prediction accuracy of the proposed model against a variety of system parameters, such as different number of inhabitants.

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