應用多族群基因演算法於居家生活習慣的分類

Application of Multi-Population Genetic Algorithm in Daily Living Habit Classification

何宗憲(Tsung-Hsien Ho)

指導教授 ： 蔡孟伸

國立臺北科技大學/機電學院/自動化科技研究所/碩士(2006年)

https://doi.org/10.6841/NTUT.2006.00137

摘要

由於社會結構漸漸轉變成高齡化的社會，居家照護的議題也越來越受重視，避免在外工作的家人擔心家中的老人或小孩，發展智慧型監控系統來反應家中所需，是個極為迫切的問題。有別以往複雜的監控系統與感測器網路的設計，提出一個簡單的硬體架構與演算法來識別使用者的生活習慣，是本論文主要的目標。本篇論文主要的研究議題就是應用多族群菁英移民遺傳演算法以尋找居家生活習慣的分類規則，藉由這些分類規則可以將新的居家生活習慣分類成重大異常、一般異常及正常的情形。在演算法中利用單一圓規則來分類出重大異常；利用複數圓規則來分類出一般異常及正常。藉由此分類系統來提早發現使用者身理上與心理上的異常行為，避免不必要的問題及疾病的發生，並提醒其家人給予適時的關心與幫助，使其健康與生活更具有保障。

關鍵字

居家照護 ； 居家監測 ； 生活習慣 ； 基因演算法 ； 分類規則

並列摘要

The social structure is migrated to aged society gradually. The health care issue becomes more and more respected. To avoid family members working in the other places worry about elder people and children at home, developing an intelligent monitoring system to response the status in house is an urgent task. This thesis proposed a simple hardware, environment, and algorithm to identify user’s daily living habit. This approach is different from others which require complex monitoring system and sensor network.
The main study issue in this thesis is utilizing multi-population elitism migration genetic algorithm (MEGA) to identify rules for classifying daily living habit. The habit can be classified into normal and abnormal ones according to these rules. The approach uses MEGA to identify single-circle and multi-circle rules by the experience collected in the past. By applying the proposed system, abnormal physical and mental activities can be identified early.

並列關鍵字

Health care ； Monitoring ； Daily living habit ； Genetic alogrithm ； Classified rule

參考文獻

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