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Fuzzy-Based Knowledge Discovery from Heterogeneous Data in Planting Systems for Elderly LOHAS
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作者 Hung-Chih Hsueh Jung-Yi Jiang +3 位作者 Jen-Sheng Tsai Wen-Hao Tsai Kuan-Rong Lee yau-hwang kuo 《Journal of Electronic Science and Technology》 CSCD 2015年第1期45-53,共9页
In this paper, we propose a knowledge discovery method based on the fuzzy set theory to help elders with plant cultivation. Initially, the fuzzy sets are constructed by using the feature selection and statistical inte... In this paper, we propose a knowledge discovery method based on the fuzzy set theory to help elders with plant cultivation. Initially, the fuzzy sets are constructed by using the feature selection and statistical interval estimation. The min-max inference and the center of gravity defuzzification method are then used to output a candidate pattern set. Finally, a pattern discovery is adopted to obtain the patterns from the candidate set for the cultivation suggestions by considering the frequency weight and user's experience. In order to demonstrate the performance of our method in planting systems, we conduct a clicks-and-mortar cultivation platform, namely Eden Garden, for the elderly lifestyles of health and sustainability(LOHAS). The experimental results show that the accuracy rate of our knowledge discovery method can reach up to 85%. Moreover, the results of the LOHAS index scale table present that the happiness of the elders is increasing while the elders are using our proposed method. 展开更多
关键词 Elderly LOHAS fuzzy set heterogeneous datalifestyles of health and sustainability
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