https://scholars.lib.ntu.edu.tw/handle/123456789/60019
標題: | A learning fuzzy decision tree and its application to tactile image | 作者: | Huang, Han-Pang Liang, Chao-Chiun |
公開日期: | 十月-1998 | 起(迄)頁: | - | 來源出版物: | 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems | 摘要: | Decision trees play important roles in many fields such as pattern recognition and classification. It is because they have simple, apparent and fast reasoning process. This paper develops an algorithm to generate a learning fuzzy decision tree. This algorithm firstly collects enough training data for generating a practical decision tree. It then uses fuzzy statistics to calculate fuzzy sets for representing the training data in order to save computing memory and increase generation speed. Finally, this algorithm uses a sub-optimal criterion to learn a decision tree from the resultant fuzzy sets. The algorithm is applied to a general-purpose tactile force sensing system. This system uses fuzzy logic to interpolate the force data. Then, the proposed algorithm is used to generate the desired decision tree from the tactile data. Based on the decision tree, the objects can be on-line recognized precisely. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-0032310140&partnerID=40&md5=5d11694e1a15021a1c87e94343f3fbd6 http://ntur.lib.ntu.edu.tw//handle/246246/2007041910021766 |
其他識別: | N/A | DOI: | 10.1109/IROS.1998.724823 | SDG/關鍵字: | Computational methods; Data acquisition; Decision theory; Fuzzy sets; Learning algorithms; Pattern recognition; Statistical methods; Trees (mathematics); Tactile force sensors; Robot learning |
顯示於: | 機械工程學系 |
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00724823.pdf | 575.57 kB | Adobe PDF | 檢視/開啟 |
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