@article{oai:ir.kagoshima-u.ac.jp:00002210,
 author = {福元, 伸也 and FUKUMOTO, Shinya and 宮島, 廣美 and MIYAJIMA, Hiromi and 長澤, 庸二 and NAGASAWA, Yoji},
 journal = {鹿児島大学工学部研究報告, The research reports of the Faculty of Engineering, Kagoshima University},
 month = {Sep},
 note = {Numerous studies have been made on fuzzy systems. In many cases, much effort is required for acquiring optimum inference rules. Therefore, a great number of attempts to reduce the effort have been made on tuning the fuzzy inference rules. When we tune the fuzzy inference rules, we aim
to minimize inference error, the number of rules, and learning speed. We have already proposed a learning method called a destructive method. However, this method contains several problems concerning learning speed and an overlap of constructed rules. So, we suggest a new learning method that uses a correlation coefficient. In order to verify the validity of this hypothesis, numerical experiments are performed.},
 pages = {181--187},
 title = {相関係数を用いる削除型ファジィモデル},
 volume = {37},
 year = {1995}
}