著者

間普 真吾 平澤 宏太郎 古月 敬之

出版者

一般社団法人 電気学会

雑誌

電気学会論文誌C(電子・情報・システム部門誌) (ISSN:03854221)

巻号頁・発行日

vol.127, no.7, pp.1061-1067, 2007-07-01 (Released:2007-09-01)

参考文献数

15

被引用文献数

8 7

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Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

著者

嶋田 香 平澤 宏太郎 古月 敬之

出版者

日本知能情報ファジィ学会

雑誌

知能と情報 : 日本知能情報ファジィ学会誌 : journal of Japan Society for Fuzzy Theory and Intelligent Informatics (ISSN:13477986)

巻号頁・発行日

vol.18, no.6, pp.881-891, 2006-12-15

被引用文献数

1 5

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遺伝的ネットワークプログラミング(GNP)を用いた興味深い相関ルールの抽出手法を提案する.GNPは,ノードをネットワーク状に接続することによって,プログラムの自動生成を行う進化論的計算手法の1つである.GNPの1つの判定ノードが1つの属性に関する判定を行うとき,処理ノードからの判定ノードの連結を相関ルールと対応させることができる.GNPはノードの再利用・共有が可能であるため探索空間を有効に構成できる.また,ルールの興味深さの指標としてサポート値,x^2値をGNPの特性を利用することで算出している.各世代のGNP個体が抽出した興味深い相関ルールはライブラリーに蓄積され,GNPは新規のルール抽出を目的として進化する.シミュレーションの結果から,提案手法が興味深い相関ルールを効率よく抽出することを示す.

著者

嶋田 香 間普 真吾 森川 英治 平澤 宏太郎 古月 敬之

出版者

The Institute of Electrical Engineers of Japan

雑誌

電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society (ISSN:03854221)

巻号頁・発行日

vol.128, no.5, pp.795-803, 2008-05-01

被引用文献数

2 1

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A method of class association rule mining from incomplete databases is proposed using Genetic Network Programming (GNP). GNP is one of the evolutionary optimization techniques, which uses the directed graph structure. An incomplete database includes missing data in some tuples, however, the proposed method can extract important rules using these tuples, and users can define the conditions of important rules flexibly. Generally, it is not easy for Aprior-like methods to extract important rules from incomplete database, so we have estimated the performances of the rule extraction and classification of the proposed method using incomplete data set. The results showed that the accuracy of classification of the proposed method is favorable even if some tuples include missing data.