The Proceedings of Design & Systems Conference
Online ISSN : 2424-3078
2013.23
Session ID : 2415
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2415 Application of Grammatical Evolution to Stock Price Prediction
Takao MizunoHideyuki SugiuraShunya MarutaMakoto YamauchiEisuke Kita
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract
Grammatical Evolution (GE), which is one of the evolutionary computations, aims to find function, program or program segment satisfying the design objective. This paper describes the improvement of the Grammatical Evolution according to Stochastic Schemata Exploiter (GE-SSE) and its application to symbolic regression problem Firstly, GESSE is compared with original GE in symbolic regression problem. The results show that GE-SSE has faster convergence property than original GE Secondly, GE-SSE is applied for the stock price prediction as the actual application of the GE-SSE.
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© 2013 The Japan Society of Mechanical Engineers
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