کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10321207 | 659280 | 2005 | 26 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Rule-based update methods for a hybrid rule base
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
In this paper, we present methods for efficient updates of a hybrid rule base. The hybrid rule base consists of neurules, a type of hybrid rules combining symbolic rules and neural networks. A neurule base, called the target knowledge, is produced by conversion from a symbolic rule base, called its source knowledge. The presented methods concern modifications to the target knowledge, due to insertion of a new rule in or removal of an old rule from its source knowledge. The methods (a) require as little re-conversion as possible and (b) preserve the number of neurules as small as possible. This is achieved by storing information related to the conversion process in a tree, called the splitting tree. Experimental results demonstrate the benefits of using the splitting tree.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Data & Knowledge Engineering - Volume 55, Issue 2, November 2005, Pages 103-128
Journal: Data & Knowledge Engineering - Volume 55, Issue 2, November 2005, Pages 103-128
نویسندگان
Jim Prentzas, Ioannis Hatzilygeroudis,