کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
392306 664756 2013 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
On the inference and approximation properties of belief rule based systems
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
On the inference and approximation properties of belief rule based systems
چکیده انگلیسی

Belief rule based (BRB) system provides a generic inference framework for approximating complicated nonlinear causal relationships between antecedent inputs and output. It has been successfully applied to a wide range of areas, such as fault diagnosis, system identification and decision analysis. In this paper, we provide analytical and theoretical analyses on the inference and approximation properties of BRB systems. We first investigate the unified multi-model decomposition structure of BRB systems, under which the input space is partitioned into different local regions. Then we analyse the distributed approximation process of BRB systems. These analysis results unveil the underlying inference mechanisms that enable BRB systems to have superior approximation performances. Furthermore, by using the Stone–Weierstrass theorem, we constructively prove that BRB systems can approximate any continuous function on a compact set with arbitrary accuracy. This result provides a theoretical foundation for using and training BRB systems in practical applications. Finally, a numerical simulation study on the well-known benchmark nonlinear system identification problem of Box–Jenkins gas furnace is conducted to illustrate the validity of a BRB system and show its inference and approximation capability.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 234, 10 June 2013, Pages 121–135
نویسندگان
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