A Hybrid Belief Rule-Based Classification System Based on Uncertain Training Data and Expert Knowledge

Converting a Rule-based Expert System into a Belief Network

Converting a rule-based expert system into a belief network.

The theory of belief networks offers a relatively new approach for dealing with uncertain information in knowledge-based (expert) systems. In contrast with the heuristic techniques for reasoning with uncertainty employed in many rule-based expert systems, the theory of belief networks is mathematically sound, based on techniques from probability theory. It therefore seems attractive to convert ...

task-based language teaching in iran: a mixed study through constructing and validating a new questionnaire based on theoretical, sociocultural, and educational frameworks

جنبه های گوناگونی از زندگی در ایران را از جمله سبک زندگی، علم و امکانات فنی و تکنولوژیکی می توان کم یا بیش وارداتی در نظر گرفت. زبان انگلیسی و روش تدریس آن نیز از این قاعده مثتسنی نیست. با این حال گاهی سوال پیش می آید که آیا یک روش خاص با زیر ساخت های نظری، فرهنگی اجتماعی و آموزشی جامعه ایرانی سازگاری دارد یا خیر. این تحقیق بر اساس روش های ترکیبی انجام شده است.پرسش نامه ای نیز برای زبان آموزان ...

A Margin-based Model with a Fast Local Searchnewline for Rule Weighting and Reduction in Fuzzynewline Rule-based Classification Systems

Fuzzy Rule-Based Classification Systems (FRBCS) are highly investigated by researchers due to their noise-stability and  interpretability. Unfortunately, generating a rule-base which is sufficiently both accurate and interpretable, is a hard process. Rule weighting is one of the approaches to improve the accuracy of a pre-generated rule-base without modifying the original rules. Most of the pro...

Identification of uncertain nonlinear systems: Constructing belief rule-based models

Article history: Received 27 September 2013 Received in revised form 10 September 2014 Accepted 26 September 2014 Available online 6 October 2014