An interpretability improvement for fuzzy rule bases obtained by the iterative rule learning approach
نویسندگان
چکیده
منابع مشابه
Improvement of Rule Generation Methods for Fuzzy Controller
This paper proposes fuzzy modeling using obtained data. Fuzzy system is known as knowledge-based or rule-bases system. The most important part of fuzzy system is rule-base. One of problems of generation of fuzzy rule with training data is inconsistence data. Existence of inconsistence and uncertain states in training data causes high error in modeling. Here, Probability fuzzy system presents to...
متن کاملMOGUL: A methodology to obtain genetic fuzzy rule-based systems under the iterative rule learning approach
The main aim of this paper is to present MOGUL, a Methodology to Obtain Genetic fuzzy rule-based systems Under the iterative rule Learning approach. MOGUL will consist of some design guidelines that allow us to obtain different genetic fuzzy rule-based systems, i.e., evolutionary algorithm-based processes to automatically design fuzzy rulebased systems by learning andror tuning the fuzzy rule b...
متن کاملAdaptability, interpretability and rule weights in fuzzy rule-based systems
This paper discusses interpretability in two main categories of fuzzy systems fuzzy rule-based classifiers and interpolative fuzzy systems. Our goal is to show that the aspect of high level interpretability is more relevant to fuzzy classifiers, whereas fuzzy systems employed in modeling and control benefit more from low-level interpretability. We also discuss the interpretabilityaccuracy trade...
متن کاملHILK++: an interpretability-guided fuzzy modeling methodology for learning readable and comprehensible fuzzy rule-based classifiers
This work presents a methodology for building interpretable fuzzy systems for classification problems. We consider interpretability from two points of view: (1) Readability of the system description and (2) Comprehensibility of the system behavior explanations. The fuzzy modeling methodology named as HILK (Highly Interpretable Linguistic Knowledge) is upgraded. Firstly, a feature selection proc...
متن کاملInterpretability Assessment in Fuzzy Rule Based Systems
Rule based systems are basically knowledge base systems. They imitate the functionalty of human decision making process in machines. The knowledge is stored in the Knowledge Base of the fuzzy rule based systems. The knowledge is expressed, manipulated and processed by using fuzzy logic. Fuzzy logic represents the human knowledge very well because its mathematical framework is very strong to dea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 2015
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2015.09.001