Extracting fuzzy if–then rules by using the information matrix technique
نویسندگان
چکیده
منابع مشابه
Extracting Fuzzy If-then Rule by Using the Information Matrix Technique with Quasi-triangular Fuzzy Numbers
In the paper [7] C. Huang and C. Moraga suggested a new method to extract fuzzy if-then rules from training data based on information matrix technique with Gaussian membership function. In this paper, we extend this method to the Archimedean t-normed space of quasitriangular fuzzy numbers.
متن کاملLearning Robot Behaviours by Extracting Fuzzy Rules from Demonstrated Actions
In this paper we describe a supervised robot learning method which enables a mobile robot to acquire the ability to follow walls and negotiate confined spaces by having these behaviours demonstrated with example actions. We achieve this by demonstrating the desired motion with a remote control while accumulating training data from the robot’s sensors and teacher’s instructions. To speed up lear...
متن کاملExtracting fuzzy sparse rules by Cartesian representation and clustering
Sparse rule base and interpolation have been proposed as possible solution to alleviate the geometric complexity problem of large fuzzy set. So far, however, there's no formal method available to extract sparse rule base. This paper combines the recently introduced Cartesian representation of membership functions and a mountain method-based clustering technique for extraction. A case study is i...
متن کاملSOLVING FUZZY LINEAR SYSTEMS BY USING THE SCHUR COMPLEMENT WHEN COEFFICIENT MATRIX IS AN M-MATRIX
This paper analyzes a linear system of equations when the righthandside is a fuzzy vector and the coefficient matrix is a crisp M-matrix. Thefuzzy linear system (FLS) is converted to the equivalent crisp system withcoefficient matrix of dimension 2n × 2n. However, solving this crisp system isdifficult for large n because of dimensionality problems . It is shown that thisdifficulty may be avoide...
متن کاملInterpreting and extracting fuzzy decision rules from fuzzy information systems and their inference
Information systems, which contain only crisp data, precise and unique attribute values for all objects, have been widely investigated. Due to the fact that in realworld applications imprecise data are abundant, uncertainty is inherent in real information systems. In this paper, information systems are called fuzzy information systems, and formalized by (objects; attributes; f), in which f is a...
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: Journal of Computer and System Sciences
سال: 2005
ISSN: 0022-0000
DOI: 10.1016/j.jcss.2004.05.001