Similarity reasoning-driven evolutionary fuzzy system for monotonic-preserving models
Fuzzy Inference System (FIS) is a popular computing paradigm which has been identified as a solution for various application domains, e.g. control, assessment, decision making, and approximation. However, it suffers from two major shortcomings, i.e., the "curse of dimensionality" and the &...
Saved in:
Main Author: | Jee, Tze Ling |
---|---|
Format: | Thesis |
Language: | English |
Published: |
Universiti Malaysia Sarawak, (UNIMAS)
2013
|
Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/13966/1/Jee.pdf http://ir.unimas.my/id/eprint/13966/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A non-linear programming-based similarity reasoning scheme for modelling of monotonicity-preserving multi-input fuzzy inference systems
by: Kai, Meng Tay, et al.
Published: (2012) -
Building Monotonicity-Preserving Fuzzy Inference Models with Optimization-Based Similarity Reasoning and a Monotonicity Index
by: Kai, M.T, et al.
Published: (2012) -
A New Framework With Similarity Reasoning and
Monotone Fuzzy Rule Relabeling for Fuzzy Inference
Systems
by: Tay, Kai Meng, et al.
Published: (2013) -
An Evolutionary-Based Similarity Reasoning Scheme for Monotonic Multi-Input Fuzzy Inference Systems
by: Kai, M.T, et al.
Published: (2011) -
A new fuzzy criterion-referenced assessment with a fuzzy rule selection technique and a monotonicity-preserving similarity reasoning scheme
by: Jee, T.L, et al.
Published: (2013)