A new approach to generate weighted fuzzy rules using genetic algorithms for estimating null values

Authors:
Shyi-Ming Chen;Chung-Ming Huang
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, 43, Section 4, Keelung Road, Taipei 106, Taiwan, ROC and Department of Computer Sc ...;Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

Citing 6
Cited 6

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
A new method to estimate null values in relational database systems based on automatic clustering techniques

Information Sciences: an International Journal
A new approach for estimating null value in relational database

Soft Computing - A Fusion of Foundations, Methodologies and Applications
Effect of rule weights in fuzzy rule-based classification systems

IEEE Transactions on Fuzzy Systems
Generating weighted fuzzy rules from relational database systems for estimating values using genetic algorithms

IEEE Transactions on Fuzzy Systems
Rule Weight Specification in Fuzzy Rule-Based Classification Systems

IEEE Transactions on Fuzzy Systems

Estimating Null Values in Relational Database Systems Having Negative Dependency Relationships Between Attributes

Cybernetics and Systems
A real-coded genetic algorithm for constructive induction

CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A fuzzy-GA wrapper-based constructive induction model

ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Automatic construction and optimization of knowledge mesh for self-reconfiguration of knowledgeable manufacturing system

Expert Systems with Applications: An International Journal
Extracting linguistic rules from data sets using fuzzy logic and genetic algorithms

Neurocomputing
A robust missing value imputation method for noisy data

Applied Intelligence

Quantified Score

Hi-index	12.05

Visualization

Abstract

In this paper, we present a new method to generate weighted fuzzy rules using genetic algorithms for estimating null values in relational database systems, where there are negative functional dependency relationships between attributes. The proposed method can get higher average estimated accuracy rates than the method presented in [Chen, S. M., & Huang, C. M. (2003). Generating weighted fuzzy rules from relational database systems for estimating null values using genetic algorithms. IEEE Transactions on Fuzzy Systems, 11(4), 495-506].