A hybrid genetic algorithm and bacterial foraging approach for global optimization
DH Kim, A Abraham, JH Cho - Information Sciences, 2007 - Elsevier
The social foraging behavior of Escherichia coli bacteria has been used to solve
optimization problems. This paper proposes a hybrid approach involving genetic algorithms …
optimization problems. This paper proposes a hybrid approach involving genetic algorithms …
Fuzzy functions with support vector machines
A new fuzzy system modeling (FSM) approach that identifies the fuzzy functions using
support vector machines (SVM) is proposed. This new approach is structurally different from …
support vector machines (SVM) is proposed. This new approach is structurally different from …
A proposed method for learning rule weights in fuzzy rule-based classification systems
In fuzzy rule-based classification systems (FRBCSs), rule weighting has often been used as
a simple mechanism to tune the classifier. In past research, a number of heuristic rule weight …
a simple mechanism to tune the classifier. In past research, a number of heuristic rule weight …
Weighting fuzzy classification rules using receiver operating characteristics (ROC) analysis
In fuzzy rule-based classification systems, rule weight has often been used to improve the
classification accuracy. In past research, a number of heuristic methods for rule weight …
classification accuracy. In past research, a number of heuristic methods for rule weight …
[BOG][B] Computational intelligence paradigms for optimization problems using MATLAB®/SIMULINK®
S Sumathi, LA Kumar - 2018 - books.google.com
Considered one of the most innovative research directions, computational intelligence (CI)
embraces techniques that use global search optimization, machine learning, approximate …
embraces techniques that use global search optimization, machine learning, approximate …
A hierarchical approach to multi-class fuzzy classifiers
In this paper we present a hierarchical approach for generating fuzzy rules directly from data
in a simple and effective way. The fuzzy classifier results from the union of fuzzy systems …
in a simple and effective way. The fuzzy classifier results from the union of fuzzy systems …
A hybrid coevolutionary algorithm for designing fuzzy classifiers
M Li, Z Wang - Information Sciences, 2009 - Elsevier
Rule learning is one of the most common tasks in knowledge discovery. In this paper, we
investigate the induction of fuzzy classification rules for data mining purposes, and propose …
investigate the induction of fuzzy classification rules for data mining purposes, and propose …
Feature selection for specific antibody deficiency syndrome by neural network with weighted fuzzy membership functions
JS Lim, TW Ryu, HJ Kim, S Gupta - … 2005, Changsha, China, August 27-29 …, 2005 - Springer
Fuzzy neural networks have been successfully applied to analyze/generate predictive rules
for medical or diagnostic data. This paper presents selected membership functions extracted …
for medical or diagnostic data. This paper presents selected membership functions extracted …
Finding fuzzy rules for iris by neural network with weighted fuzzy membership function
JS Lim - International Journal of Fuzzy Logic and Intelligent …, 2004 - koreascience.kr
Fuzzy neural networks have been successfully applied to analyze/generate predictive rules
for medical or diagnostic data. However, most approaches proposed so far have not …
for medical or diagnostic data. However, most approaches proposed so far have not …
A hybrid genetic algorithm and bacterial foraging approach for global optimization and robust tuning of PID controller with disturbance rejection
DH Kim, A Abraham - Hybrid evolutionary algorithms, 2007 - Springer
The social foraging behavior of Escherichia coli (E. Coli) bacteria has been used to solve
optimization problems. This chapter proposes a hybrid approach involving genetic algorithm …
optimization problems. This chapter proposes a hybrid approach involving genetic algorithm …