Complexity Analysis of Input Rules for Genetic – Fuzzy Data Mining
Sameh Hassanien Basha;
Abstract
The problem of rule generation is of profound importance. Genetic-Fuzzy
methods for rule generation for fuzzy systems have been used, where
genetic algorithms were used for optimizing the number and parameters
of rules.
Traditional methods using Genet
methods for rule generation for fuzzy systems have been used, where
genetic algorithms were used for optimizing the number and parameters
of rules.
Traditional methods using Genet
Other data
| Title | Complexity Analysis of Input Rules for Genetic – Fuzzy Data Mining | Other Titles | تحليل مستوى تعقيد قواعد الادخال للتنقيب عن البيانات باستخدام الطرق الجينية الغائمة | Authors | Sameh Hassanien Basha | Keywords | Complexity Analysis of Input Rules for Genetic – Fuzzy Data Mining | Issue Date | 2011 | Description | The problem of rule generation is of profound importance. Genetic-Fuzzy methods for rule generation for fuzzy systems have been used, where genetic algorithms were used for optimizing the number and parameters of rules. Traditional methods using Genet |
Attached Files
| File | Size | Format | |
|---|---|---|---|
| 111673Sameh Hassanein Basha Master Thesis.pdf | 288.04 kB | Adobe PDF | View/Open |
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