کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1181747 962985 2006 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Ensemble classifier system based on ant colony algorithm and its application in chemical pattern classification
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
Ensemble classifier system based on ant colony algorithm and its application in chemical pattern classification
چکیده انگلیسی

A novel ant colony algorithm, mass recruitment and group recruitment based continuous ant colony optimization (MG-CACO), is proposed to solve continuous optimization problems. MG-CACO, which can capture the interdependencies between attributes and does not need discretization as a preprocessing step for optimization, was applied to extract classification rules from samples. To improve the predictive performance of the classifier, the ensemble strategy was adopted and the MG-CACO based ensemble classifier system called MG-CACO-ECS was built. Several datasets, obtained from UCI (University of California, Irvine) machine learning repository, were employed to illustrate the validity of MG-CACO-ECS. The results indicated that MG-CACO-ECS has satisfactory prediction accuracy. Furthermore, the problem of the producing area discrimination of olive oil was studied, and the obtained results demonstrated that MG-CACO-ECS has better prediction accuracy than the reported results.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 80, Issue 1, 20 January 2006, Pages 39–49
نویسندگان
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