کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
496624 862866 2011 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A Quantum-inspired Evolutionary Algorithm with a competitive variation operator for Multiple-Fault Diagnosis
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
A Quantum-inspired Evolutionary Algorithm with a competitive variation operator for Multiple-Fault Diagnosis
چکیده انگلیسی

A heuristic search algorithm, the Quantum-inspired Competitive Evolutionary Algorithm (QuCEA), based on both quantum and evolutionary computing, is proposed. The individuals of a population, coded as qubit strings, evolve by means of an original variation operator inspired by competitive learning. The proposed operator is application independent and intuitively controllable by a single real parameter. QuCEA has been applied to Multiple-Fault Diagnosis, a typical NP-hard problem for industrial diagnosis. In particular, the proposed algorithm gives remarkable results both in simulation and in on-field tests for a lift monitoring system, also in comparison with a standard genetic algorithm and a state-of-the-art Quantum-inspired Evolutionary Algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 11, Issue 8, December 2011, Pages 4655–4666
نویسندگان
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