Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer

المؤلفون المشاركون

Guan, Qiu
Ling, Haifeng
Zheng, Yujun

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2012، العدد 2012 (31 ديسمبر/كانون الأول 2012)، ص ص. 1-11، 11ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2012-12-20

دولة النشر

مصر

عدد الصفحات

11

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Particle swarm optimization (PSO) is a stochastic optimization method sensitive to parameter settings.

The paper presents a modification on the comprehensive learning particle swarm optimizer (CLPSO), which is one of the best performing PSO algorithms.

The proposed method introduces a self-adaptive mechanism that dynamically changes the values of key parameters including inertia weight and acceleration coefficient based on evolutionary information of individual particles and the swarm during the search.

Numerical experiments demonstrate that our approach with adaptive parameters can provide comparable improvement in performance of solving global optimization problems.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Zheng, Yujun& Ling, Haifeng& Guan, Qiu. 2012. Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-11.
https://search.emarefa.net/detail/BIM-1029504

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Zheng, Yujun…[et al.]. Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer. Mathematical Problems in Engineering No. 2012 (2012), pp.1-11.
https://search.emarefa.net/detail/BIM-1029504

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Zheng, Yujun& Ling, Haifeng& Guan, Qiu. Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-11.
https://search.emarefa.net/detail/BIM-1029504

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1029504