A Danger-Theory-Based Immune Network Optimization Algorithm

المؤلفون المشاركون

Li, Tao
Xiao, Xin
Shi, Yuanquan
Zhang, Ruirui

المصدر

The Scientific World Journal

العدد

المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-13، 13ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2012-02-13

دولة النشر

مصر

عدد الصفحات

13

التخصصات الرئيسية

الطب البشري
تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability.

This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet.

The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones.

By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies’ concentrations through its own danger signals and then triggers immune responses of self-regulation.

So the population diversity can be maintained.

Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population.

Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Zhang, Ruirui& Li, Tao& Xiao, Xin& Shi, Yuanquan. 2012. A Danger-Theory-Based Immune Network Optimization Algorithm. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1033331

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Zhang, Ruirui…[et al.]. A Danger-Theory-Based Immune Network Optimization Algorithm. The Scientific World Journal No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-1033331

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Zhang, Ruirui& Li, Tao& Xiao, Xin& Shi, Yuanquan. A Danger-Theory-Based Immune Network Optimization Algorithm. The Scientific World Journal. 2012. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1033331

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1033331