Optimization on Black Box Function Optimization Problem
Joint Authors
Xiao, Jin-ke
Li, Wei-min
Li, Wei
Xiao, Xin-rong
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-29
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
There are a large number of engineering optimization problems in real world, whose input-output relationships are vague and indistinct.
Here, they are called black box function optimization problem (BBFOP).
Then, inspired by the mechanism of neuroendocrine system regulating immune system, BP neural network modified immune optimization algorithm (NN-MIA) is proposed.
NN-MIA consists of two phases: the first phase is training BP neural network with expected precision to confirm input-output relationship and the other phase is immune optimization phase, whose aim is to search global optima.
BP neural network fitting without expected fitting precision could be replaced with polynomial fitting or other fitting methods within expected fitting precision.
Experimental simulation confirms global optimization capability of MIA and the practical application of BBFOP optimization method.
American Psychological Association (APA)
Xiao, Jin-ke& Li, Wei-min& Li, Wei& Xiao, Xin-rong. 2015. Optimization on Black Box Function Optimization Problem. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074382
Modern Language Association (MLA)
Xiao, Jin-ke…[et al.]. Optimization on Black Box Function Optimization Problem. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1074382
American Medical Association (AMA)
Xiao, Jin-ke& Li, Wei-min& Li, Wei& Xiao, Xin-rong. Optimization on Black Box Function Optimization Problem. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074382
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074382