DocumentCode
2681408
Title
Notice of Retraction
Study on generalized fractal algorithm of global optimization
Author
Julong Song ; Xiangjian He ; Fucai Qian
Author_Institution
Sch. of Sci., Xi´an Shiyou Univ., Xi´an, China
Volume
5
fYear
2010
fDate
27-29 March 2010
Firstpage
286
Lastpage
290
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
To promote a fractal algorithm from being suitable for global optimization only on three dimensional spaces to an n dimensional space, this paper presents a simple and convenient method for dividing an n-dimensional hypercube. A key problem is then solved to develop the fractal algorithm in a high dimensional space so that the fractal algorithm becomes a generalized global optimization algorithm. The theoretical foundation of the algorithm is set up. Simulations show the generalized fractal algorithm is effective.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
To promote a fractal algorithm from being suitable for global optimization only on three dimensional spaces to an n dimensional space, this paper presents a simple and convenient method for dividing an n-dimensional hypercube. A key problem is then solved to develop the fractal algorithm in a high dimensional space so that the fractal algorithm becomes a generalized global optimization algorithm. The theoretical foundation of the algorithm is set up. Simulations show the generalized fractal algorithm is effective.
Keywords
fractals; optimisation; generalized fractal algorithm; global optimization algorithm; high dimensional space; n-dimensional hypercube; Artificial neural networks; Australia; Control system synthesis; Fractals; Hypercubes; Optimization methods; Space technology; State-space methods; Steady-state; Technological innovation; Fractal Algorithm; Global optimization; Golden Section Method;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location
Shenyang
Print_ISBN
978-1-4244-5845-5
Type
conf
DOI
10.1109/ICACC.2010.5487247
Filename
5487247
Link To Document