DocumentCode
522815
Title
Notice of Retraction
Toward graph´s peak resolution by using DPSO algorithm
Author
Hong Zhou ; Zheng Zhao ; Hongpo Wang ; Yvfeng Li
Author_Institution
Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
Volume
1
fYear
2010
fDate
10-11 May 2010
Firstpage
111
Lastpage
114
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.
In this paper we introduced the Dynamic Particle Swarm Optimization (DPSO) algorithm to resolve graph´s peaks in chromatographic analysis. To accelerate the convergence speed, clustering degree and evolution velocity, inertia weight was adopted. The algorithm was tested on both simulated and real overlapping chromatographic peaks. Results indicate that the presented algorithm has fast convergence speed, high accuracy and reliability, and in some cases better than existing techniques.
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.
In this paper we introduced the Dynamic Particle Swarm Optimization (DPSO) algorithm to resolve graph´s peaks in chromatographic analysis. To accelerate the convergence speed, clustering degree and evolution velocity, inertia weight was adopted. The algorithm was tested on both simulated and real overlapping chromatographic peaks. Results indicate that the presented algorithm has fast convergence speed, high accuracy and reliability, and in some cases better than existing techniques.
Keywords
chromatography; convergence of numerical methods; graph theory; particle swarm optimisation; chromatographic analysis; clustering degree; convergence speed; dynamic particle swarm optimization; evolution velocity; graph peak resolution; inertia weight; Agricultural engineering; Algorithm design and analysis; Clustering algorithms; Computer science; Heuristic algorithms; Iterative algorithms; Particle swarm optimization; Photonics; Power engineering and energy; Testing; Graph´s peak; chromatographic analysis; dynamic particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Optics Photonics and Energy Engineering (OPEE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5234-7
Type
conf
DOI
10.1109/OPEE.2010.5508179
Filename
5508179
Link To Document