DocumentCode
532855
Title
Notice of Retraction
Evaluation of component factors of maize yield based on PPC model under different film-mulching methods and drip irrigation
Author
Lv Guo-liang ; Wei Yong-xia
Author_Institution
Water & Civil Eng. Coll., Northeast Agric. Univ., Harbin, China
Volume
12
fYear
2010
fDate
22-24 Oct. 2010
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 order to find the factors with prominent contribution to the maize yield, an evaluation model which is based on the combination of projection pursuit classification model (PPC) and real coding based accelerating genetic algorithm (RAGA) was established, took the component factors as the evaluation indexes, and the data observed in the experimental base which located in Dumeng county Heilongjiang province in 2009 was analyzed by means of the model. The results showed that the main factors with prominent contribution to the maize yield were grain number per spike and spikes per hm2 for double line film-mulching treatment and 100-seed weight and spikes per hm2 for film-mulching between furrows treatment.
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 order to find the factors with prominent contribution to the maize yield, an evaluation model which is based on the combination of projection pursuit classification model (PPC) and real coding based accelerating genetic algorithm (RAGA) was established, took the component factors as the evaluation indexes, and the data observed in the experimental base which located in Dumeng county Heilongjiang province in 2009 was analyzed by means of the model. The results showed that the main factors with prominent contribution to the maize yield were grain number per spike and spikes per hm2 for double line film-mulching treatment and 100-seed weight and spikes per hm2 for film-mulching between furrows treatment.
Keywords
crops; genetic algorithms; hydraulic systems; irrigation; Dumeng county; Heilongjiang province; PPC model; component factors; drip irrigation; evaluation indexes; film-mulching treatment; furrows treatment; maize yield; projection pursuit classification; real coding based accelerating genetic algorithm; spike; Computational modeling; Data models; Indexes; Irrigation; Optimization; Soil; PPC; RAGA; drip irrigation; evaluation; film-mulching; maize yield;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5622433
Filename
5622433
Link To Document