DocumentCode :
569403
Title :
Wheat Cultivar Classifications Based on Tabu Search and Fuzzy C-means Clustering Algorithm
Author :
Li Lin ; Liu Suhua
Author_Institution :
Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
fYear :
2012
fDate :
17-19 Aug. 2012
Firstpage :
493
Lastpage :
496
Abstract :
Aimed at the characteristic of recognizing wheat seed, a method is proposed based on fuzzy theory. In this paper, Fuzzy C-means Clustering is introduced and remarked firstly. On the basis of systematic analysis of current algorithms, Tabu search is inducted into fuzzy clustering to solve the locality and the sensitivity of the initial condition of Fuzzy C-means Clustering. Then, this paper proposes the fuzzy discern method based on approach degree and the principle of closest. The deficiency of dose-approximation value is proposed. Finally, it provides the design method and the new algorithm. Simulation results show that this method has good performance regarding both the quality of obtained answer and efficiency.
Keywords :
approximation theory; crops; fuzzy set theory; pattern clustering; sensitivity; approach degree; dose-approximation value; fuzzy C-means clustering algorithm; fuzzy discern method; fuzzy theory; initial condition locality; initial condition sensitivity; tabu search; wheat cultivar classifications; wheat seed recognition; Algorithm design and analysis; Character recognition; Clustering algorithms; Genetic algorithms; Optimization; Search problems; Approach degree; Fuzzy C-means Clustering; Fuzzy Pattern Recognition; Tabu Search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
Type :
conf
DOI :
10.1109/ICCIS.2012.365
Filename :
6300551
Link To Document :
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