Wheat Cultivar Classifications Based on Tabu Search and Fuzzy C-means Clustering Algorithm
Lin Li, Suhua Liu · 2012
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.