Fuzzy C-Means Algorithm on Identifying Grade of Expansive Soil
Arm to uncertainty, noise and multimodal of expansive soil in conventional test, fuzzy sets is introduced to clustering. The author chooses liquid limit, plasticity index, clay content, free expansion rate, CBR92 and CBR30 expansion rates as the evaluation indicators of expansive soil. Based on these, clustering of expansive soil samples is conducted using fuzzy C-means algorithm, and its clustering results is compared with the results using SOM ANN. The results show that, fuzzy C-means algorithm could achieve clustering of expansive soil accurately and efficiently.
expansive soil clustering fuzzy C-means algorithm membership
SHI Xiu-song CHENG Zhan-lin
Yangtze River Scientific Research Institute, Key Laboratory of Geotechnical Mechanics and Engineering of The Ministry of Water Resources, Wuhan 430010, China
国际会议
The Third International Conference on Modelling and Simulation(第三届国际建模、计算、仿真、优化及其应用学术会议 ICMS 2010)
无锡
英文
180-183
2010-06-04（万方平台首次上网日期，不代表论文的发表时间）