首页 | 本学科首页   官方微博 | 高级检索  
     

基于改进遗传算法的棉花异性纤维目标特征选择
引用本文:杨文柱,李道亮,魏新华,康玉国,李付堂. 基于改进遗传算法的棉花异性纤维目标特征选择[J]. 农业机械学报, 2010, 41(4): 173-178. DOI: 10.3969/j.issn.1000-1298.2010.04.035
作者姓名:杨文柱  李道亮  魏新华  康玉国  李付堂
作者单位:1. 河北大学数学与计算机学院,保定,071002;中国农业大学信息与电气工程学院,北京,100083
2. 中国农业大学信息与电气工程学院,北京,100083
3. 江苏大学现代农业装备与技术省部共建教育部重点实验室,镇江,212013
4. 北京中棉机械成套设备有限公司,北京,100089
基金项目:国家自然科学基金,十一五国家科技支撑计划资助项目 
摘    要:为提高基于机器视觉的棉花异性纤维在线分类的精度和速度,提出了一种基于改进遗传算法的特征选择方法.采用分段式染色体管理方案实现对多质特征空间局部化管理;利用分段交叉和变异算子避免出现无效染色体,提高搜索效率;通过自适应调整交叉和变异概率实现强搜索能力和快收敛速度的动态平衡.实验结果表明,该方法比基本遗传算法搜索能力更强、收敛速度更快,所得最优特征子集较小,更适用于棉花异性纤维在线分类.

关 键 词:棉花  异性纤维  特征选择  改进遗传算法

for Cotton Foreign Fiber Objects Based on Improved Genetic Algorithm
Yang Wenzhu Li Daoliang Wei Xinhua Kang Yuguo Li Futang. for Cotton Foreign Fiber Objects Based on Improved Genetic Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery, 2010, 41(4): 173-178. DOI: 10.3969/j.issn.1000-1298.2010.04.035
Authors:Yang Wenzhu Li Daoliang Wei Xinhua Kang Yuguo Li Futang
Affiliation:1/a>;2;1.College of Mathematics & Computer Science/a>;Hebei University/a>;Baoding 071002/a>;China 2.College of Information and Electrical Engineering/a>;China Agricultural University/a>;Beijing 100083/a>;China 3.Key Laboratory of Modern Agricultural Equipment and Technology/a>;Ministry of Education & Jiangsu Province/a>;Jiangsu University/a>;Zhenjiang 212013/a>;China 4.China Cotton Machinery & Equipment Co./a>;Ltd./a>;Beijing 100089/a>;China
Abstract:An optimal feature subset selection method based on improved genetic algorithm(IGA) was presented.A novel scheme named segmented chromosome management was adopted in IGA.This scheme encodes the chromosome in binary as a whole while separates it logically into three segments for local management.These three segments are segment C for color feature,segment S for shape feature and segment T for texture feature separately.A segmented crossover operator and a segmented mutation operator are designed to operate o...
Keywords:Cotton  Foreign fiber  Feature selection  Improved genetic algorithm
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《农业机械学报》浏览原始摘要信息
点击此处可从《农业机械学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号