基于粗糙集正域的手写字母识别算法.pdf

118 2014 ，50（23 ） Computer Engineering and Applications 计算机工程与应用 基于粗糙集正域的手写字母识别算法 唐朝辉，陈玉明，吴克寿 TANG Chaohui, CHEN Yuming, WU Keshou 厦门理工学院 计算机科学与技术系，福建 厦门 361024 Department of Computer Science and Technology, Xiamen University of Technology, Xiamen, Fujian 361024, China TANG Chaohui, CHEN Yuming, WU Keshou. Handwritten letter recognition algorithm based on rough set positive region. Computer Engineering and Applications, 2014, 50 （23 ）：118-121. Abstract ：According to the characteristics of handwritten letter recognition, a new handwritten letter recognition algo- rithm is proposed based on the rough set theory. The hypothesis of normal distribution has been tested to ensure the reli- ability of the collected samples. By using upper approximation, lower approximation, as well as positive region of rough set, feature selection is made in order to simplify the decision-making system. Classification rules are then extracted from the simplified decision-making system. Experimental results show that the new algorithm has higher recognition accuracy, and is feasible and effective. Key words ：rough set; positive region; handwriting recognition; feature selection; supervised learning 摘 要：针对手写字母识别的特点，结合粗糙集相关理论，提出了一种新的手写字母识别算法。通过对采集的样本 进行正态分布假设验证，保证样本的可靠性；利用粗糙集上近似、下近似以及正域概念，对手写样本决策系统进行特 征选择以简化决策系统，并进一步提炼手写分类规则。实验结果表明，新算法具有较高的识别准确率，是有效可行的。 关键词：粗糙集；正域；手写识别；特性选择；监督学习 文献标志码：A 中图分类号：TP 181 doi ：10.3778/j.issn. 1002-8331.1212-0221 1 引言 1982 年由波兰数学家Pawlak[4] 首次提出的粗糙集 后PC 时代，大量手持设备、小型网络终端相继面 （rough set ）理论是一种处理模糊和不确定知识的数学 [4-5] 世，键盘编码输入方式越来越不能满足客户的需求，为 工具 ，现已经被广泛应用于数据挖掘、人工智能、模式 [6- 11] 满足用户日益增长的使用体验和易用性需求，采用手写 识别等诸多领域 。粗糙集可用于特征选择，其目的 输入是