南京大学学报(自然科学版) ›› 2014, Vol. 50 ›› Issue (2): 159.
丁卫平1, 2, 3*, 王建东2, 陈森博1, 2, 程学云1, 沈学华1
Ding Weiping1,2,3, Wang Jiandong2, Chen Senbo1,2, Cheng Xueyun1, Sen Xuehua1
摘要: 结合粗糙集属性约简二进制优化模型,提出一种基于改进混合蛙跳算法的粗糙属性交叉熵优化约简算法, 该算法将粗糙集属性划分至不同蛙群进化模因组内,每个模因组内属性集设计成以精英个体为中心力的蛙群并行演化方式,并采用交叉熵最小原理进行精英个体寻优全局最优约简集,快速而有效地处理大规模信息系统的属性约简。UCI仿真实验结果表明本文提出的算法在搜索全局最小属性约简解效率和精度方面具有明显优势,该算法应用于含噪音的人脑核磁共振图像MRI分割实验,其对MRI图像分割的高效性进一步表明该算法具有较强的适用性。
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