摘要
针对传统DNALA算法运行效率低、最终数据挖掘结果精度不理想等问题,提出了一种基于谱聚类矩阵的改进DNALA(DNALA-I)算法,提高了时间效率以及结果精度。该算法通过频谱聚类方法中的计算距离矩阵方法对传统DNALA算法中通过多序列比计算距离矩阵的方法进行改进,在不降低数据挖掘精度的前提下能够有效减少对齐序列所花费的时间,提高算法的运行效率。仿真实验结果表明:本文算法相较传统的DNALA算法不仅提高了时间效率,并且保证了实验结果的计算精度。
Traditional DNALA algorithm has the shortcomings of low efficiency in terms of running time and unsatisfactory accuracy of the data mining results.To overcome these shortcomings,an improved DNALA algorithm is proposed based spectral clustering matrix,called DNALA-I,which can improve the time efficiency and accuracy of the results.The calculation of the distance matrix by multi sequence ratios in the traditional DNALA algorithm is improved by calculation of the spectral clustering distance matrix in the DNALA-I algorithm.Experiment results show that,compared with the traditional DNALA algorithm,the proposed DNALA-I algorithm can effectively reduce the time for sequence alignment meanwhile remain the data mining accuracy.
作者
邓剑勋
熊忠阳
邓欣
DENG Jian- xun;XIONG Zhong- yang;DENG Xin(College of Computer Science, Chongqing University, Chongqing 400044, China;School of Software, Chongqing College of Electronic Engineering, Chongqing 401331, China;School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2018年第3期903-908,共6页
Journal of Jilin University:Engineering and Technology Edition
基金
重庆市教委2015年度科学技术研究项目(kj1503004)
国家自然科学基金项目(61403054)
