网络安全下基于改进遗传算法的流数据挖掘方法研究
Research on data mining based on improved genetic algorithm in network security
李茂民1
作者信息
- 1. 广东松山职业技术学院,广东韶关 512100
- 折叠
摘要
[目的/意义]通过改进双链量子遗传算法对流数据进行有效挖掘,解决传统方法中存在的局限性,促使改进后的算法能够更好地适应流数据的特性,并提升数据处理的速度和精度,以此推动流数据挖掘技术的发展.[方法/过程]对现有的双链量子遗传算法进行深入分析,识别出在流数据挖掘应用中的不足之处,并提出一系列改进措施,将其改进整合到算法框架中,形成新的改进双链量子遗传算法.通过构建模拟环境和实际数据集,对改进双链量子遗传算法进行详细的性能评估和测试.[结果/结论]与传统方法相比,改进双链量子遗传算法在处理速度、准确率和稳定性等方面均有明显优势.特别是在高维数据和大规模数据集的处理上,改进后的新算法展现出更好的扩展性和适应性.此外,新算法的自适应性,使其能够根据数据流的变化自动调整策略,进一步提高流数据挖掘效率,为网络安全提供重要技术支持.
Abstract
[Purpose/Significance]By improving the double stranded quantum genetic algorithm for effective mining of streaming data,the limitations of traditional methods are solved,and the improved algorithm can better adapt to the characteristics of streaming data and improve the speed and accuracy of data processing,thereby promoting the development of streaming data mining technology.[Method/Process]An in-depth analysis was conducted on the existing double stranded quantum genetic algorithm,identifying its shortcomings in stream data mining applications,and proposing a series of improvement measures.These improvements were integrated into the algorithm framework to form a new improved double stranded quantum genetic algorithm.A detailed performance evaluation and testing of the improved double stranded quantum genetic algorithm were conducted by constructing simulated environments and actual datasets.[Results/Conclusion]Compared with traditional methods,the improved double stranded quantum genetic algorithm has significant advantages in processing speed,accuracy,and stability.Especially in the processing of high-dimensional data and large-scale datasets,the improved new algorithm demonstrates better scalability and adaptability.In addition,the adaptability of the new algorithm enables it to automatically adjust strategies based on changes in data flow,further improving the efficiency of stream data mining and providing important technical support for network security.
关键词
双链量子遗传算法/流数据/挖掘方法/数据安全治理/网络安全Key words
double stranded quantum genetic algorithm/stream data/excavation methods/data security governance/network security引用本文复制引用
基金项目
韶关市科研计划项目(230327108037119)
出版年
2024
NETL
NSTL
万方数据