基于改进神经网络的挖掘算法设计Design of mining algorithm based on improved neural network
黄文锋
摘要(Abstract)：
针对传统的数据挖掘算法存在结构复杂、耗时长、数据分析过程中易出现错误,数据计算结果难以准确表达结果等缺陷,提出结合神经网络在数据挖掘中的应用方法。由于神经网络拥有对噪声数据承受能力高、错误率低等优点,因此结合神经网络系统对数据挖掘算法进行改进设计可大幅度提高数据准确性,该方法拥有结构简单、表述清晰、精准度高等优势。为基于神经网络的数据挖掘算法的可行性进行了严谨的实验分析,对实验数据进行认真的记录和研究,实验结果表明,基于神经网络的挖掘算法相比传统数据挖掘算法,其精度明显提高,且整个过程耗时较短,由此可证实基于神经网络的数据挖掘算法具有更高的实用性。
关键词(KeyWords)： 数据挖掘;神经网络;粗糙集;数据挖掘算法;数据计算;可行性分析
基金项目(Foundation): 2017年河南省科技厅科技攻关项目(172102210140)~~
作者(Author): 黄文锋
DOI: 10.16652/j.issn.1004-373x.2018.14.035
参考文献(References)：
- [1]王春梅.基于神经网络的数据挖掘算法研究[J].现代电子技术,2017,40(11):111-114.WANG Chunmei.Research on data mining algorithm based on neural network[J].Modern electronics technique,2017,40(11):111-114.
- [2]郑斌.基于改进遗传算法的不完整大数据填充挖掘算法[J].微电子学与计算机,2016,33(2):96-99.ZHENG Bin.Incomplete data filling mining algorithm based on the improved genetic algorithm[J].Microelectronics&computer,2016,33(2):96-99.
- [3]李滨旭,姚姜虹.基于改进QPSO和RBF神经网络的文本分类方法[J].计算机系统应用,2016,25(7):264-267.LI Binxu,YAO Jianghong.Document classification based on improved QPSO and RBF neural networks[J].Computer systems&applications,2016,25(7):264-267.
- [4]张华,王金兰.基于物联网和SOM算法的信息监控系统设计[J].计算机测量与控制,2017,25(4):84-86.ZHANG Hua,WANG Jilan.Design of information monitoring system based on Internet of Things and SOM algorithm[J].Computer measurement&control,2017,25(4):84-86.
- [5]田野,张程,毛昕儒,等.运用PCA改进BP神经网络的用电异常行为检测[J].重庆理工大学学报,2017,31(8):125-133.TIAN Ye,ZHANG Cheng,MAO Xinru,et al.Research on abnormal behavior of power consumption based on BP neural network with PCA[J].Journal of Chongqing Institute of Technology,2017,31(8):125-133.
- [6]陆安江,金力,杨家红,等.基于改进的BP神经网络在车牌识别中的应用研究[J].贵州大学学报(自然科学版),2015,32(6):71-74.LU Anjiang,JIN Li,YANG,Jiahong,et al.Application research based on improved BP neural network algorithm in license plate recognition[J].Journal of Guizhou University(Natural science),2015,32(6):71-74.
- [7]张连滨,葛浙东,鞠明远,等.改进型神经网络在木件打磨机器人中的应用[J].林业机械与木工设备,2017,45(4):19-22.ZHANG Lianbin,GE Zhedong,JU Mingyuan,et al.Application of improved neural network in woodpiece polishing robot[J].Forestry machinery&woodworking equipment,2017,45(4):19-22.
- [8]赵建华.基于SOM神经网络的半监督分类算法[J].西华大学学报(自然科学版),2015,34(1):36-40.ZHAO Jianhua.Semi-supervised classification algorithm based on SOM neural network[J].Journal of Xihua University(Natural science edition),2015,34(1):36-40.
- [9]伍华丽,任心怡.基于模糊约束的数据库特定数据挖掘算法[J].计算机仿真,2016,33(10):240-243.WU Huali,REN Xinyi.Specific data mining algorithm based on fuzzy constraint database[J].Computer simulation,2016,33(10):240-243.
- [10]白丽扬,赵金海,刘占新,等.基于数据挖掘算法的底板破坏深度预测[J].煤炭工程,2017,49(6):92-95.BAI Liyang,ZHAO Jinhai,LIU Zhanxin,et al.Depth prediction of floor damage based on data mining algorithm[J].Coal engineering,2017,49(6):92-95.
- [11]邢开颜,李梅.数据挖掘分类算法在信号分类中的应用[J].软件,2016,37(6):1-6.XING Kaiyan,LI Mei.Application of data mining classification algorithm in classification and recognition of signals[J].Software,2016,37(6):1-6.
- [12]任关友,王昕,李英娜,等.基于粒子群优化神经网络算法的用户防窃电研究[J].软件,2017,38(8):215-219.REN Guanyou,WANG Xin,LI Yingna,et al.Research on user′s anti-stealing power based on particle swarm optimization neural network algorithm[J].Software,2017,38(8):215-219.
- [13]HUCHAO L I,SHAO A,DENGXIN H E,et al.Application of back-propagation neural network in predicting non-systematic error in numerical prediction model[J].Plateau meteorology,2015,42(6):1198-1201.
- [14]THEANDER E,JONSSON R,SJ?STR?M B,et al.Prediction of Sjogren′s syndrome years before diagnosis and identification of patients with early onset and severe disease course by autoantibody profiling[J].Arthritis&rheumatology,2015,67(9):2427-2436.