Interval-value attribute reduction algorithm for meteorological observation data based on genetic algorithm

doi:10.11772/j.issn.1001-9081.2017.09.2678

Journal of Computer Applications ›› 2017, Vol. 37 ›› Issue (9): 2678-2683.DOI: 10.11772/j.issn.1001-9081.2017.09.2678

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Interval-value attribute reduction algorithm for meteorological observation data based on genetic algorithm

ZHENG Zhongren¹, CHENG Yong², WANG Jun^1,2, ZHONG Shuiming¹, XU Liya³

1. School of Computer & Software, Nanjing University of Information Science and Technology, Nanjing Jiangsu 210044, China;
2. Information Construction and Management Department, Nanjing University of Information Science and Technology, Nanjing Jiangsu 210044, China;
3. School of Information Science and Technology, Jiujiang University, Jiujiang Jiangxi 332005, China

Received:2017-03-17 Revised:2017-04-25 Online:2017-09-10 Published:2017-09-13
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61402236, 61373064), the "Six Talent Peaks Project in Jiangsu Province (2015-DZXX-015), CERNET Innovation Project (NGⅡ20160318).

基于遗传算法的气象观测数据区间值属性约简算法

郑忠仁¹, 程勇², 王军^1,2, 钟水明¹, 徐利亚³

1. 南京信息工程大学计算机与软件学院, 南京 210044;
2. 南京信息工程大学信息化建设与管理处, 南京 210044;
3. 九江学院信息科学与技术学院, 江西九江 332005

通讯作者: 郑忠仁,zrzheng@foxmail.com
作者简介:郑忠仁(1991-),男,江苏淮安人,硕士研究生,主要研究方向:大数据;程勇(1980-),男,重庆人,高级工程师,博士,CCF会员,主要研究方向:无线传感器网络、大数据;王军(1970-),男,安徽铜陵人,教授,博士,CCF会员,主要研究方向:无线传感器网络、大数据;钟水明(1971-),男,江西瑞金人,讲师,博士,CCF会员,主要研究方向:人工神经网络、模式识别、数据挖掘;徐利亚(1984-),男,江西九江人,讲师,博士,主要研究方向:无线传感器网络、大数据。
基金资助:
国家自然科学基金资助项目（61402236， 61373064）；江苏省"六大人才高峰"项目（2015-DZXX-015）；赛尔网络下一代互联网技术创新项目（NGⅡ20160318）。

Abstract

Abstract: Aiming at the problems that the purpose of the meteorological observation data acquisition is weak, the redundancy of data is high, and the number of single values in the observation data interval is large, the precision of equivalence partitioning is low, an attribute reduction algorithm for Meteorological Observation data Interval-value based on Genetic Algorithm (MOIvGA) was proposed. Firstly, by improving the similarity degree of interval value, the proposed algorithm could be suitable for both single value equivalence relation judgment and interval value similarity analysis. Secondly, the convergence of the algorithm was improved by the improved adaptive genetic algorithm. Finally, the simulation experiments show that the number of the iterations of the proposed algorithm is reduced by 22, compared with the method which operated AGAv (Adaptive Genetic Attribute reduction) algorithm to solve the optimal value. In the time interval of 1 hour precipitation classification, the average classification accuracy of the MOIvGA (λ-Reduction in Interval-valued decision table based on Dependence) algorithm is 6.3% higher than that of RIvD algorithm; the accuracy of no rain forecasting is increased by 7.13%; at the same time, the classification accuracy can be significantly impoved by the attribute subset received by operating the MOIvGA algorithm. Therefore, the MOIvGA algorithm can increase the convergence rate and the classification accuracy in the analysis of interval value meteorological observation data.

Key words: meteorological observation data, attribute reduction, interval-value similarity, genetic algorithm, attribute subset

摘要： 针对气象观测数据采集目的性弱、数据冗余度较高以及观测数据区间化中单值较多、等价类划分精度低的问题，提出一种基于遗传算法的气象观测数据区间值属性约简算法（MOIvGA）。首先，通过改进区间值相似度，使其能够同时适用于单值等价关系判断和区间值相似度分析；其次，通过改进自适应遗传算法，提高其收敛性；最后，通过仿真实验证明，相对于运行自适应遗传属性约简（AGAv）算法求解最优值，所提算法迭代代数减少了22代；在区间长度为1 h降水分类中，基于依赖度的区间值决策表λ-约简（MOIvGA）平均分类准确率比RIvD算法提高了6.3%，对无雨的预测准确率提高了7.13%；同时约简后的属性子集显著提高了分类准确率。由此可见，MOIvGA在区间值气象观测数据分析中能够提高收敛速度以及分类准确率。

关键词: 气象观测数据, 属性约简, 区间值相似度, 遗传算法, 属性子集

CLC Number:

TP18
TP301.6

ZHENG Zhongren, CHENG Yong, WANG Jun, ZHONG Shuiming, XU Liya. Interval-value attribute reduction algorithm for meteorological observation data based on genetic algorithm[J]. Journal of Computer Applications, 2017, 37(9): 2678-2683.

郑忠仁, 程勇, 王军, 钟水明, 徐利亚. 基于遗传算法的气象观测数据区间值属性约简算法[J]. 计算机应用, 2017, 37(9): 2678-2683.

References

[1] 白雪.气象领域事件挖掘相关问题的研究[D].上海:复旦大学,2013:1-10.(BAI X. Research on relevant issues of event mining in meteorological field[D]. Shanghai:Fudan University, 2013:1-10.)
[2] 赵方霞.基于气象数据的数据挖掘算法研究[D].北京:北方工业大学,2011:1-14.(ZHAO F X. Research on data mining algorithm based on the meteorological data[D]. Beijing:North China University of Technology, 2011:1-14.)
[3] LI P, WU J, QIAN H. Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China[J]. Environmental Monitoring and Assessment, 2012, 184(8):4841-4854.
[4] CHANG S. A novel attribute reduction method based on rough sets and its application[J]. International Journal of Advancements in Computing Technology, 2012, 4(3):99-104.
[5] 于莹莹,曾雪兰,孙兴星.优势关系下的区间值信息系统及其属性约简[J].计算机工程与应用,2011,47(35):122-124.(YU Y Y, ZENG X L, SUN X X. Interval-valued information system based on dominance relation and its attribute reduction[J]. Computer Engineering and Applications, 2011, 47(35):122-124.)
[6] ZENG A, PAN D, ZHENG Q L, et al. Knowledge acquisition based on rough set theory and principal component analysis[J]. IEEE Intelligent Systems, 2006, 21(2):78-85.
[7] JEON G, KIM D, JEONG J. Rough sets attributes reduction based expert system in interlaced video sequences[J]. IEEE Transactions on Consumer Electronics, 2006, 52(4):1348-1355.
[8] SINHA D, LAPLANTE P. A rough set-based approach to handling spatial uncertainty in binary images[J]. Engineering Applications of Artificial Intelligence, 2004, 17(1):97-110.
[9] KAYA Y, UYAR M. A hybrid decision support system based on rough set and extreme learning machine for diagnosis of hepatitis disease[J]. Applied Soft Computing, 2013, 13(8):3429-3438.
[10] ASHARAF S, MURTY M N. A rough fuzzy approach to web usage categorization[J]. Fuzzy Sets & Systems, 2004, 148(1):119-129.
[11] CHENG C H, CHEN T L, WEI L Y. A hybrid model based on rough sets theory and genetic algorithms for stock price forecasting[J]. Information Sciences, 2010, 180(9):1610-1629.
[12] GRECO S, MATARAZZO B, SLOWINSKI R. Rough sets theory for multicriteria decision analysis[J]. European Journal of Operational Research, 2001, 129(1):1-47.
[13] ZHAO H, MIN F, ZHU W. Test-cost-sensitive attribute reduction based on neighborhood rough set[C]//Proceedings of the 2011 IEEE International Conference on Granular Computing. Piscataway, NJ:IEEE, 2011:802-806.
[14] 杨青山,王国胤,张清华,等.基于优势关系的区间值粗糙集扩充模型[J].山东大学学报(理学版),2010,45(9):7-13.(YANG Q S, WANG G Y, ZHANG Q H, et al. The interval-valued rough set extended model based on the dominance relation[J]. Journal of Shandong University (Natural Science), 2010, 45(9):7-13.)
[15] 徐菲菲,雷景生,毕忠勤,等.大数据环境下多决策表的区间值全局近似约简[J].软件学报,2014,25(9):2119-2135.(XU F F, LEI J S, BI Z Q, et al. Approaches to approximate reduction with interval-valued multi-decision tables in big data[J]. Journal of Software, 2014, 25(9):2119-2135.)
[16] 张楠,苗夺谦,岳晓冬.区间值信息系统的知识约简[J].计算机研究与发展,2010,47(8):1362-1371.(ZHANG N, MIAO D Q, YUE X D. Approaches to knowledge reduction in interval-valued information systems[J]. Journal of Computer Research and Development, 2010, 47(8):1362-1371.)
[17] 陈子春,秦克云.区间值信息系统在变精度相容关系下的属性约简[J].计算机科学,2009,36(3):163-166.(CHEN Z C, QIN K Y. Attribute reduction of interval-valued information system based on variable precision tolerance relation[J]. Computer Science, 2009, 36(3):163-166.)
[18] 贾凡,薛佩军,许嘉.决策区间值信息系统的交互相容关系及属性约简[J].计算机科学,2012,39(s3):245-248.(JIA F, XUE P J, XU J. Interactive tolerance relation in interval-valued decision table and attribute reduction[J]. Computer Science, 2012, 39(s3):245-248.)
[19] 邓刚锋,黄先祥,高钦和,等.基于改进型遗传算法的虚拟人上肢运动链逆运动学求解方法[J].计算机应用,2014,34(1):129-134. (DENG G F, HUANG X X, GAO Q H, et al. Solution method for inverse kinematics of virtual human's upper limb kinematic chain based on improved genetic algorithm[J]. Journal of Computer Applications, 2014, 34(1):129-134.)
[20] 孙越泓,魏建香,夏德深.基于自适应遗传算法的B样条曲线拟合的参数优化[J].计算机应用,2010,30(7):1878-1882.(SUN Y H, WEI J X, XIA D S. Parameter optimization for B-spline curve fitting based on adaptive genetic algorithm[J]. Journal of Computer Applications, 2010, 30(7):1878-1882.)

Interval-value attribute reduction algorithm for meteorological observation data based on genetic algorithm

基于遗传算法的气象观测数据区间值属性约简算法

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