A Missing Data Filling Method for Effectiveness Evaluation System

Abstract

Abstract:

To solve the data missing problem in effectiveness evaluation of weapon systems, a novel method was proposed to fill the missing data. The effectiveness evaluation system was described from the perspective of information entropy while the so called weighted generalized information entropy was found on the intervalvalued information system. Besides, the nonnegativity, monotony and extremality of the new information entropy were discussed. Based on the new theory, and according to the variation of the information entropy before and after data missing of the effectiveness evaluation system, a novel method for filling the missing data based on weighted generalized information entropy was proposed, and the theory of weighted generalized information entropy was explained from the perspective of knowledge granularity. The proposed algorithm performs better in comparison with other algorithms, which verifies that the algorithm is valid in filling missing data of effectiveness evaluation system in consequence.

Key words:

effectiveness evaluation; data missing; data filling; weighted generalized information entropy

CLC Number:

TP 301

WANG Jun1, 2,LI Jianxun1,HAN Shan3,WANG Xing2. A Missing Data Filling Method for Effectiveness Evaluation System[J]. Journal of Shanghai Jiao Tong University, 2017, 51(2): 180-.

References

［1］ZHANG Qingchen, CHEN Zhikui. A weighted kernel possibilistic cmeans algorithm based on cloud computing for clustering big data ［J］. International Journal of Communication Systems, 2014, 27(9): 1378-1391.
［2］CHEN S, HUANG M, TANG S, et al. Capacity of data collection in arbitrary wireless sensor networks ［J］.IEEE Transactions on Parallel and Distributed Systems, 2012, 23(1): 52-60.
［3］胡玄子, 陈小雪, 钱叶亮, 等. 数据处理中缺失数据填充方法的研究［J］. 湖北工业大学学报, 2013, 28(5): 82-84.
HU Xuanzi, CHEN Xiaoxue, QIAN Yeliang, et al. Reseach on the method of filling missing data in data processing［J］. Journal of Hubei University of Technology, 2013, 28(5): 82-84.
［4］朱晓峰. 缺失值填充的若干问题研究［D］. 桂林: 广西师范大学研究生院,2007.
［5］冷泳林, 陈志奎, 张清辰, 等. 不完整大数据的分布式聚类填充算法［J］. 计算机工程, 2015, 41(5): 19-25.
LENG Yonglin, CHEN Zhikui, ZHANG Qingchen, et al. Distributed clustering and filling algorithm of incomplete big data ［J］. Computer Engineering, 2015, 41（5）: 19-25.
［6］陈爽, 宋金玉, 刁兴春, 等. 基于关系马尔可夫模型的枚举型缺失值估计［J］. 上海交通大学学报, 2013, 47(8): 1246-1250.
CHEN Shuang, SONG Jinyu, DIAO Xingchun, et al. Estimation of enumerative missing values based on relational markov model ［J］. Journal of Shanghai Jiao Tong University, 2013, 47(8): 1246-1250.
［7］SHAN Han, LIN Chen, ZHI Zhang, et al. A new information filling technique based on generalized information entropy［J］. International Journal of Computers Communications and Controls, 2014, 9(2): 172-186.
［8］黄国顺, 曾凡智, 文翰. 代数约简的知识粒度表示及其高效算法［J］. 控制与决策, 2014, 29(8): 1354-1362.
HUANG Guoshun, ZENG Fanhi,WEN Han. Knowledge granularity representation and efficient algorithm of algebraic reduction ［J］. Control and Decision, 2014, 29(8): 1354-1362.
［9］张裕. 基于粒计算的决策表知识约简算法研究［D］. 太原：太原理工大学研究生院, 2015.
［10］景运革, 李天瑞. 基于知识粒度的增量约简算法［J］. 山东大学学报（工学版）, 2016, 56(1): 1-9.
JING Yunge, LI Tianrui. An incremental approach for reduction based on knowledge granularity ［J］. Journal of Shandong University(Engineering Science), 2016，56(1): 1-9.
［11］MIAO Duoqian,FAN Shidong. The calculation of knowledge granulation and its application［J］． Systems EngineeringTheory ＆ Practice, 2002, 33(1): 48-56.
［12］朱红. 粒度聚类方法研究［D］. 江苏，徐州: 中国矿业大学研究生院, 2013.
［13］王世强，张登福，毕笃彦，等. 基于模糊粗糙集依赖度的两步属性约简方法［J］. 北京工业大学学报, 2013, 39(6): 828-834.
WANG Shiqiang，ZHANG Dengfu，BI Duyan, et al. Twostep attribute reduction method based on fuzzy rough sets dependency ［J］. Journal of Beijing University of Technology, 2013, 39(6): 828-834.

[1]	JIN Yang,CAI Xiaojuan,LI Guoqiang. Expressiveness of WellStructured Pushdown Systems [J]. Journal of Shanghai Jiaotong University, 2015, 49(08): 1084-1089.
[2]	ZOU Zhiwen，LI Qiao，KOU Aijun. Approximate Top-k Query Algorithm for Spatial Keyword in Sensor Networks [J]. Journal of Shanghai Jiaotong University, 2014, 48(10): 1457-1460.
[3]	FANG Pengya,CHANG Xinlong,HU Kuan,ZHANG Xiaojun. Optimization of Multidisciplinary Reliability Design Based on Interval Uncertainty [J]. Journal of Shanghai Jiaotong University, 2014, 48(10): 1451-1456.
[4]	YUAN Xinpan1,SHENG Xinhai1,LONG Jun2,ZHANG Zuping2,GUI Weihua2. Estimation of Three-Way Similarities Based on Connected Bit Minwise Hash [J]. Journal of Shanghai Jiaotong University, 2014, 48(07): 936-941.
[5]	LIU Tian-Tang, JIANG Zhi-Bin, HU Hong-Tao, LIU Ran. An Enhanced Hybrid Genetic Algorithm for the Capacitated Arc Routing Problem [J]. Journal of Shanghai Jiaotong University, 2013, 47(04): 619-625.
[6]	LI Yuan-1, JIANG Jiang-2, ZHANG Min-Xuan-1, WEI Shao-Jun-3 . Automatic Word-Length Determination Tool Based on Simulated Annealing Algorithm [J]. Journal of Shanghai Jiaotong University, 2013, 47(01): 76-80.
[7]	LIU Tian-Tang, JIANG Zhi-Bin, GENG Na, LIU Ran, LIU Shu-Jun. The Heterogeneous Fixed Fleet Capacitated Arc Routing Problem [J]. Journal of Shanghai Jiaotong University, 2012, 46(11): 1759-1763.
[8]	JIANG Meng-Zhi-1, 2 , ZHAO Feng-Jing-2. Bisimulation Research on C Model Embedded with Computable Function [J]. Journal of Shanghai Jiaotong University, 2012, 46(04): 620-623.
[9]	ZHU Wei-a, XU Ke-Lin-a, ZHOU Bing-Hai-a, XU Jin-Chao-b. Study on Multistage Multiobjective Network Location Problem Based on Greedy Heuristic Algorithm [J]. Journal of Shanghai Jiaotong University, 2012, 46(02): 269-275.
[10]	ZENG Min1,2,3,LUO Yuan1. On the Two Kinds of Depth Distribution over F2 [J]. Journal of Shanghai Jiaotong University, 2008, 42(12): 2060-2064.
[11]	ZHANG Mina^a,QI Zheng-wei^b,DONG Xiao-ju^a. Executable Specification of P Systems with Active Membranes and Its Implementation [J]. Journal of Shanghai Jiaotong University, 2008, 42(10): 1635-1639.
[12]	ZHU Yi, YANG Gen-ke, PAN Chang-chun. Threshold Constraint Based DepthFirstSearch for BranchBound Algorithm Solving Asymmetric Traveling Salesman Problems [J]. Journal of Shanghai Jiaotong University, 2008, 42(10): 1665-1668.
[13]	FANG Pengya,CHANG Xinlong,HU Kuan,ZHANG Youhong. Asymptotic Relaxation Based Collaborative Optimization [J]. Journal of Shanghai Jiaotong University, 2013, 47(12): 1896-1901.
[14]	YANG Fuzhou,WANG Haiyan,SHEN Xiaohong,JING haixia. Super-Directional Element Distribution Model of NLA Based on TR [J]. Journal of Shanghai Jiaotong University, 2013, 47(12): 1907-1910.
[15]	ZHOU Na，MI Weijian，XU Ziqi,SHU Fan. Solution to Multi-Line Layout Problems of Equipment Based on Improved Adaptive Genetic Algorithm [J]. Journal of Shanghai Jiaotong University, 2013, 47(12): 1924-1929.