Spare Parts Varieties Level Configuration Based on Grey Situation Decision

被引：0
作者：
Ren Xi [1 ]
Zhao Jian-jun [1 ]
Yang Li-bin [1 ]
机构：
[1] Naval Aeronaut & Astronaut Univ, Yantai 264001, Peoples R China
来源：
26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC) | 2014年
关键词：
Grey situation decision; Varieties of spare parts; Maintenance level;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The main factors that affect the Determine of spare parts varieties are analyzed, the introduction of grey situation decision method to solve the varieties of spare parts in order to determine the maintenance level, a new spare parts varieties quantitative method is provided.
引用
收藏
页码：2241 / 2243
页数：3
相关论文
共 18 条
[1]  
Askari M, 2011, J APPL SCI, V11
[2]  
Cao L.W., 2006, J. China Univ. Min. Technol, V16, P393, DOI [10.1016/S1006-1266(07)60033-9, DOI 10.1016/S1006-1266(07)60033-9]
[3]  
Dai Jun-wei, 2008, GREY MARKOV CHAINS A
[4]  
Das S, 2002, PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOL I, P664, DOI 10.1109/ICIF.2002.1021218
[5]  
Deng J.L., 1988, Grey Prediction and Decision Making
[6]  
Deng JL, 2002, The foundation of grey theory
[7]  
Deng Ju-long, 2004, J GREY SYSTEM, V16
[8]  
Ge Tao, 2001, J SYSTEM SIMULATION, V15, P301
[9]   Energy demand estimation of South Korea using artificial neural network [J].
Geem, Zong Woo ;
Roper, William E. .
ENERGY POLICY, 2009, 37 (10) :4049-4054
[10]   Grey system theory-based models in time series prediction [J].
Kayacan, Erdal ;
Ulutas, Baris ;
Kaynak, Okyay .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (02) :1784-1789
12