期刊文献+

基于信息聚合的电力企业供应链大数据研究 被引量:3

A Big Data Study on Power Company Supply Chain Based on Information Fusion
下载PDF
导出
摘要 大数据时代为供应链带来了新的机会和挑战,供应链的经营与管理必须紧密对接大数据时代发展的特征。指出信息聚合符合了供应链运营中的信息萃取、整合与优化利用等要求,通过信息聚合,能够及时、有效地获取与分析具有价值的数据,提高供应链经营管理的效率与效益,降低经营成本和风险。然后以电力企业供应链大数据为实例,阐明了利用信息聚合方法进行大数据分析的过程,从而证明了信息聚合方法的有效性和实用性。 With the advent of the big data era come new opportunities and challenges which require the operation and management of the supply chains to adapt to the characteristics of the era. In this paper, we pointed out that information fusion fitted the requirement on the extraction, integration and optimized utilization of information in supply chain operation and that, through information fusion, we could obtain and analyze valuable data in a timely and effective manner, enhance the efficiency and benefit of supply chain operation and management, and reduce the operational cost and risks. Next, based on the empirical big data of an electric power company supply chain, we demonstrated the process of information fusion in the big data analysis, thus proving the validity and practicality of the method.
出处 《物流技术》 2016年第7期135-138,180,共5页 Logistics Technology
关键词 大数据 供应链 信息聚合 电力企业 big data supply chain information fusion electric power company
  • 相关文献

参考文献7

二级参考文献24

  • 1HALL R. Towards a fusion of formal and informal learning envi- ronments: the impact of the read/write web [ J ]. Electronic Journal of e-Learning, 2009, 7 ( 1 ) : 29-40. 被引量:1
  • 2REZAPOUR S, FARAHANI R Z. Strategic design of competing centralized supply chain networks for markets with deterministic demands [J]. Advances in Engineering Software, 2010, 41 (5) : 810-822. 被引量:1
  • 3WEBER R H. Intemet of things-new security and privacy chal- lenges [J]. Computer Law & Security Review, 2010, 26 ( 1 ) : 23-30. 被引量:1
  • 4LIN Jun, NG Tsan Sheng. Robust multi-market newsvendor models with interval demand data [ J ]. European Journal of Operational Research, 2011, 212 (2): 361-373. 被引量:1
  • 5BERNARD R. Robustness in operational research and decision aiding: a multi-faeeted issue [J]. European Journal of Opera- tional Research, 2010, 200 (3): 629-638. 被引量:1
  • 6LAU H C W, HO G T S, ZHAO Y, CHUNG N S H. Development of a process mining system for supporting knowledge discovery in a supply chain network [ J ]. Interna- tional Journal of Production Economics, 2009, 122 (1): 176-187. 被引量:1
  • 7TSUI E, WANG W M, CHEUNG C F, et al. A concept-rela- tionship acquisition and inference approach for hierarchical tax- onomy construction from tags [ J ]. Information Processing & Management, 2010, 46 (1): 44-57. 被引量:1
  • 8PISHVAEE M S, RABBANI M, TORABI S A. A robust opti- mization approach to closed-loop supply chain network design under uncertainty [ J ]. Applied Mathematical Modelling, 2011, 35 (2): 637-649. 被引量:1
  • 9LinkinPark.大数据分析与处理方法介绍[EB/OL]http://www36com/archives/3512,1998,2013—09—23. 被引量:2
  • 10赵方婷.大数据:开辟供应链管控新蓝海[N].现代物流报.2015-6-18. 被引量:1

共引文献46

同被引文献54

引证文献3

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部