大数据背景下社会系统优化定量研究  

Quantitative Research of Social System Optimization under the Background of Big Data

作　　者：李忱[1] 黄强[1] 

机构地区：[1]太原科技大学中国系统哲学研究中心,山西太原030024

出　　处：《系统科学学报》2016年第4期20-27,共8页Chinese Journal of Systems Science

基　　金：国家自然科学基金项目(11372207)

摘　　要：社会优化的思想自古有之,东西方哲人都对此进行了积极的探索。但是,以往的优化思想多以主观描述为主,缺乏科学性。系统科学、系统哲学的出现为优化问题奠定了科学基础,最小作用量原理的提出为优化问题提供了理论依据,变分法成为解决优化问题时可以使用的数学工具,基于这三个条件,本文给出了社会系统优化问题定量研究的一般方法。大数据时代的到来,标志着人类在量化认识世界的道路上迈出了一大步,过去不可计量、分析、存储和共享的很多东西都被数据化了,这无疑为社会系统的定量研究提供了极大的便利。A thought of social optimization has existed for a long time. Both Eastern and Western philosophers have conducted active exploration. However, previous thought of optimization focused on sub- jective description, which is poor in scientificity. Now, modern scientific and technological revolution has changed this state. Systems science andsystems philosophy liethe scientific foundation for the optimization research. Principle of least action provides a theoretical basis for optimization research. Calculus of varia- tions is used as a mathematical tool for optimization research. Based on these three conditions, this paper developed a general method for the social system optimization with quantitative research. The use of big data makes a large contribution on quantization understanding of the world. The data which could not be measured,analysed, stored and shared in the past has been digitized. This would make quantitative research more convenient in social system.

关 键 词：社会优化 系统哲学 最小作用量原理 定量研究 大数据 

分 类 号：N94-02[自然科学总论—系统科学]