基于灰色聚类理论的失业地区差异性评估模型

Assessment Model of Unemployment Regional Difference Based on the Grey Cluster Theory

由于经济发展水平与就业政策的不同,我国不同地区的失业问题存在较大差异,正确地评估各地区失业状况,是我国在经济转轨时期必须认真对待解决的客观现实问题。以我国30个省市自治区为聚类对象,选取各地区不同年度的失业率为聚类指标,定义相应指标的白化权函数,给出失业问题评估的聚类模型,并且编写相应的算法。利用这一模型把30个地区按失业程度分成三类:低、中和高,并且分析原因。结果系统、客观、准确地评价出各地区失业程度,对解决我国失业问题具有一定的参考价值。

Due to the different levels of economic development and employment policies, the unemployment problem is quite different in different regions of China. How to correctly evaluate the unemployment situation in different areas is the objective reality, our country must take se-riously in the times of economic transition. Uses 30 provinces and Autonomous regions as clustering objects. Chooses the unemployment rates from various years as clustering indexes and defines whitening weight functions from corresponding indexes. Provides clustering models of the unemployment assessment and compiles corresponding algorithms. Divids 30 regions into 3 groups by the unemployment rates：low,medium, and high. The conclusion provids a systematic, objective and accurate evaluation of unemployment in various re-gions, it may has some reference value for solving China＇s unemployment problems.