基于模糊神经网络的高层次创新型科技人才的评价  

Research on the Evaluation of High-level Innovative Scientific Talents based on the Methord of Fuzzy Neural Network

作　　者：陈苏超[1] 薛晔[1] 

机构地区：[1]太原理工大学经济管理学院,太原030024

出　　处：《太原理工大学学报》2014年第3期420-424,共5页Journal of Taiyuan University of Technology

基　　金：国家自然科学青年基金资助项目(41101507);国家自然科学基金资助项目(51378329);山西省软科学研究计划资助项目(2011041050-02);广义虚拟经济研究专项联合资助项目(GX2011-1013(M))

摘　　要：为了提高高层次创新型科技人才的引进与管理的科学性,弥补高层次创新型科技人才评价中的不足,本研究首先根据高层次创新型科技人才的概念及特征设计了三个层次的评价指标,运用模糊层次分析法对三级评价指标进行筛选;其次,针对指标体系中的属性指标,引入模糊数或模糊语言变量将其量化;第三,利用模糊神经网络模型对高层次创新型科技人才进行评价。从山西省"百人计划"人才中选取样本数据,进行实例分析,结果表明:本研究提出的模型评价结果与实际情况一致,验证其可靠性。有望为高层次创新型科技人才的评价和引进提供科学决策的理论依据,从而提高人才引进的效率并降低风险。In order to improve the scientific nature of introduction and management of highlevel innovative scientific talents, this research aimed to make up for the deficiency in the evaluation. Firstly, according to the concept and features of high-level innovative scientific talents, three levels of assessment indexes were designed. Fuzzy AHP was used to screen Tertiary evaluation index. Secondly, for the attribute index of index system, fuzzy number and fuzzy language variables were introducted to make it quantitative. Thirdly, fuzzy neural network model was used to evaluate high-level innovative scientific talents. Finally, the sample data from Shanxi Province ＂hundred talents＂ is selected for the model training and testing as a case analysis. The result shows that the model evaluation result is consistent with the actual situation and the model is reliable. It provides scientific theory basis of decision for the evaluation and introduction of high-level innovative talents of science and technology.

关 键 词：高层次创新型科技人才 评价指标体系 三角模糊数 模糊层次分析法 模糊神经网络 

分 类 号：C969[经济管理—人力资源管理] TP391.75[自动化与计算机技术—计算机应用技术]