论文部分内容阅读
[目的 /意义]基于已有的评价指标体系,建立图书馆成效(绩效)评估的投影寻踪分类(PPC)模型,厘清各个评价指标与图书馆成效(绩效)之间的影响关系及其重要性,对图书馆成效(绩效)高低进行排序,提出提升图书馆成效(绩效)的措施和建议。[方法 /过程]根据抽样得到的图书馆实际调查评价指标数据,编制基于群智能乌鸦搜索算法的PPC模型程序,选取合理的窗宽半径值,建立求得真正全局最优解的图书馆成效(绩效)评价PPC模型、投影向量及其系数和样本投影值。[结果 /结论]PPC模型能够同时完成确定各个评价指标的权重和构建图书馆成效(绩效)评价函数,具有客观性好、结构简单、数学意义清晰和后续应用便捷等特点,评价结果与专家评价法结果基本一致,说明PPC模型能很好地应用于图书馆成效(绩效)评估研究,为图书馆成效(绩效)评估提供新方法。
[PURPOSE / Significance] Based on the existing evaluation index system, a PPC model of library performance (performance) evaluation is established to clarify the relationship between each evaluation index and library performance (performance) and its importance To sort out the effectiveness of the library (performance), put forward measures and suggestions to improve library performance (performance). [Method / Process] According to the actual library survey index data, the PPC model program based on swarm intelligence crow search algorithm is compiled, the reasonable value of the window width radius is selected, and the library effect of finding the true global optimal solution is established Performance) Evaluate PPC models, projection vectors and their coefficients and sample projection values. [Result / Conclusion] The PPC model can determine the weight of each evaluation index and construct the evaluation function of library performance (performance) at the same time. It has the characteristics of good objectivity, simple structure, clear mathematical meaning and convenient application. The evaluation results are in line with the expert evaluation The results are basically the same, indicating that the PPC model can be well applied to the study of library performance (performance) evaluation, providing a new method for library performance (performance) evaluation.