| 基于GM(1,1)模型的学科创新力预测 |
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| 引用本文： | 钱玲飞,杨建林.基于GM(1,1)模型的学科创新力预测[J].情报科学,2012(4):530-534. |
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| 作者姓名： | 钱玲飞 杨建林 |
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| 作者单位： | 南京航空航天大学图书馆;南京大学信息管理系 |
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| 基金项目： | 国家社会科学基金项目(09BTQ020) |
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| 摘 要： | 首先以情报学为例,通过关键词综合评价,得出情报学近18年的6组学科创新力值,并分别用GM(1,1)全模型、GM(1,1)部分模型、GM(1,1)新信息模型和GM(1,1)新陈代谢模型对学科创新力的6组值进行模拟,通过分析比较,得出GM(1,1)新陈代谢模型具有较高精度,然后选取该模型对情报学学科创新力进行预测。接着计算图书馆学近12年的4组学科创新力数据,建立图书馆学学科创新力GM(1,1)新陈代谢模型,用该模型对图书馆学创新力进行预测。最后将图书馆学与情报学学科创新力进行比较和分析,得出情报学和图书馆学不同的学科特点和发展趋势。
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| 关 键 词： | 学科创新力 GM(1 1)模型 预测 情报学 图书馆学 |
Disciplinary Creativity Prediction Based on GM(1,1) |
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| QIAN Ling-fei,YANG Jian-lin.Disciplinary Creativity Prediction Based on GM(1,1)[J].Information Science,2012(4):530-534. |
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| Authors: | QIAN Ling-fei YANG Jian-lin |
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| Institution: | 1.Library of Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China; 2.Department of Information Management,Nanjing University,Nanjing 210093,China) |
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| Abstract: | The paper obtains six groups disciplinary creativity values of information science through keywords analysis,builds models with GM(1,1) full model,GM(1,1) partial model,GM(1,1) new information model,and GM(1,1) metabolic model separately,then simulates disciplinary creativity values with those models.Though analysis and comparison,the paper gets conclusion that the GM(1,1) metabolic model is the most accurate and proper one.Then the paper builds models with GM(1,1) metabolic model to simulate and predict the disciplinary creativity values of library science.In the end,the paper compares and analyzes disciplinary creativity of information science and library science,then draws different features and development trends of those two disciplinaries. |
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| Keywords: | disciplinary creativity GM(1 1) prediction information science library science |
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