本文關(guān)鍵詞：科技產(chǎn)出影響因素分析與預(yù)測(cè)研究——基于多元回歸和BP神經(jīng)網(wǎng)絡(luò)的途徑，，由筆耕文化傳播整理發(fā)布。

科技產(chǎn)出影響因素分析與預(yù)測(cè)研究——基于多元回歸和BP神經(jīng)網(wǎng)絡(luò)的途徑

Research on analysis of influencing factors and prediction for scientific and technological outputs an approach based on multiple linear regression and BP neural network

[1] [2]

HUZe-wen WU Yi-shan （ 1. School of Information Management, Nanjing University, Jiangsu 210093, China; 2. Institute of Scientific ＆ Technical Information of China, Beijing 10003

[1]南京大學(xué)信息管理學(xué)院,江蘇南京210093; [2]中國科學(xué)技術(shù)信息研究所,北京100038

文章摘要：首先通過文獻(xiàn)研究和網(wǎng)絡(luò)調(diào)查等定性分析方法梳理出科技產(chǎn)出能力的所有可能的影響因素,并在數(shù)據(jù)可獲得性的前提下,以1996-2008年為時(shí)間維,采集科技產(chǎn)出能力及其影響因素的相關(guān)數(shù)據(jù),然后對(duì)科技產(chǎn)出能力及其影響因素之間的相互關(guān)系進(jìn)行二元相關(guān)分析,并利用多元線性回歸分析方法從所有相關(guān)因素中篩選出影響程度較高的因素,構(gòu)建科技產(chǎn)出能力的影響因素分析與預(yù)測(cè)模型。最后基于二元相關(guān)分析的結(jié)果,選擇相關(guān)程度較高的因素,利用目前流行的BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)方法對(duì)科技產(chǎn)出能力進(jìn)行預(yù)測(cè)研究,并與多元回歸分析預(yù)測(cè)模型的預(yù)測(cè)性能進(jìn)行比較。

Abstr：Firstly, some qualitative analysis methods such as literature research and network investigation are applied to find out all the possible factors influencing scientific and technological（S＆T） outputs, and considering data availability, collect all related data to S＆T productivity and their influencing factors for the period 1996 -2008. Then based on the collected data, a bivariate correlation analysis method is utilized to analyse the mutual relations between S＆T outputs and their influencing factors, and with the multiple linear regression method selecting the high - influencing factors to construct a model analyzing influencing factors and prediction for S＆T outputs. Lastly based on the results of bivariate correlation analysis, a currently prevalent BP neural network prediction method is used to do a prediction study on S＆T outputs, and compare the predictive performance with that of multiple linear regression method.

文章關(guān)鍵詞：

Keyword：:multiple linear regression BP neural network scientific and technological outputs PCT patent applications SCI papers productivity impact factors analysis bivariate correlation analysis prediction

課題項(xiàng)目：國家自然科學(xué)基金資助項(xiàng)目（70973118）;江蘇省普通高校研究生科研創(chuàng)新計(jì)劃項(xiàng)目（CXZZ12-0075）

  本文關(guān)鍵詞：科技產(chǎn)出影響因素分析與預(yù)測(cè)研究——基于多元回歸和BP神經(jīng)網(wǎng)絡(luò)的途徑，由筆耕文化傳播整理發(fā)布。