基于TGSOM的SDM技术及其在研发绩效评估中的应用

Zhibin Liu, Hanxian Hu
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引用次数: 1

摘要

研究与开发活动(R&D)作为高新技术企业的核心竞争力发挥着极其重要的作用和深远的意义。为了科学准确地衡量高新技术企业的研发绩效,本文将树状自组织成长图(TGSOM)网络引入到空间数据挖掘(SDM)中,用于空间聚类。该方法不仅弥补了一般空间数据挖掘中数据量大、计算量大的局限性,而且克服了传统地图(SOFM)必须预先指定的局限性。对河北省110家高新技术企业的绩效测量结果表明,该方法的结果是可靠的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SDM Techniques Based on TGSOM and its Application in R&D Performance Evaluation
Research and development activities (R&D) as the core competitiveness in the high-tech enterprises play an extremely important role and far-reaching significance. In order to measure the R&D performance of the high-tech enterprises scientifically and accurately, this paper introduces the tree-structured growing self-organizing maps (TGSOM) network into the spatial data mining (SDM) to be used in spatial clustering. This method not only can make up the limitation of the more data limit and biggish computation in the common spatial data mining, but also overcome the restriction of traditional maps (SOFM) that must appoint in advance. The performance measurement of 110 high-tech enterprises in Hebei Province shows that the results given by this method are reliable.
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