基于数据挖掘技术的大学城融合发展现状分析及优化路径探索

Xin Ma, Siew Eng Lin
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引用次数: 0

摘要

大学是城市发展到一定阶段的必然产物。在不同的社会环境和历史阶段,大学始终与城市共生发展,高等教育体系与新兴技术的融合可以加速大学与城市的区域经济发展。本研究基于数据挖掘技术,采用神经网络算法建立算法模型,以sigmoid函数为激励函数,对东莞市新兴科技产业与高校融合发展进行分析,为城市与高校融合发展提供优化路径。研究结果表明,在科技成果领域,东莞市高校2021年申请专利49726件,授权专利25523件,效率为51.33%。在城市经济发展方面,2021年东莞地区生产总值增长势头强劲,实现区域生产总值1085.54亿元,比上年增长8.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of the current situation of university- city integration development based on data mining technology and exploration of the optimization path
University is an inevitable product of a city's development to a specific stage. In different social environments and historical stages, universities always develop symbiotically with cities, and the integration of the higher education system and emerging technologies can accelerate the regional economic development of universities and cities. Based on data mining technology, this study uses a neural network algorithm to establish an algorithmic model and sigmoid function as the incentive function to analyze the integration development of emerging technology industry and universities in Dongguan city and provide an optimization path for the integration development of city and universities. The research results show that in the field of scientific and technological research results, the universities in Dongguan City applied for 49,726 patents in 2021 and authorized 25,523, with an efficiency rate of 51.33%. In the area of urban economic development, Dongguan's GDP in 2021 showed strong momentum, achieving a regional GDP of 108.554 billion yuan, an increase of 8.2% over the previous year.
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