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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >Analysis of enterprise site selection and R&D innovation policy based on BP neural network and GIS system
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Analysis of enterprise site selection and R&D innovation policy based on BP neural network and GIS system

机译:基于BP神经网络和GIS系统的企业网站选择与研发创新政策分析

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摘要

The traditional spatial optimization location solution is difficult to solve the space optimization location problem under the condition of large data volume. However, GIS has the advantage of analyzing and processing spatial data, which can effectively compensate for this defect. In this paper, we analyze the enterprise site selection and R&D innovation policy based on BP neural network and GIS system. As a tool for the government to guide, encourage, support and adjust innovation activities and application of achievements, science and technology policy can provide new support for the development of innovation by improving the industrial chain and innovating the industrial structure. Moreover, the quantitative analysis of the entropy weight method and the qualitative analysis of the AHP method are combined to analyze a number of influencing factors. Based on this, the overlay of various factors is further analyzed, and the maximum eigenvalues of the target layer and the criterion layer and the weights of each index are calculated using MATLAB tools. Therefore, according to the different characteristics of different periods and different fields, the government should formulate science and technology innovation policies to improve the specificity and applicability of the policies.
机译:传统的空间优化位置解决方案难以在大数据量的条件下解决空间优化位置问题。然而,GIS具有分析和处理空间数据的优点,这可以有效地补偿这种缺陷。本文基于BP神经网络和GIS系统分析了企业网站选择和研发创新政策。作为政府的工具,以指导,鼓励,支持和调整创新活动和应用成就,科学和技术政策可以通过改善产业链和创新产业结构来为创新的发展提供新的支持。此外,组合了熵权法的定量分析和AHP方法的定性分析,分析了许多影响因素。基于此,进一步分析了各种因素的覆盖层,并且使用MATLAB工具计算目标层和标准层的最大特征值以及每个索引的重量。因此,根据不同时期和不同领域的不同特点,政府应制定科技创新政策,以提高政策的特殊性和适用性。

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