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Public service resource allocation evaluation and site selection optimization decision making method using PCA-SOM based on autoencoder
- Telecommunications Science Vol. 40, Issue 2, Pages: 158-168(2024)
- 作者机构：
- 作者简介：
- 基金信息：
DOI：10.11959/j.issn.1000-0801.2024034
CLC： TP29；V241-
Published Online：2024-02，
Published：20 February 2024
- 稿件说明：
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Jun WEI, Hua WANG, Fanglin GUO, et al. Public service resource allocation evaluation and site selection optimization decision making method using PCA-SOM based on autoencoder[J]. Telecommunications science, 2024, 40(2): 158-168.
Jun WEI, Hua WANG, Fanglin GUO, et al. Public service resource allocation evaluation and site selection optimization decision making method using PCA-SOM based on autoencoder[J]. Telecommunications science, 2024, 40(2): 158-168. DOI： 10.11959/j.issn.1000-0801.2024034.
摘要
当前城市规划和公共服务资源配置存在分配不均和选址效率低下的问题。将公共服务资源的电力消耗数据与其资源数量、区域人口数量相结合，基于主成分分析（principal component analysis，PCA）评估各区域公共服务资源的配置状况，并以兰州市为案例，运用自组织映射（self-organizing mapping，SOM）算法进行教育资源的优化选址。研究发现，电力数据能有效指示资源配置的不足，并为优化分配提供精确的指导。尤其在兰州市，SOM算法的应用不仅提高了教育资源选址的效率，还促进了资源的公平分配。不仅为甘肃省提供了公共服务资源配置的科学决策依据，也为其他地区在相似领域的研究提供了参考。
Abstract
The distribution of urban planning and allocation of public service resources currently lacks consistency and suffers from inefficient siting.Electricity consumption data for public service resources was combined with resource quantity and regional population size to evaluate the allocation of public service resources in each region using principal component analysis (PCA).Additionally
the self-organizing mapping (SOM) algorithm was utilized to optimize the siting of educational resources in Lanzhou City as a case.The power data demonstrated the inadequacy of resource allocation and offered accurate guidance for optimal allocation
especially in Lanzhou City.By utilizing the SOM algorithm
the efficiency of educational resource siting was enhanced
and resource allocation was fairly promoted.This study offers a well-researched justification for public service resource allocation in Gansu Province
and serves as a significant reference point for similar research in other regions.
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