基于离散Hopfield神经网络的区域物流评价  

Regional Logistics Evaluation Based on Discrete Hopfield Neural Network

作　　者：忽晓阳 HU Xiaoyang(College of Management and Economics,Tianjin University,Tianjin 300072,China)

机构地区：[1]天津大学管理与经济学部,天津300072

出　　处：《综合运输》2021年第7期104-109,共6页China Transportation Review

摘　　要：区域物流的发展程度、技术水平、投入产出效率的高低己成为对一个区域的综合实力进行衡量的重要风向标。规范、先进、科学的区域物流评价体系,可以为区域未来物流发展规划提供纲领式的指导。本文基于全国(大陆)各省市区域物流的实际发展情况与相关数据,以因子分析、离散霍普菲尔德网络和聚类分析等算法为核心、构建区域物流发展评价指标体系,并对全国各省市区域物流发展状况进行定量评价。评价模型可在无监督的情况下,自我屏蔽小部分噪声数据的影响,收敛于最优的等级评价方式。The level of development,technology,and input-output efficiency of regional logistics have become one of the important indicators to measure the overall strength of a region.A standardized,advanced and scientific regional logistics evaluation system can provide programmatic guidance for the future logistics development planning of this region.Based on the actual development of regional logistics in the provinces(municipalities)across the country(mainland)and related data,this paper constructs an evaluation index system for regional logistics development based on factor analysis,Discrete Hopfield Neural Networks and cluster analysis and other algorithms.Quantitative evaluation of regional logistics development status of all provinces(municipalities)across the country(mainland).The evaluation model can self-shield the influence of a small part of the noise data without supervision,and converge on the best grade evaluation method.

关 键 词：区域物流 离散霍普菲尔德网络 评价体系 因子分析 协调发展 

分 类 号：F259.27[经济管理—国民经济]