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基于LV的SD模型反馈关系判定 被引量:1

Judgment of Feedback Relationship of SD Model Based on LV
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摘要 统动力学(SD)模型适合反馈关系明确的静态反馈系统,但对于反馈关系模糊的动态反馈系统,SD模型预测存在较大的误差.针对SD模型中反馈循环机制单调的问题,引入生态学中的Lotka-Volterra(LV)理论,利用LV模型对系统中历史数据关系进行判定处理,量化系统关系微变的节点,将SD模型中反馈节点按照LV理论进行时序演变判定,建立具有动态时变性质的LV-SD模型.通过Vensim模拟重庆市综合交通运输系统中三种运输方式的作用关系变化对GDP的影响,建立三维LV判定下的SD运输系统,模拟结果显示LV-SD模型比SD模型预测精度提高了近28%.LV理论能够量化SD模型中的反馈环节点关系,提高预测精度. System dynamics(SD)model is suitable for static feedback systems with clear feedback relationship,but for dynamic feedback systems with fuzzy feedback relationship,SD model has a large error in prediction.In view of the monotony of feedback loop mechanism in SD model,Lotka-Volterra(LV)theory in ecology was introduced,and the historical data relations in the system were judged and processed by LV model,and the nodes with slightly changed system relations were quantified.According to LV theory,the feedback nodes in SD model were judged for time evolution,and a dynamic time-varying LV-SD model was established.Vensim was used to simulate the influence of the change of the relationship between the three modes of transportation on GDP in Chongqing comprehensive transportation system,and the SD transportation system based on three-dimensional LV judgment was established.The simulation results show that the prediction accuracy of LV-SD model is improved by nearly 28%compared with SD model.The research shows that LV theory can quantify the feedback link relationship in SD model and improve the prediction accuracy.
作者 汪勇 徐韬 庞天泽 WANG Yong;XU Tao;PANG Tianze(Shanghai Urban Construction Design&Research(Group)Co.Ltd.,Shanghai 200092,China;Chongqing Municipal Research Institute of Design,Chongqing 400020,China;School of Civil Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,China)
出处 《武汉理工大学学报(交通科学与工程版)》 2021年第3期429-434,共6页 Journal of Wuhan University of Technology(Transportation Science & Engineering)
基金 国家社会科学基金项目(17XGL009)。
关键词 综合交通运输 系统动力学模型 LOTKA-VOLTERRA模型 反馈环 动态时变 comprehensive transportation system dynamics model Lotka-Volterra model feedback loop dynamic time-varying
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