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高速铁路运营客流量及收入集成估算系统研究

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针对现行高速铁路决策阶段运营客流量和收入预测误差大,历史数据存在的线性、二维、来源不可靠等问题.在深入分析客流量和收入影响因素的非线性、非确定性、耦合、非平衡性等演变趋势和机理的基础上,深入挖掘历史数据,依据BPNN、改进FC、FIS、粗糙集等理论方法,建立高速铁路运营客流量和收入多维时空基础历史数据库,构建基于BIM、PYTHON的客流量和收入非线性多维智能预测系统,实现对高速铁路运营客流量和收入的准确预测和多维展现.筛选出高速铁路运营客流量和收入相关复杂性影响因素;构建高速铁路运营客流量和收入历史数据多维时空数据支持系统;构建BPNN、改进FC、FIS运营客流量和收入预测模型,提高方法拟合性和预测准确性、有效性;设计并创建基于BIM、PYTHON的高速铁路运营客流量和收入多维智能展现系统,为提升高速铁路投资决策可靠性、可视化、智能化提供了技术和方法支持.
Research on Integrated Estimation System for Passenger Flow and Revenue of High-speed Railway Operations
In view of the problems of large errors in the forecast of passenger flow and revenue in the current decision-making stage of high-speed railway,as well as the linear,two-dimensional and unreliable sources of historical data,on the basis of in-depth analysis of the evolution trend and mechanism of the non-linearity,non-certainty,coupling and non-balance of the influencing factors of passenger flow and revenue,the historical data was dug further and a multidi-mensional spatiotemporal basic historical database of passenger flow and income in high-speed railway operations was es-tablished,based on the theoretical methods of BPNN,improved FC,FIS and rough set.A nonlinear multidimensional intelligent forecasting system was constructed for passenger flow and revenue based on BIM and PYTHON to achieve ac-curate forecast and multi-dimensional presentation of passenger flow and revenue of high-speed railway operations.The results show that following the selection of the complex influencing factors related to passenger flow and revenue of high-speed railway,a multi-dimensional spatiotemporal data support system is constructed for historical data of passenger flow and income of high-speed railway.The establishment of BPNN,improved FC and FIS operating passenger flow and reve-nue forecasting models improves the method fit and forecast accuracy and effectiveness.The multi-dimensional intelligent display system designed and created for passenger flow and income of high-speed railway operations based on BIM and PYTHON provides technical and methodological support for improving the reliability,visualization and intelligence of high-speed railway investment decision.

high-speed railwayforecastpassenger flowincomemulti-dimensionintelligence

孟阳、段鹏鑫、邓康丽、段晓晨

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石家庄铁道大学管理学院,河北石家庄 050043

河北经贸大学统计与数学学院,河北石家庄 050061

高速铁路 预测 客流量 收入 多维 智能

国家自然科学基金

72071133

2024

铁道学报
中国铁道学会

铁道学报

CSTPCD北大核心
影响因子:0.9
ISSN:1001-8360
年,卷(期):2024.46(4)
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