CAJ | 학술논문

区域物流需求的定量分析对于各种区域物流发展政策、区域物流规划有着重大意义。以广东、上海、广西三个地区为例，采集大量历史数据，构建完整的区域物流需求影响因素指标体系，利用粗糙集理论提取指标体系中的重要指标特征，从而构建PSO-SVM的物流预测模型。仿真结果表明，通过约简所得的不同地区的物流影响因子能够有效地代表非线性的物流数据特征，避免定性分析所带来的影响因子选择的主观性，以此构建的PSO-SVM模型能够准确有效地预测物流需求量。
구역물류수구적정량분석대우각충구역물류발전정책、구역물류규화유착중대의의。이엄동、상해、엄서삼개지구위례，채집대량역사수거，구건완정적구역물류수구영향인소지표체계，이용조조집이론제취지표체계중적중요지표특정，종이구건PSO-SVM적물류예측모형。방진결과표명，통과약간소득적불동지구적물류영향인자능구유효지대표비선성적물류수거특정，피면정성분석소대래적영향인자선택적주관성，이차구건적PSO-SVM모형능구준학유효지예측물류수구량。
Quantitative analysis of regional logistics demand has great significance for regional logistics development policy and regional logistics planning.In this paper, taking three regions of Guangdong , Shanghai, Guangxi as the example, we collect a large number historical data and build a complete influencing factors index system for regional logistics demand .We use rough set theory to extract important characteristics in the index system so as to build the PSO-SVM logistics forecasting model .Simulation results show that the logistics influencing factors of different regions derived from reduction can effectively represent the nonlinear characteristics of logistics data and avoid the subjectivity in influencing factors selection brought by the qualitative analysis , and the PSO-SVM model constructed in this way can accurately and effectively predict the logistics demand .