parking demand management 停车需求管理
parking-demand 停车需求
parking demand ratio 停车需求率
parking demand model 停车需求模型
parking demand forecast 停车需求预测
parking demand prediction 停车需求预测
parking demand predicating 停车需求预测
Parking demand forecasting methods used in cur- rent engineering practice suffer from two main shortcomings. Firstly, the estimated total parking volume may not always be within a reasonable range.
工程领域传统的停车需求预测方法存在两大缺陷,不能保证停车需求总量预测结果处于现实的合理区间,且模糊了停车泊位与车辆之间的内在联系。
参考来源 - 停车需求预测方法及应用Basing on the analysis and comparison the parking demand forecast model currently, recommend the parking generation rate model and discuss the modeling modifiability through the parameters of the peak-hour flow rate and vehicle growth rate.
在分析比较了国内外目前常用的停车需求预测模型的基础上，结合城市写字楼的停车特点，选用了停车生成率模型，并加入了高峰小时停车周转率、机动车增长率对停车生成率模型进行了修正。
参考来源 - 城市写字楼机动车停车设施配建研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Finally, construct the predicting model among parking demand and the remaining factors.
最终建立停车需求与剩余因素之间的预测模型。
Secondly, the prediction modeling based on BP artificial neural network for parking demand.
其次，建立基于BP神经网络的停车需求预测模型。
According to this, Guangzhou parking demand management task, principles and strategy are put forward.
在此基础上，提出了广州市停车需求管理的根本任务、原则和阶段性策略。
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