不透水层是指能够隔离地表水渗透到土壤的覆盖表面,以不透水层分布变化来研究铜川城市化进程。利用决策树分类结合生物物理成分指数(BCI)和裸土指数(MBSI)的方法对1986,1991,1996,2002,2007,2012和2017年的遥感影像数进行不透水层提取,...不透水层是指能够隔离地表水渗透到土壤的覆盖表面,以不透水层分布变化来研究铜川城市化进程。利用决策树分类结合生物物理成分指数(BCI)和裸土指数(MBSI)的方法对1986,1991,1996,2002,2007,2012和2017年的遥感影像数进行不透水层提取,采用指标分析、重心轨迹偏移等方法探究不透水层空间扩展特征,并结合统计年鉴、DEM数据研究铜川市不透水层扩展驱动机制。结果表明:文中提出的基于决策树分类模型结合BCI和MBSI的方法对不透水层提取与验证数据的拟合优度达到0.88.铜川市的不透水层面积持续增加,面积从1986年的5.7 km 2增加到2017年的61.5 km 2,年均增长速度高达1.8%,特别是2007—2017年是快速城市化时期,增长面积占31 a变化总面积的69.3%.不透水层的重心呈先北后南的阶段性变化,1986—2002年向北移动,2002—2007年向南移动,2007—2017年继续向西南方向移动。通过对驱动力指标分析表明,经济及人口增长对不透水层扩展有着直接推动作用,矿产资源分布、地理环境限制和规划政策引导为影响研究区不透水层变化的主要因素。展开更多
The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of ...The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.展开更多
文摘不透水层是指能够隔离地表水渗透到土壤的覆盖表面,以不透水层分布变化来研究铜川城市化进程。利用决策树分类结合生物物理成分指数(BCI)和裸土指数(MBSI)的方法对1986,1991,1996,2002,2007,2012和2017年的遥感影像数进行不透水层提取,采用指标分析、重心轨迹偏移等方法探究不透水层空间扩展特征,并结合统计年鉴、DEM数据研究铜川市不透水层扩展驱动机制。结果表明:文中提出的基于决策树分类模型结合BCI和MBSI的方法对不透水层提取与验证数据的拟合优度达到0.88.铜川市的不透水层面积持续增加,面积从1986年的5.7 km 2增加到2017年的61.5 km 2,年均增长速度高达1.8%,特别是2007—2017年是快速城市化时期,增长面积占31 a变化总面积的69.3%.不透水层的重心呈先北后南的阶段性变化,1986—2002年向北移动,2002—2007年向南移动,2007—2017年继续向西南方向移动。通过对驱动力指标分析表明,经济及人口增长对不透水层扩展有着直接推动作用,矿产资源分布、地理环境限制和规划政策引导为影响研究区不透水层变化的主要因素。
基金Project(2012CB725402)supported by the National Key Basic Research Program of ChinaProjects(51338003,50908051)supported by the National Natural Science Foundation of China
文摘The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.
