社区生活圈的新时间地理学研究框架

社区生活圈从居民日常活动及行为视角考察城市社区,是城市地理学和城市相关学科的研究前沿,也是中国国土空间规划体系创新的重要组成部分,以及中国城市社会可持续发展的重要抓手。伴随着流动性和信息化的不断深入,社区生活圈的主体日益多元化、社区活动和居民时空行为日益多样化、社区空间的功能与意义日益丰富化,亟需城市地理学的研究创新与实践引导。时间地理学是理解人与环境关系的社会—技术—生态综合方法,为早期基于时空行为与生活空间的社区生活圈研究提供了重要基础。新时间地理学重视家庭及其他组织企划的交互与时空组合,可为社区生活圈内个体—家庭—社区之间的复杂互动关系研究、时空行为的社会文化制约与多情境分析及模拟提供重要支撑。论文基于新时间地理学方法,从理论、方法和实证3个维度提出社区生活圈的新时间地理学研究框架,具体包括构建社区生活圈的时空行为理论,揭示社区生活圈的时空间结构;创新社区生活圈的时空行为分析和模拟方法;从社区生活圈时空行为优化、社区交往生活圈、社区安全生活圈等方面创新中国城市规划与管理等研究内容。     

COMPARING TRADITIONAL METHODS FOR SELECTING CLASS INTERVALS ON CHOROPLETH MAPS*

The most common goal when classing data for choropleth maps is to create homogeneous classes which contain similar data values. None of the four traditional data classing methods examined here (quartile, equal interval, standard deviation, and natural breaks) consistently generalized the experimental data sets into homogeneous classes. These methods were most accurate for data sets with specific distributional characteristics, but none classed all of any type of distribution accurately. Only the optimization method produced reliable and accurate results for all of the experimental data.     

A Voronoi neighborhood-based search heuristic for distance/capacity constrained very large vehicle routing problems

Local search heuristics for very large-scale vehicle routing problems (VRPs) have made remarkable advances in recent years. However, few local search heuristics have focused on the use of the spatial neighborhood in Voronoi diagrams to improve local searches. Based on the concept of a k-ring shaped Voronoi neighbor, we propose a Voronoi spatial neighborhood-based search heuristic and algorithm to solve very large-scale VRPs. In this algorithm, k-ring Voronoi neighbors of a customer are limited to building and updating local routings, and rearranging local routings with improper links. This algorithm was evaluated using four sets of benchmark tests for 200–8683 customers. Solutions were compared with specific examples in the literature, such as the one-depot VRP. This algorithm produced better solutions than some of the best-known benchmark VRP solutions and requires less computational time. The algorithm outperformed previous methods used to solve very large-scale, real-world distance constrained capacitated VRP.     

An improved ant colony optimization (I-ACO) method for the quasi travelling salesman problem (Quasi-TSP)

Traveling salesman problem (TSP) and its quasi problem (Quasi-TSP) are typical problems in path optimization, and ant colony optimization (ACO) algorithm is considered as an effective way to solve TSP. However, when the problems come to high dimensions, the classic algorithm works with low efficiency and accuracy, and usually cannot obtain an ideal solution. To overcome the shortcoming of the classic algorithm, this paper proposes an improved ant colony optimization (I-ACO) algorithm which combines swarm intelligence with local search to improve the efficiency and accuracy of the algorithm. Experiments are carried out to verify the availability and analyze the performance of I-ACO algorithm, which cites a Quasi-TSP based on a practical problem in a tourist area. The results illustrate the higher accuracy and efficiency of the I-ACO algorithm to solve Quasi-TSP, comparing with greedy algorithm, simulated annealing, classic ant colony algorithm and particle swarm optimization algorithm, and prove that the I-ACO algorithm is a positive effective way to tackle Quasi-TSP.     

粒子群神经网络混合模型在农用地分等中的应用

针对常规农用地分等模型因子权重计算存在人为干扰和神经网络模型自身优化过程中易陷入局部最优的情况,该文综合了BP神经网络非线性权重数据挖掘特性和粒子群的全局优化能力,建立了农用地分等计算的粒子群神经网络混合模型(PSO-BP网络模型),并应用于广东省揭西县农用地分等计算中,发现PSO-BP网络模型能避免定级因子权重确定的人为干扰,同时具有较高的优化效率,应用效果较好。     

基于缓解沙漠高速公路风沙危害的路基参数优化——以榆靖高速公路为例

在沙漠地区修筑高速公路时,风沙对公路路基的危害是公路安全和运营的最大影响因子之一。为了寻求最适合沙漠地区高速公路风沙危害最经济的理论路基断面形式,通过对榆（林）靖（边）沙漠高速公路各种路基实测数据应用数学模型进行定量分析,查明了影响路基沙害程度的主要参数,提出了减少路基沙害程度的设计理念,并对不同路基形式的沙害程度进行了比较,给出了路基沙害程度较小的路基断面形式及参数值。研究成果对今后在沙漠地区修筑高速公路设计及施工具有一定的指导意义。     

吉林省村域尺度下居民点空间分布特征及优化重组模式

乡村聚落的空间优化与重构是提高土地资源利用效率,改善农村生产生活条件,促进乡村可持续发展的重要手段。以吉林省为例,采用核密度估计方法和景观形状指数分析了农村居民点空间分布特征,基于农户调查数据估算了吉林省不同区域的农村宅基地闲置情况,将农村居民点长期存在的“破碎化”和日益突出的“空心化”相结合,提出了在行政村尺度下农村居民点优化重组的“整小填大”新模式。结果表明：① 吉林省农村居民点规模小且零散分布,尤其中部呈破碎化分布,形态不规则,具有较大的整治潜力;② 吉林省农村宅基地平均闲置率为18.32%,西部地区最高（24.48%）,分别高于东部和中部地区约6%和12%;③“整小填大”模式可使农村居民点数量减少44.6%,增加有效耕地面积1 046.66 km²。     

基于贝叶斯网络的生态系统服务空间格局优化——以泾河流域为例

城市高速发展引起了区域土地利用格局的改变,不仅影响生态环境质量,而且还对生态系统服务的空间格局产生影响,在此基础上优化生态系统服务显得至关重要。在泾河流域2000—2020年净初级生产力（Net primary productivity, NPP）、农业生产力、土壤保持和产水服务空间评估的基础上,将贝叶斯网络和生态系统服务相结合,在关键变量子集和可视化的最优状态子集的基础上,评估了4种生态系统服务需要优化的区域,为区域经济和生态和谐发展提供参考。结果表明：（1） 水文评价模型（Soil and water assessment tool, SWAT）模型能较准确地模拟区域的径流量。通过模拟值和观测值对比分析,该模型具有较高的决定性系数（R²>0.6）和纳什效率系数（NSE>0.5）,可为进一步评估产水服务提供保障。（2） 2000—2020年泾河流域4种生态系统服务的时空差异性较为显著。在时间尺度上,4种生态系统服务均呈现波动中上升的趋势,在空间尺度上呈现较为稳定的变化趋势。（3） 通过对4种生态系统服务优化区域进行叠加分析,发现综合优化区域集中在彭阳县的中部和西南部以及环县的零星区域。研究结果对指导优化区域进行生态系统的可持续管理以及改善生态系统的退化状况具有重要意义。     

基于粒子群优化神经网络算法的深基坑变形预测方法

深基坑变形预测是进行施工参数调整和确保深基坑施工安全的重要手段,而如何对其变形进行有效、准确的预测是一个有待解决的技术难题。采用粒子群优化算法对神经网络模型的初始权值和阈值进行优化,并将已有的变形监测数据作为神经网络的输入参数,建立了基于粒子群优化神经网络算法的深基坑变形预测方法。将形成的方法应用于长春市火车站北广场深基坑开挖监测工程中。结果表明：8号水平位移测点预测结果的均方根误差为3.78%,平均百分比误差为5.48%;9号地面沉降点预测结果的均方根误差为5.62%,平均百分比误差为3.23%。经验证,本文方法预测深基坑开挖过程中的变形具有较高的可信度。     

An application of Karmarkar's interior-point linear programming algorithm for multi-reservoir operations optimization

Optimization of multi-reservoir systems operations is typically a very large scale optimization problem. The following are the three types of optimization problems solved using linear programming (LP): (i) deterministic optimization for multiple periods involving fine stage intervals, for example, from an hour to a week (ii) implicit stochastic optimization using multiple years of inflow data, and (iii) explicit stochastic optimization using probability distributions of inflow data. Until recently, the revised simplex method has been the most efficient solution method available for solving large scale LP problems. In this paper, we show that an implementation of the Karmarkar's interior-point LP algorithm with a newly developed stopping criterion solves optimization problems of large multi-reservoir operations more efficiently than the simplex method. For example, using a Micro VAX II minicomputer, a 40 year, monthly stage, two-reservoir system optimization problem is solved 7.8 times faster than the advanced simplex code in MINOS 5.0. The advantage of this method is expected to be greater as the size of the problem grows from two reservoirs to multiples of reservoirs. This paper presents the details of the implementation and testing and in addition, some other features of the Karmarkar's algorithm which makes it a valuable optimization tool are illuminated.