基于GIS的零售业商圈分析

科学、合理的市场需求分析和选址分析是零售商投资决策的重要依据。介绍了零售业商圈分析的基本过程及相应分析方法，并利用组件GIS技术，在商业地理信息管理系统的基础上构建了市场饱和度分析、商圈划分、需求估计3个商业应用分析模型，实现了对商圈的定量及可视化分析。最后以上海市徐汇区为研究区域，以大型综合超市这一商业业态为例进行了实验分析。     

浅谈智慧商圈的智慧化建设

为了解决商圈发展中的制约因素,认为应对前端基础设施进行智慧化建设,实现对商圈内的商户、客户的全方位感知;再对客流进行实时监测、统计、热力分析,实现数字赋能,用数据来辅助决策;同时建设线上服务中心来优化运营,从而可以更好的服务商圈内游客.智慧商圈的打造,必将提升商户及游客的好感,拉动商圈消费,提升商圈的商业活力.     

基于组件的上海市商业地理信息系统开发

在上海市商业服务业普查基础上,利用基于组件的GIS开发技术开发了上海市商业地理信息系统(单机版)。系统除了具有GIS基本的查询分析功能外,还根据商业管理与分析的特点,开发了商圈生成、商业网点的自动定位、网点分布的集聚度分析等功能。对系统的功能设计、界面设计以及开发技术进行了介绍,并总结了系统的特点。     

北京CBD首期WiFi商圈网络启用

<正>今后,东三环边财富中心连廊上的巨幅屏幕,将会被"移植"到从此经过或到商场购物的市民手机上。近日,CBD首期WiFi商圈网络在财富购物中心商场内开启。市民不但可以利用这一网络免费上网,还能接收到CBD商圈里最新的商业购物、休闲娱乐信息。据透露,不久后,"WiFi商圈"项目后期还将在CBD区域内覆盖建外SOHO等商业写字楼。日前,在CBD写字楼里上班的市民张洁在财富购物中     

面向智慧商圈的多源数据采集与综合评价系统

针对智慧商圈建设过程中各类数据需求,设计一个多源数据采集与综合评价系统。利用Pyspider框架采集数据,基于二分思想和多边形规则对采集的数据进行商圈边界探测、商圈内点判定,通过构建一套兴趣点与商圈的映射规则,解决不同数据源对商圈定义不同的问题。利用融合后的数据,从60多个维度进行商圈结构分析和对标分析。实验结果表明,该系统能为各类分析模型提供数据支持,从而为各类商业行为提供决策支撑。     

基于出租车GPS数据的商圈分析

出租车运营特性具有随机性、即走即停、覆盖范围广的特点,行驶的起止点由乘客决定,其运营规律能够很好地反映乘客出行的特点。根据出租车GPS的定位数据在真实地理空间的覆盖情况,可以还原居民出行的活动轨迹,挖掘潜在信息。提出采用出租车GPS定位数据进行商圈分析。通过对GPS定位数据进行网格划分、聚类,使用R语言建立相应的数据模型以及对模型的应用和结果分析。实验结果表明,将不同时段、不同地点的出租车特征进行统计分析做出折线图,可以识别出不同商圈类型,根据这些信息为潜在顾客的分布制定适宜的商业对策。     

基于GIS技术的零售商业规划管理创新

GIS（Geographic Information System,地理信息系统）与其它信息系统的区别十分明显，其核心是空间数据，也就是说它是关于空间数据的信息系统，在商业规划管理中，无论是店铺的区位选址，还是客户关系分析，商圈分析都离不开空间数据的支持。     

连锁门店选址与配送中心选择联合决策研究

借助商圈理论,在多商品多配送中心情况下,建立了连锁门店选址与配送中心选择联合决策问题的模型,针对该模型的特点,提出了一种适用的求解策略。通过改进哈夫模型,利用基于聚集度的启发式算法,对门店进行分类,确定门店与商圈的隶属情况;以商圈利润最大为目标建立混合整数规划模型,利用非线性规划寻优的遗传算法求解。应用算例进一步说明了该模型的可行性和有效性。     

国内

<正>杭州:湖滨打造智慧商圈"十年磨一剑",杭州湖滨商圈去年迎来了破茧成蝶般的蜕变:吃饭去知味观、杭州酒家,购物穿梭在解百、湖滨银泰,顺便再去工联、龙翔买点小东西……国际一线品牌的入驻、百年老店的回归,让这里已然成为杭州人气最旺的地方之一。更可喜的是,商圈内近来注入了愈来愈浓的"智慧元素":下载APP可点菜买单、商圈"角落头"WIFI随便用……这一切为商圈的发展注入新的活力,也让市民畅享吃、住、行、游、购、娱等方方面面智能化、个性化的服务。     

揭秘鼎好差异化经营之路

中关村商圈是中国商业竞争最为激烈的地区之一,在这个不足10平方公里的“弹丸之地”,云集了数千个IT品牌,上万个电子产品品类。电子卖场之间的竞争呈白热化。就是在这样的竞争环境下,鼎好用了5年就超过所有竞争对手,成为行业老大,个中原因,值得探究。     

Stable fitting of 2D curves and 3D surfaces by implicit polynomials

This work deals with fitting 2D and 3D implicit polynomials (IPs) to 2D curves and 3D surfaces, respectively. The zero-set of the polynomial is determined by the IP coefficients and describes the data. The polynomial fitting algorithms proposed in this paper aim at reducing the sensitivity of the polynomial to coefficient errors. Errors in coefficient values may be the result of numerical calculations, when solving the fitting problem or due to coefficient quantization. It is demonstrated that the effect of reducing this sensitivity also improves the fitting tightness and stability of the proposed two algorithms in fitting noisy data, as compared to existing algorithms like the well-known 3L and gradient-one algorithms. The development of the proposed algorithms is based on an analysis of the sensitivity of the zero-set to small coefficient changes and on minimizing a bound on the maximal error for one algorithm and minimizing the error variance for the second. Simulation results show that the proposed algorithms provide a significant reduction in fitting errors, particularly when fitting noisy data of complex shapes with high order polynomials, as compared to the performance obtained by the above mentioned existing algorithms.     

Parameter estimation of time-varying systems via Chebyshev polynomials of the second kind

A new method for the parameter estimation of linear time-varying systems using Chebyshev polynomials of the second kind is presented. The systems are characterized by linear differential equations with time-varying coefficients that are in the form of polynomials in the time variable. The operational matrices of integration and time-variable multiplication of Chebyshev polynomials of the second kind play key roles in the derivation of the algorithm. Least-squares estimation of overdetermined linear algebraic equations obtained from polynomial approximations of the systems is used to estimate the unknown parameters. Illustrative examples give satisfactory results     

多元非线性多项式智能拟合法及其应用研究

提出基于矩阵法结合遗传算法的多元非线性多项式智能拟合法。该法先将多元非线性多项式转化成多元线性多项式，建立最小二乘法标准矩阵，用遗传算法对多项式的项数、各项类型、次数等进行搜索组合，得到最优的拟合函数式，从而实现智能拟合的目的。用该法拟合了金祖源乱堆填料层压降通用关联图，结果令人满意。智能拟合法与传统的非智能拟合法相比具有可以自动寻求最优多项式、拟合精度高的优点。用Visual Basic6．0编程实现智能拟合法，算法稳定，收敛速度快。     

The 3L algorithm for fitting implicit polynomial curves andsurfaces to data

We introduce a completely new approach to fitting implicit polynomial geometric shape models to data and to studying these polynomials. The power of these models is in their ability to represent nonstar complex shapes in two(2D) and three-dimensional (3D) data to permit fast, repeatable fitting to unorganized data which may not be uniformly sampled and which may contain gaps, to permit position-invariant shape recognition based on new complete sets of Euclidean and affine invariants and to permit fast, stable single-computation pose estimation. The algorithm represents a significant advancement of implicit polynomial technology for four important reasons. First, it is orders of magnitude taster than existing fitting methods for implicit polynomial 2D curves and 3D surfaces, and the algorithms for 2D and 3D are essentially the same. Second, it has significantly better repeatability, numerical stability, and robustness than current methods in dealing with noisy, deformed, or missing data. Third, it can easily fit polynomials of high, such as 14th or 16th, degree. Fourth, additional linear constraints can be easily incorporated into the fitting process, and general linear vector space concepts apply     

Local hybrid approximation for scattered data fitting with bivariate splines

We suggest a local hybrid approximation scheme based on polynomials and radial basis functions, and use it to improve the scattered data fitting algorithm of (Davydov, O., Zeilfelder, F., 2004. Scattered data fitting by direct extension of local polynomials to bivariate splines. Adv. Comp. Math. 21, 223–271). Similar to that algorithm, the new method has linear computational complexity and is therefore suitable for large real world data. Numerical examples suggest that it can produce high quality artifact-free approximations that are more accurate than those given by the original method where pure polynomial local approximations are used.     

A method for regularization of evolutionary polynomial regression

While many applications require models that have no acceptable linear approximation, the simpler nonlinear models are defined by polynomials. The use of genetic algorithms to find polynomial models from data is known as evolutionary polynomial regression (EPR). This paper introduces evolutionary polynomial regression with regularization, an algorithm extending EPR with a regularization term to control polynomial complexity. The article also describes a set of experiences to compare both flavors of EPR against other methods including linear regression, regression trees and support vector regression. These experiments show that evolutionary polynomial regression with regularization is able to achieve better fitting and needs less computation time than plain EPR.     

隐式多项式曲线的信息建模研究进展

用隐式多项式曲线来描述数据点集合轮廓具有天然的优势,尤其是在数据点集合轮廓的拟合过程中体现得更为明显。概括了基于隐式多项式曲线的信息建模研究现状,侧重于目前国内外各种隐式多项式曲线拟合算法的分析以及优劣比较。以多个图像物体数据点集合轮廓为例,使用各种拟合算法对其进行拟合,并给出了拟合的效果,分析了算法的优劣和改进措施以及以后的研究方向.     

一种基于几何性质的鱼眼图像校正算法

为快速、高效地校正具有径向畸变的鱼眼图像,提出一种基于几何性质的校正算法。根据投影不变性原理以及径向畸变的几何特性,计算畸变直线的斜率,并通过求解线性方程组得出多项式校正模型的参数。实验结果表明,该算法能够以较低的运算复杂度获得较高的校正精度,相比于采用数学迭代拟合直线的方法,该算法在图像整体校正质量上有明显改善。     

Analysis of time-varying scaled systems via general orthogonal polynomials

General orthogonal polynomials are introduced to analyze and approximate the solution of a class of scaled systems. Using the operational matrix of integration, together with the operational matrix of linear transformation, the dynamical equation of a scaled system is reduced to a set of simultaneous linear algebraic equations. The coefficient vectors of the general orthogonal polynomials can be determined recursively by the derived algorithm. An illustrative example is given to demonstrate the validity and applicability of the orthogonal polynomial approximations.     

不变根分布的多项式的最大摄动界

已知不确定的特征多项式p(s,q),其系数依赖于参数向量q,一个富有意义的问题是: 可以允许q摄动多大而使摄动后的多项式仍保持标称多项式p(s,0)所具有的惯性(亦称根 分布)数?这就是所谓不变根分布的多项式的最大摄动界问题.本文将就仿射线性及仿射双 线性两情况给出上述问题的解答与算法.