移民搬迁农户收入来源的区位差异研究

移民搬迁的迁入区条件有较大差异,致使移民户收入差距拉大。以宁夏为例,采用典型调查法选取"十二五"期间移民搬迁的若干具有代表性移民安置点,设计出反映地理位置、自然环境、经济条件等方面的指标进行Q型聚类分析,将不同安置点划分为4类,比较各类特点以及农户生计特点;对分布在四类安置点的农户进行抽样调查,用描述统计方法比较家庭收入的均值和标准差,反映不同迁入区移民户收入来源及其差异,并对差异原因分析。研究结果表明:(1)移民农户收入与地域有直接关系,各类地区由于自然条件、资源禀赋以及政策扶持差异而导致移民收入有较大差距。移民区公共投入建设的力度、政府组织培训、劳务输出对移民收入及来源有很大影响;各地的经济基础也直接影响到移民的收入水平;移民户个人因素也不容忽视。(2)移民区后期建设应区别对待,因地制宜,改善条件,加大资源条件差的安置区的基础建设投入力度;加强产业培育,引导致富;通过各种形式组织农民培训;重视移民区社会管理,健全管理体系,建设和谐新村。     

基于主成分与聚类分析法的城市土地利用规划分区研究——以广州市为例

[目的]土地利用分区是土地利用总体规划的核心内容之一,是合理确定土地利用方向,优化土地利用结构与布局的重要途径。为了对广州市土地利用及未来发展方向提供理论指导,结合其土地利用现状和特点,选取土地利用结构、土地开发利用程度、社会经济状况和环境资源承载力4项一级指标及15项二级指标,建立土地利用综合分区指标体系。[方法]通过SPSS19.0软件,运用主成分分析法提取出前4个主成分,并将其作为新的样本数据,采用层次聚类分析法对广州市土地利用进行综合分区。[结果]根据聚类分区结果,将广州市分为4类土地利用区:中心发达区,包括荔湾区、海珠区、天河区和越秀区;综合发展区,包括白云区、番禺区、花都区、增城区和从化区;重点潜力区即南沙区;资源组合区是(新)黄埔区。根据各分区的差异性,提出各区域土地资源开发利用中存在的主要问题及未来发展方向。[结论]根据各区的自然经济条件及土地利用状况,将广州市分为4类土地利用区具有合理性,能为广州市今后土地利用规划的科学编制提供参考。     

基于综合价值分析的电子商务企业模糊聚类分析

在电子商务行业,因买卖双方目的不同,对商家的要求是不同的,为提高交易成功率,应对商家进行动态分类,以满足不同的需要。为此,本文从综合价值角度出发,构建电子商务企业综合评价指标体系,包含26个属性指标,引入模糊聚类分析,建立电子商务企业动态分类机制,通过实例分析,验证该方法的有效性合理性。     

要素密集型逆转与贸易获利能力提升——以中美纺织业为例

本文运用灰色聚类法并以中美纺织业为例,研究了产业生产要素密集型的逆转与贸易获利能力的提升问题。研究表明:以2000年中国制造业作为衡量标准,美国的纺织业在2003年从劳动密集型产业逆转成为技术密集型产业,而中国的纺织产业在考察期间一直为劳动密集型产业。文章进一步分析了要素密集型逆转的动因及贸易利得效应,发现在发生要素密集型逆转后美国纺织出口企业的获利能力明显大于中国,表明通过要素密集型逆转实现产业内升级是一条可行的路径选择。     

Segmenting the College Educated Generation Y Health and Wellness Traveler

Generation Y is considered to be the next largest cohort group to significantly impact the health and wellness travel industry. This study sought to create a profile of the Gen Y health and wellness traveler using push and pull motivations and perceived wellness. K-means clustering revealed five distinct traveler segments. Wellness was found to be a motivating factor as well as the other internal and external motivators used in this study. Men were found to travel more for escape and women for the nightlife. Opportunities to both seek and avoid contact with others were revealed. Suggestions for future marketing messages for the Gen Y wellness traveler are offered.     

Price Cycles and Asymmetric Price Transmission in the U.S. Pork Market

Economists have proposed several plausible explanations for observed price transmission asymmetries in commodity markets. Unfortunately, the econometric methods commonly used in such studies cannot empirically distinguish pricing behavior under the competing theories. We argue that the theories may be classified by firm responses to high- and low-frequency price cycles and use Engle's band spectrum regression to test the symmetry of high- and low-frequency cycles in weekly pork prices. The findings indicate that changes in wholesale prices are asymmetrically transmitted to retail prices in relatively low-frequency cycles, which does not support search costs and other high-frequency explanations. Conversely, wholesale pork prices asymmetrically adjust to changes in farm prices at all frequencies.     

浅论一种新的检查算法

利用平均步长的方法,查找给定值的结点位置,使用C语言描述其算法,讨论了该算法的平均检索长度,与其他算法比较,得出了该算法的优劣结论。     

A Fuzzy Clustering Algorithm Based on the Analogy with Mechanical Physics: MeccFuz

This paper presents a new algorithm of fuzzy clustering, based on analogy withmechanics physics. The vectors x_i are compared with `material points' and the clusters can be looked on as material points clouds, that are characterized byspecific units. The choice is based on a study of potential energy. Once a specificunit is chosen, we calculated the membership of the other units whit respect it.A study of a sociology test is performed and the results are very encouraging,though an further deepening is needed like a thermodynamics analogy application.     

A Partially Observed Model for Micromovement of Asset Prices with Bayes Estimation via Filtering

A general micromovement model that describes transactional price behavior is proposed. The model ties the sample characteristics of micromovement and macromovement in a consistent manner. An important feature of the model is that it can be transformed to a filtering problem with counting process observations. Consequently, the complete information of price and trading time is captured and then utilized in Bayes estimation via filtering for the parameters. The filtering equations are derived. A theorem on the convergence of conditional expectation of the model is proved. A consistent recursive algorithm is constructed via the Markov chain approximation method to compute the approximate posterior and then the Bayes estimates. A simplified model and its recursive algorithm are presented in detail. Simulations show that the computed Bayes estimates converge to their true values. The algorithm is applied to one month of intraday transaction prices for Microsoft and the Bayes estimates are obtained.