奥运会男子现代五项前三名成绩的灰色马尔可夫链预测模型的研究

研究了奥运会男子现代五项前三名成绩的预测模型.将灰色GM(1,1)模型和马尔可夫模型结合,构建了灰色马尔可夫预测模型.对奥运会男子现代五项前三名成绩趋势进行了预测,给出了第30届奥运会男子现代五项前三名成绩的预测结果,并大大提高了预测精度.     

奥运会男子现代五项前三名成绩的灰色预测模型的研究

研究了奥运会男子现代五项前三名成绩的灰色预测模型.将奥运会第16届至第29届男子现代五项前三名成绩数据进行分析处理,采用包络线法和新陈代谢法建立GM(1,1)灰色预测模型,预测了第30届男子现代五项前置名成绩.并对预测结果进行了分析.结果表明:该模型精度较高、预测误差小,预测结果可为我国体育决策部门、教练和运动员提供参...     

基于灰色马尔科夫模型的中国女子竞走成绩的预测

以中国女子竞走年度最好成绩作为原始数据序列建立灰色马尔科夫预测模型.研究表明:灰色马尔科夫预测模型对中国女子竞走成绩的预测具有更高的精确度与实用价值;通过对女子竞走年度最好成绩进行预测,预测结果显示中国女子竞走与世界女子竞走的年度最好成绩呈现出拉大趋势.     

推铅球的最佳抛射角应小于45°

推铅球运动起源于公元前的投掷石块比赛 ,后普及发展为最早的投掷项目之一 ,公元 1896年在雅典举行的第一届奥运会上 ,男子铅球列为正式的比赛项目 ,创造了 11.2 2米的纪录 .在 1984年伦敦举行的第 14届奥运会上 ,女子铅球也列为正式项目 ,创造了 13.75米的纪录 .推铅球的规则是 :运动员要在直径为 2 1.35米的圆形投掷场地进行投掷动作 ,从 1975年起规定铅球的质量为 7.2 6千克 .投掷方法也在不断改革 :古老的上步推球或垫步推球改为侧向滑步推球、背向滑步推球、旋转推球等 .近半个世纪以来 ,成绩有很大提高 ,男子铅球纪录提高了 4米 ,女子…     

基于最小二乘法的灰色组合预测模型及其应用

根据GM(1,1)模型原理,构建了灰色增量模型和灰色组合预测模型.分别利用中国和河南1986-2015年的人口数据建立模型,采用最小二乘法求解灰色组合预测模型的最优权系数.通过GM(1,1)模型、灰色增量模型和灰色组合预测模型对上述算例进行误差分析,实验结果表明灰色组合预测模型预测精度明显的优于其它单项预测模型.     

基于灰色马尔科夫模型的中国女子中长跑成绩的预测

以中国女子中长跑年度最好成绩作为原始数据序列利用灰色马尔科夫模型进行建模、预测与分析,意在为中国女子中长跑运动的可持续发展提供参考依据.研究表明:灰色马尔科夫预测模型对中国女子中长跑成绩的预测具有更高的精确度与实用价值;通过对女子中长跑年度最好成绩的预测可知:中国女子中长跑与世界女子的成绩差距呈现出拉大的发展趋势,这将对其各项目的发展带来严峻挑战.     

一类改进的灰色预测模型及其应用

通过将GM(1,1)模型中的灰色作用量改为动态形式,并利用最小二乘法确定时间响应函数中的常数c以及采用新陈代谢的思想,提出了一种改进的灰色预测模型.实例分析表明:改进模型在预测精度和实用性上均有较大改善,从而拓宽了灰色预测模型的适用范围.     

第29届奥运会中外男篮技术成绩统计分析

本文对第29届奥运会中国男篮同相遇对手的技术成绩指标,进行了相关性、偏相关、回归分析等多元统计分析,通过回归方程找出影响总得分的主要因素,利用多因变量的线性模型对29届中国队与对手整体上进行比较,并对中国队在28、29两届上进行了整体的比较。结果显示:29届奥运会上中国队和对手在整体水平上有一定的差异;和28届相比,中国队前后差异不大,说明中国男篮进步幅度不是太大。     

基于灰色关联理论的阿拉尔市城镇化水平评价及预测

从社会发展指标、经济建设指标、社会稳定指标和生态环境指标四个方面选取16个指标作为评价阿拉尔市城镇化水平指标,运用灰色关联理论法,计算各指标之间的关联度并排序.选取排名前面的指标,运用灰色GM(1,1)预测模型,建立阿拉尔市城镇化水平灰色预测模型,通过残差分析检验了模型的可行性.     

基于等维递补的多变量灰色组合预测模型

利用等维递补建立单个多变量灰色预测模型,进而建立多变量灰色组合预测模型.通过实例说明多变量灰色组合模型的应用和效果.     

初始因子在奥运会径赛数据分析中的应用——兼与Johnson R A和Wichern D W教授、王学民同志商榷

这里将初始因子的一些应用观点和结论列出,并通过奥运会男子径赛数据,指出初始因子应用中存在的问题,应用因子分析模型L及其精确解,初始因子解决问题的步骤,解决了奥运会男子径赛数据分析中存在的一些问题.     

Achievement and benchmarking of countries at the Summer Olympics using cross efficiency evaluation method

In this paper, an extension tool of data envelopment analysis (DEA), namely cross efficiency evaluation method, is used to measure the performance of the nations participating in the last six Summer Olympic Games. The model in the paper considers two inputs (GDP per capita and population) and three outputs (number of gold, silver and bronze medals won), and the weight restrictions are included to guarantee that a unit of silver medal corresponds to a higher valuation than a unit of bronze medal, and the highest for gold medal. The results for the last six Summer Olympic Games are analyzed, and a unique ordering of the participants based on average cross efficiency is provided, also cluster analysis technique is used to select the more appropriate targets for poorly performing countries to use as benchmarks.     

Ranking of countries in sporting events using two-stage data envelopment analysis models: a case of Summer Olympic Games 2016

After important sport events as the Summer Olympic Games (SOG) are, the participating countries are ranked according to the number of gold, silver and bronze medals. A lexicographic ranking is usually applied in official reports which leads to higher ranking of countries with one gold and no other medals comparing to countries without any gold but with several silver or bronze medals. Moreover, this ranking does not take into account the specific conditions of the countries (population, economic strength measured by gross domestic product and tradition in sports). The aim of the paper is not only to evaluate the absolute achievements of the countries but evaluate their performance with respect to the resources they can spent. A two-stage data envelopment analysis model is formulated and solved by an original slack-based measure procedure. The first stage evaluates the performance of the countries in training of athletes and the second stage evaluates the achievements of the nominated athletes. The models with variable returns to scale and weight restrictions are applied. The models and their results are illustrated on the case of Olympic Games 2016 and compared with results given by traditional approaches.     

Measuring the performance of nations at the Olympic Games using DEA models with different preferences

It is well known that Olympic Games often use Lexicographic preference to rank the nations that won the medals. However, Lexicographic preference is not the underlying preference that is used in the standard DEA models. Hence, we discuss the issue of the underlying preferences in DEA models for measuring the performance of nations at the Olympic Games, and then propose new DEA models with Lexicographic preference to measure the performance of the nations.     

The medal points’ incenter for rankings in sport

This work addresses the issue of finding a system of points for medals in Olympic ranking and scoring systems in sport. The incenter of a convex cone is used to obtain this system. The work deals also with the scoring systems. In applications, we present a ranking of countries in the 2010 Olympic Games and a ranking of drivers in the 2011 Formula One World Championship.     

The linear formulation of the ZSG-DEA models with different production technologies

The zero sum gains data envelopment analysis models (ZSG-DEA models) are non-linear. In this paper, we first show that the ZSG-DEA models can be transformed to linear or parametric linear models and discuss the feasible domains of the parameters. Second, we show that the linear formulations of ZSG-DEA models under the equal output reduction strategy and the proportional output reduction strategy in a single output case are equivalent to the output-oriented super-efficiency model under variable returns-to-scale (VRS) assumption. As a matter of course, the models may encounter infeasibility. Third, we propose the linear transformations of ZSG-DEA models under constant returns-to-scale (CRS) assumption and compare them with the VRS models. In the end, we evaluate the participant countries at the Olympic Games by the linear equivalent models with multiple outputs under different weight restrictions. Our results are compared with the efficiencies obtained from the original ZSG-DEA model with an aggregated output under both CRS and VRS assumptions. It is found that the original method with aggregated output tends to underestimate the efficiencies of DMUs.     

城市举办大型体育赛会能力的评估研究

城市争办大型体育赛会的激烈竞争凸显对其举办能力评估的重要性。本文运用搜集信息、调查统计、参数估计、聚类分析的方法,构建城市举办大型体育赛会能力的评估指标体系,提出相应的评估方法和步骤。以"十冬会"为例进行实证研究,分析哈尔滨举办"十冬会"的长处与不足。评估结果与选择2010冬奥会候选城市时国际奥委会评估小组对哈尔滨的评价具有较好的一致性。本文的结论为该评估指标体系和评估方法可有效分析城市举办大型体育赛会的能力,为提高城市申办国际性大型体育赛会的竞争力提供参考。