关于求解实对称非负定矩阵之g—逆的一个算法

我们约定,若对矩阵A=(a_(i.i)n×n进行T_h变换的累计次数为奇数,则称对a_(k.k)进行了有效变换,否则称对a_(k.k)进行了无效变换。若已对个m不同的对角元分别进行了有效变换,则称已对A进行了m次有效变换。若对A进行了一系列变换后,结果矩阵仍存在没有进行有效变换的非零对角元,则称此时消去变换是“可继续的”。选择一个尚未进行有效变换的主对角元进行消去变换,称为选择一个可行方向。若对A沿某可行方向进行了一系列有效变换后,结果矩阵中所有非零主对角元均已进行了有效变换,则称此时巳对A沿此可行方向进行了“无后续的变换”。     

不同参数下Galton板实验的探讨及仿真

介绍了 Galton板实验的实验现象和物理背景 ,建立了细致的概率模型对实验进行了分析 ,并基于模型对不同参数下的 Galton板实验进行了探讨 ,还利用 MATLAB编制了仿真软件 ,对结论进行了验证 .     

基于多属性群决策模型的评教方法

对高校学生网上评教存在的主要问题进行了分析,给出了网上评教的信息处理新方法.首先利用信息熵和正态分布函数对学生可信度函数进行了定义,再根据可信度大小对学生评价的权重进行了分配,最后利用加权算术平均算子对课程班的得分进行集结.数值算例分析了方法的有效性、合理性和可操作性.     

基于HBP估计的宏观经济统计数据诊断方法实证研究

HBP估计是具有高失效点的稳健估计方法,根据生产函数模型,利用LMS和MCD估计方法对浙江省相关年份的GDP进行了定量诊断,发现研究期间的GDP存在异常点和高杠杆点,并对异常点进行了验证,对高杠杆点进行了分析,解释了高杠杆点的产生原因。同时利用RLS估计方法对模型进行回归,根据回归结果对异常点进行了修正。     

基于神经网络的我国猪肉年度消费需求量预测研究

主要运用神经网络对中国猪肉年度消费需求量的预测问题进行了研究.首先对畜产品预测方法进行了综述,对神经网络预测原理进行了介绍,然后分别建立GM(1,1)、ARIMA模型、GRNN神经网络模型,GA-GRNN神经网络模型模型对猪肉消费量进行了预测,最后对模型进行了集成.结果表明,优化后的GA-GRNN模型预测误差率显著降低,集成模型在稳定性和精度方面均比较理想.     

丙型肝炎中免疫模型的动力学分析

对肝炎C病毒与宿主细胞及免疫反应之间关系的动力系统进行了分析,得到了模型平衡点的存在条件,并对复杂的平衡点进行了数值模拟,模拟结果显示系统是趋于渐进稳定的.而且对染病初期,进行抗病毒治疗的数学模型也进行了数值模拟,并且能够达到预期的效果.     

黑龙江省农业综合生产能力的动态分析

对农业综合生产能力的概念进行了界定,建立了农业综合生产能力的评价指标体系及评价方法,对不同时期黑龙江省农业综合生产能力进行测算,并对黑龙江省农业综合生产能力及其组成部分的变动趋势进行了动态分析.     

基于因子分析的畜产品消费需求量影响因素研究

主要运用因子分析方法对畜产品消费需求量的影响因素问题进行了研究.首先确定了影响猪肉消费的14个影响因素,然后通过因子分析对影响因素进行降维处理,接着对因子进行了旋转,进一步修正了因子分析的结果,同时运用主成分分析,对因子个数的科学性进行了验证,最后确定了影响猪肉消费需求的3个主要因子,即需求因子、价格因子和人口因子.     

离散时间投资组合保险策略CPPI及其实证分析

本文重点讨论了在离散时刻对投资组合进行调整的CPPI策略.给出了组合价值的过程表达式,并对其进行风险分析;引入二次期望效用函数,给出了确定CPPI策略中最优乘数的方法;讨论了借贷限制对CPPI策略的影响并将其与买入持有策略进行比较分析。最后,文章对CPPI策略的投资效果进行了实证分析.     

基于GOMPERTZ函数的上证综合指数预测的实证研究

对基于G om pertz函数的上证综合指数进行预测的可行性进行了分析,同时,在对上证综合指数的具体走势及实际数据进行研判的基础上,对牛市行情下上证综合指数的运行进行了预测的实证研究,得出了相应的结论,并提出了该预测方法进一步完善之处和可进一步深入研究的问题.     

居民生活私人交通碳排放驱动因素的“三级分解”模型

突破以往采用难以保证精确性估算数据的局限,根据居民生活私人交通所消耗的能源种类,利用官方统计年鉴中的数据,在保证数据真实性的基础上,基于扩展的IPAT与LMDI模型,构建一个包含居民私人交通碳排放强度、碳排放结构、交通消费倾向、收入、家庭规模与户数6个因素的居民私人交通碳排放驱动因素的"三级分解模型",对居民生活私人碳排放及其驱动因素进行核算.结果建议进一步降低居民私人交通碳排放强度,提高居民能源消费的利用效率;同时鼓励发展小排量与新能源汽车消费,并且大力发展公共交通,倡导居民出行多采用公共交通工具出行,引导节能减排的出行方式.     

基于模糊聚类分析的教师课堂教学质量评价

用模糊聚类的方法对教师的课堂教学进行分类分析,选取合适的相似系数,建立模糊相似矩阵,用直接聚类法进行分类,它不能实现我们传统意义的名次排序,但它很好的实现了量化评价和质性评价的结合,实现了评价的诊断功能,为信息反馈提供了依据,充分发挥了评价的导向和激励功能.     

基于集对分析的地区经济发展水平综合评价研究——以环渤海地区为例

地区经济发展水平问题是一个复杂的系统问题,运用集对分析同一度概念的综合评价方法,以环渤海地区为例,对其五个省市经济发展情况进行了综合评价、排序及分析,为环渤海地区经济发展提供借鉴和参考.     

Using the Tower of Hanoi puzzle to infuse your mathematics classroom with computer science concepts

This article suggests that logic puzzles, such as the well-known Tower of Hanoi puzzle, can be used to introduce computer science concepts to mathematics students of all ages. Mathematics teachers introduce their students to computer science concepts that are enacted spontaneously and subconsciously throughout the solution to the Tower of Hanoi puzzle. These concepts include, but are not limited to, conditionals, iteration, and recursion. Lessons, such as the one proposed in this article, are easily implementable in mathematics classrooms and extracurricular programmes as they are good candidates for ‘drop in’ lessons that do not need to fit into any particular place in the typical curriculum sequence. As an example for readers, the author describes how she used the puzzle in her own Number Sense and Logic course during the federally funded Upward Bound Math/Science summer programme for college-intending low-income high school students. The article explains each computer science term with real-life and mathematical examples, applies each term to the Tower of Hanoi puzzle solution, and describes how students connected the terms to their own solutions of the puzzle. It is timely and important to expose mathematics students to computer science concepts. Given the rate at which technology is currently advancing, and our increased dependence on technology in our daily lives, it has become more important than ever for children to be exposed to computer science. Yet, despite the importance of exposing today's children to computer science, many children are not given adequate opportunity to learn computer science in schools. In the United States, for example, most students finish high school without ever taking a computing course. Mathematics lessons, such as the one described in this article, can help to make computer science more accessible to students who may have otherwise had little opportunity to be introduced to these increasingly important concepts.     

Building Complex Solutions From Simple Solutions in the Animation Tutor: Task Completion

The goal of this project, an animation-based tutor for algebra word problems, is to build instructional software to improve estimation, reasoning, and problem-solving skills. In this study, we focused on the 2nd (task completion) module, which uses tank-filling problems in which the unknown variable is the time it will take to fill a tank. Students build on the answers to a simple (no leak) problem to estimate, and then calculate, answers to problems in which there is a leak in the bottom of the tank, a leak in the side of the tank, and a delay in starting one of the pipes. We evaluated the software in an intermediate algebra class consisting of a diverse group of students at a community college. We use the findings to discuss what works (estimation and the solution of the simpler problems) and to make recommendations on how to improve use of the decomposition method for solving the more complex problems.     

A Longitudinal Look at Attitudes and Perceptions Related to the Integration of Mathematics,Science, and Technology Education

The purpose of this study is to provide an in‐depth analysis of attitudes and perceptions related to the integration of mathematics, science, and technology education of preservice teachers preparing to teach STEM disciplines. Longitudinal data by individual cohort and across 7 years of the Integrated Mathematics, Science, and Technology (MSAT) Program are reported, analyzed, and interpreted to help design and improve preservice teacher education programs and improve teaching and learning in STEM classrooms. Results of quantitative analyses indicate that there was generally no change in preservice teacher attitudes and perceptions related to the value of the integration of mathematics, science, and technology education—they clearly valued integration at the onset and at the completion of the program. However, there was a significant change in preservice teacher attitudes and perceptions related to integration feasibility in terms of inefficiency and difficulty. Implications for teacher education programs include: (a) more exposure to concepts, processes, and skills in STEM that are similar, analogous, complementary, or synergistic; (b) familiarity with instructional strategies and access to resources; (c) deeper understanding of content across STEM; and (d) strategies for collaboration and team work to make integrated instruction time more efficient and less difficult to manage.     

Selective responses by entropy minimization

In this paper, we propose a method of entropy minimization for increasing selectivity and obtaining simple network architectures. An entropy function is defined with respect to the state of hidden units. By minimizing this entropy, the selectivity of hidden units can significantly be increased. Since a unit tends to respond to specific input patterns, the meaning or the function of the hidden units can easily be understood. In addition, we have observed that by minimizing the entropy, some units are forced to be inactive, responding to no input patterns. Thus, these inactive units can be deleted, and we can construct smaller network architectures. We applied the entropy method to standard and recurrent back-propagation. Experimental results confirmed that the number of units selectively responding to a specific pattern increased gradually, while units with low selectivity responding to multiple patterns decreased as entropy decreased. In addition, the number of units responding to no input patterns increased in proportion to the decrease of the entropy. These results show that the entropy minimization method can be used to improve the selectivity, and therefore, the interpretability of the network's behaviors. Then, the method can be used to suppress unnecessary units and to produce simple internal representation or simple network architectures.     

Providing operational analysis to a peace support operation: the Kosovo experience

The Operational Analysis (OA) Branch of the HQ ARRC deployed into Kosovo concurrently with the withdrawal of Serbian forces. The authors, all members of the Operational Analysis Branch, were responsible for providing general scientific, and more specifically Operational Research, advice to General Jackson, Commander of the Kosovo Force. This paper outlines the work done by OA Branch leading up to, and during the challenging period from the first deployment of troops into Kosovo in June 1999 to October 1999. The work of the branch was in two major sections; the first, support to returning Kosovo to normality and the second, to monitor the compliance of the Kosovo Liberation Army (UCK) with the undertaking to demilitarise. OA Branch provided not only the military with work to quantify the return to normality, but also worked with and provided data to aid agencies. The work ranged from assessments of damage to the infrastructure of Kosovo, particularly the housing, through to the monitoring of crime. The population estimates produced by the branch corrected the emotive image being produced in the media, and became the subject of an international press conference. OA Branch's weekly Compliance Monitoring report was the authoritative document for checking on the progress of the UCK towards demilitarisation; this coupled with work on trends in violence were regularly briefed to the KFOR Commander.     

Auctions with bidder-determined allowable combinations

Combinatorial auctions are desirable as they enable bidders to express the synergistic values of a group of assets and thus may lead to better allocations. Compared to other types of auctions, they keep bidders from being exposed to risks (of receiving only parts of combinations that would be valuable to them) or from being overly cautious (in order to minimize such risks). However, computation time needed to determine the set of optimal winning combinations in a general combinatorial auction may grow exponentially as the auction size increases, and this is sometimes given as a reason for not using combinatorial auctions. To determine the winning allocation in a reasonable time, a bid taker might try to limit the kinds of allowable combinations, but bidders may disagree on what combinations should be allowed, and this may make limiting the allowable combinations politically infeasible.This paper proposes and tests successfully a new approach to managing the computational complexity of determining the set of winning combinations. The main idea is to let bidders themselves determine and prioritize the allowable combinations. Using bidder-determined combinations has two nice properties. First, by delegating the decision on what is biddable to the bidders who know what combinations are important to them, the bid taker is able to be (and appear) fair. Second, since bidders know their economics and have the incentive to get important combinations included, bidder prioritization of combinations will tend to assure that the most economically-important combinations are included in determining the winning set of bids if the bid taker is not able to consider all of the combinations submitted by bidders. The proposed auction process is useful in situations, such as government auctions, in which the bid taker is reluctant to limit the allowable combinations.     

Imprecise stochastic orders and fuzzy rankings

We extend the notion of stochastic order to the pairwise comparison of fuzzy random variables. We consider expected utility, stochastic dominance and statistical preference, which are related to the comparisons of the expectations, distribution functions and medians of the underlying variables, and discuss how to generalize these notions to the fuzzy case, when an epistemic interpretation is given to the fuzzy random variables. In passing, we investigate to which extent the earlier extensions of stochastic dominance and expected utility to the comparison of sets of random variables can be useful as fuzzy rankings.