一类非线性混合整规划的无约束连续化解法

将整系数多项式 0 - 1混合整规划问题化成无约束多项式规划问题。通过解该问题 ,能得到原问题的近似解。处理方法的特点是能够直接处理不等式约束情形 ,而不需要先将不等式约束化成等式约束再来处理     

Human Salmonellosis: Estimation of Dose-Illness from Outbreak Data

The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al . Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.     

线性科学与非线性科学哲学思想研究

在简述线性科学的科学基础、科学方法和哲学思想的基础上，研究了非线性科学的科学基础、科学方法和哲学思想，其中较为详细地探讨了非线性科学的哲学范畴和哲学思想，认为要多角度观察事物，要从变化中认识主要矛盾，事物的发展是多元竞争与协同的统一，这一结果将对非线性科学的哲学思想的进一步研究有一定的启发和借鉴作用。     

ADDITIVE MODELS WITH PREDICTORS SUBJECT TO MEASUREMENT ERROR

This paper develops a likelihood‐based method for fitting additive models in the presence of measurement error. It formulates the additive model using the linear mixed model representation of penalized splines. In the presence of a structural measurement error model, the resulting likelihood involves intractable integrals, and a Monte Carlo expectation maximization strategy is developed for obtaining estimates. The method's performance is illustrated with a simulation study.     

城市土地集约利用的内涵及对策研究

本文经过分析,从不同方面对城市土地集约利用进行了解释,尝试性地给出了城市土地集约利用的内涵.同时,在理解城市土地集约利用内涵的基础上,对土地集约利用的政策进行了分析,提出了一些解决实际问题的措施.     

智能化仪表传感器非线性校正的实现

本文描述了传感器非线性特性预处理的方法．实践证明该方法适用于标准或非标准特殊传感器，处理结果使智能型仪表的测试精度有显著提高．     

合作处理中的团队透明性

对合作处理中的一些基本概念给出了明确的定义，并提出了一个有用的合作团队的模型。模型中的团队代理是实现透明性的依托，在此对其特性、行为及其构造作了描述。把合作团队的透明性分解为环境透明和编程透明，并给出两种进明性在ＯＳＥｗａｒｅ中的实现方法。     

基于二阶段随机规划的城市医疗废弃物回收网络设计

城市医疗废弃物日益增加,且回收需求量受诸多因素的影响,难以准确预测,假定回收需求为确定值的医疗废弃物网络优化设计不能与实际需求相匹配。本文考虑了离散随机参数环境下,医疗回收网络设计中选址规划、分配计划及运输规划的协同优化问题,建立了以选址成本、运输成本最小为目标,设施与车辆能力限制为约束的二阶段随机规划模型。根据模型特点,设计了基于Benders decomposition的求解算法,同时,设计了一系列加速技术用于提高算法的求解效率。最后,以国内某城市医疗回收网络为背景设计算例,检验本文模型和求解策略的可行性和有效性。结果表明：相比确定性规划,随机规划的解能够节约总成本,结合一系列加速技术的Benders decomposition方法比CPLEX与纯的Benders decomposition更有优势。     

国内外学前儿童计算思维研究述评

人工智能时代,计算思维已成为21世纪个体的必备素养。近年来,人们开始逐渐意识到从儿童早期培养计算思维的重要性,从小开始培养儿童的计算思维已成为世界各国的共识。然而,当前尚未对学前儿童计算思维的研究进行全面系统地梳理。因此,本研究结合文献计量法与内容分析法,对来自国内外核心数据库中的30篇实证研究进行了系统梳理,以此全面地了解国内外学前儿童计算思维培养的研究现状与发展趋势。与此同时,立足现状提出了对策与展望。     

复调和函数的混合边值问题

利用Ｆｏｕｒｉｅｒ方法得到复调和函数的混合边值问题解的表示式及解的存在性定理并讨论了解的唯一性．