关中平原人地关系地域系统SD模型及仿真

以渭河流域关中平原为例,在深入分析系统内外因素及其反馈关系的基础上,运用系统动力学（SD）构建关中平原人地关系地域系统模型,以模型为基础,建立了关中平原发展的三种可能情景,即理想条件下、资源约束下、资源环境约束下。采用Vensim PLE软件进行系统仿真模拟,获取三种情景下系统的仿真结果。对模拟结果分析显示：水资源和环境污染对未来关中平原发展具有重大而深远的影响,盲目的追求经济发展将使资源和污染更为恶化,必须将水安全和生态环境的保护作为建设中的重点。仿真的结果对关中地区未来发展战略制定提供了理论和现实依据。     

Planning life tests with progressively Type-I interval censored data from the lognormal distribution

In this paper, we determine optimally spaced inspection times for the two-parameter lognormal distribution for any given progressive interval censoring plan. We investigate the effect of the number of inspections and the choice of those optimally spaced inspection times based on the asymptotic relative efficiencies of the maximum likelihood estimates of the parameters. We also discuss the optimal progressive Type-I interval censoring plan when the inspection times and the expected proportions of total failures in the experiment are pre-fixed.     

准时生产方式下混流装配线的调度问题

混流装配线的调度问题是 JIT生产方式中的一个重要问题 .本文建立了多级混流装配线的调度模型 ,其目标是使不同生产级上各零部件的消耗量尽可能保持均匀 ,并用遗传算法和模拟退火进行求解 .试验表明 :遗传算法和模拟退火算法的求解质量比“目标追随法”有所提高     

Using the EM algorithm for Bayesian variable selection in logistic regression models with related covariates

We develop a Bayesian variable selection method for logistic regression models that can simultaneously accommodate qualitative covariates and interaction terms under various heredity constraints. We use expectation-maximization variable selection (EMVS) with a deterministic annealing variant as the platform for our method, due to its proven flexibility and efficiency. We propose a variance adjustment of the priors for the coefficients of qualitative covariates, which controls false-positive rates, and a flexible parameterization for interaction terms, which accommodates user-specified heredity constraints. This method can handle all pairwise interaction terms as well as a subset of specific interactions. Using simulation, we show that this method selects associated covariates better than the grouped LASSO and the LASSO with heredity constraints in various exploratory research scenarios encountered in epidemiological studies. We apply our method to identify genetic and non-genetic risk factors associated with smoking experimentation in a cohort of Mexican-heritage adolescents.     

带中途脱挂的干/支线两级运输网络牵引车调度优化

甩挂运输因牵引车与半挂车并行作业的高效性，在快递运输企业中逐渐得到应用。基于两级运输网络，本文提出"可中途脱挂"的甩挂运输新模式，同时，允许干/支线任务由同一台牵引车混合执行，构建了混合整数规划模型，并开发了混合模拟退火算法进行求解。在干/支线任务比例变化和任务总数变化两类仿真算例下，将本文的甩挂运输模式与"不可中途脱挂、干/支线任务混合执行"及"不可中途脱挂、干/支线任务分开执行"两种模式的总成本进行对比，验证了模型的有效性，体现出本文模式的显著优势及鲁棒性，并为快递运输企业的现实运营提供决策支持。     

Simulating dependent binary variables through multinomial sampling

A new method for simulating dependent binary data is presented. This methodology does not require specification of a parametric joint distribution, and instead uses desired dependence levels and marginal probabilities to construct a cumulative distribution function for the multinomial distribution of all possible combinations of binary outcomes. This method is simple to use and compute, and through simulation studies is found to be comparable with the gold-standard approach by Emrich and Piedmonte [A method for generating high-dimensional multivariate binary variates. Amer Statist. 1991;45(4):302–304].     

双肢薄壁墩温度效应仿真分析

在日照温度分布理论以及有限元分析方法的基础上，利用ANSYS的二次开发功能，编制了双肢矩形薄壁空心墩结构的温度场和温差效应分析的专用程序，并结合实例验证了仿真分析的准确性。同时以某高墩大跨连续刚构桥的双肢薄壁墩为研究对象，利用二次开发成果，对双肢矩形薄壁空心墩在日照温度荷载作用下的温度效应进行了分析，得出了双肢薄壁墩结构在悬臂状态与铰支状态两种不同的工况下，桥墩的温度应力与整体变形。结论可以为双肢薄壁墩的设计和施工提供参考。     

基于模拟退火遗传算法(N+M)容错系统优化模型的求解

本文提出了求解（N＋M）容错系统优化模型的模拟退火遗传算法．该算法在遗传算法的约束条件处理、交叉和变异概率选取、变异个体等环节引入了模拟退火机制，实现了模拟退火和遗传算法的融合，进一步改善算法的搜索能力、搜索效乍和收敛性能，计算结果验证了算法的有效性和正确性。     

A Bayesian decision theory approach to variable selection for discrimination

Motivated by examples in spectroscopy, we study variable selection for discrimination in problems with very many predictor variables. Assuming multivariate normal distributions with common variance for the predictor variables within groups, we develop a Bayesian decision theory approach that balances costs for variables against a loss due to classification errors. The approach is computationally intensive, requiring a simulation to approximate the intractable expected loss and a search, using simulated annealing, over a large space of possible subsets of variables. It is illustrated by application to a spectroscopic example with 3 groups, 100 variables, and 71 training cases, where the approach finds subsets of between 5 and 14 variables whose discriminatory power is comparable with that of linear discriminant analysis using principal components derived from the full 100 variables. We study both the evaluation of expected loss and the tuning of the simulated annealing for the example, and conclude that computational effort should be concentrated on the search.     

Minimax A‐ and D‐optimal integer‐valued wavelet designs for estimation

The author discusses integer‐valued designs for wavelet estimation of nonparametric response curves in the possible presence of heteroscedastic noise using a modified wavelet version of the Gasser‐Müller kernel estimator or weighted least squares estimation. The designs are constructed using a minimax treatment and the simulated annealing algorithm. The author presents designs for three case studies in experiments for investigating Gompertz's theory on mortality rates, nitrite utilization in bush beans and the impact of crash helmets in motorcycle accidents.