B－P网络用于水质综合评价方法的研究

本文应用误差反向传播（Ｂ—Ｐ）算法的人工神经网络建立了水质综合评价模型。该模型应用于实例的水质评价结果表明Ｂ—Ｐ网络用于水质综合评价具有客观性和实用性。     

现代企业制度下如何加强企业内部审计

加强企业内部审计是现代企业制度发展的客观需求,我国企业内部审计体系建设尚处于初级阶段,文章分析了加强企业内部审计的必要性和我国企业内部审计存在的主要问题,并提出了相应的优化措施,以期能对企业内部审计体系的完善起到一定的作用.     

Modeling and spatial prediction of pre-settlement patterns of forest distribution using witness tree data

At the time of European settlement, land surveys were conducted progressively westward throughout the United States. Outside of the original 13 colonies, surveys generally followed the Public Land Survey system in which trees, called witness trees, were regularly recorded at 1 mi by 1 mi grid intersections. This unintentional sampling provides insight into the composition and structure of pre-European settlement forests, which is used as baseline data to assess forest change following settlement. In this paper, a model for the Public Land Surveys of east central Alabama is developed. Assuming that the locations of trees of each species are realized from independent Poisson processes whose respective log intensities are linear functions of environmental covariates (i.e., elevation, landform, and physiographic province), the species observed at the survey grid intersections are independently sampled from a generalized logistic regression model. If all 68 species found in the survey were included, the model would be highly over-parameterized, so only the distribution of the most common taxon, pines, will be considered at this time. To assess the impact of environmental factors not included in the model, a hidden Gaussian random field shall be added as a random effect. A Markov Chain Monte Carlo algorithm is developed for Bayesian inference on model parameters, and for Bayes posterior prediction of the spatial distribution of pines in east central Alabama. Received: June 2004 / Revised: November 2004     

A capture-recapture model with heterogeneity and behavioural response

We develop the non-parametric maximum likelihood estimator (MLE) of the full M_bh capture-recapture model which utilizes both initial capture and recapture data and permits both heterogeneity (h) between animals and behavioural (b) response to capture. Our MLE procedure utilizes non-parametric maximum likelihood estimation of mixture distributions (Lindsay, 1983; Lindsay and Roeder, 1992) and the EM algorithm (Dempsteret al., 1977). Our MLE estimate provides the first non-parametric estimate of the bivariate capture-recapture distribution.Since non-parametric maximum likelihood estimation exists for submodels M_h (allowing heterogeneity only), Mb (allowing behavioural response only) and M₀ (allowing no changes), we develop maximum likelihood-based model selection, specifically the Akaike information criterion (AIC) (Akaike, 1973). The AIC procedure does well in detecting behavioural response but has difficulty in detecting heterogeneity.     

二维水质模型横向扩散系数的人工神经网络模拟

将人工神经网络的理论和方法引入河流横向扩散系数的理论预测中，提出了基于BP人工神经网络的横向扩散系统预测模型，应用国内外河流的实测样本对模型进行训练与检验表明，该模型用于横向扩散系数的计算不仅可行而且精度较高，为河流横向扩散系数预测研究开辟了新途径。     

济南裕兴化工总厂清洁生产审计

清洁生产审计是清洁生产的前提。根据产品的物料消耗以及废弃物量、环保费用和限期治理的要求 ,确定审计的重点是济南裕兴化工总厂钛白车间。对已产生的污染控制方案依据技术可行性、环境效果、经济效益、实施难度和对生产及产品影响等 5个因素进行筛选 ,共产生污染控制方案 69个。已经实施的无 /低费方案 ,收到了一定的环境效益和经济效益。对 3个中 /高费推荐方案进行技术、环境和经济评估 ,确定先启动钛白废酸浓缩至 40 %除铁后供磷肥配酸方案和钛白酸解尾气系统改造方案     

有限元仿真技术在板材成形中的应用

有限元仿真技术具有很强的经济性和柔性，已广泛应用于汽车钢铁工业领域。文中论述了板材成形有限元仿真分析的关键技术及其研究进展，并采用动力显式有限元软件LS-DYNA对轻型车侧围后外板零件冲压成形过程进行了仿真计算，分析了变形过程的金属流动规律。     

基于遗传算法的人工神经网络在降水酸度预测中的应用

在误差反向传播(Back Propagation)算法的人工神经网络结构模型的基础上，应用遗传算法训练神经网络权重，实现网络结构的优化。用优化后的BP人工神经网络建立了江西省南昌市的降水酸度预测模型。并将该模型预测结果与BP算法和多元线性回归法的预测结果进行了比较。检验结果表明：基于遗传算法的人工神经网络优于BP算法及多元线性回归法，具有良好的预测效果。     

我国环境审计方法和应解决的问题

中国严峻的环境状况和持续的经济发展使环境审计成为必要 ,本文提出了中国的环境审计内容和方法 ,并对我国开展环境审计应解决的若干重要问题进行了探讨 ,所得结果可供管理部门参考。     

加速基因算法在海洋环境预报中的应用

基于自然选择和自然基因机制的基因算法是一种优秀的寻优方法，它利用遗传操作算子来模拟生物界的优生劣汰的规律，是一种多路径全局优化方法。为增强经典基因算法对实际模型参数变化范围的适应性，加快其全局寻优速度和简化算法参数设置技术，本文给邮了一种改进基因算法，并在海渔期预报，冰情预报中得到成功应用。该法可广泛用于各种工程模型优化之中。