基于人工神经网络理论的船舶动力装置安全综合评价模型

为提高船舶动力装置安全综合评价水平，依据人工神经网络的基本原理，分析了BP神经网络模型的基本原理和优化策略，将其应用于船舶动力装置的安全评价之中。提出了基于神经网络理论的船舶动力装置综合安全评价模型及实现方法，并以实例论证了此方法的可行性。     

基于BP网络的建筑安装施工现场安全综合评价的研究

针对目前我国建筑安装施工现场安全评价技术的不成熟和欠科学性的现状 ,笔者分析和综合了目前安全评价技术 ,结合建筑业特点 ,提出了基于BP神经网络的建筑安装施工现场安全评价方法 ,并对该评价模型的原理、方法及算法进行了研究。首先 ,结合建筑安装施工现场安全生产的特点建立评价指标体系 ,随后 ,运用层次分析法确定指标及准则层的权重 ,并运用模糊综合评价法生成评价样本集 ,最后 ,利用样本集训练BP网络 ,待误差满足要求后 ,即可运用训练成功的BP神经网络进行安全评价。     

Environmental assessment of supercritical water oxidation of sewage sludge

Environmental aspects of using supercritical water oxidation (SCWO) to treat sewage sludge were studied using a life cycle assessment (LCA) methodology. The system studied is the first commercial scale SCWO plant for sewage sludge in the world, treating sludge from the municipal wastewater treatment facility in Harlingen, TX, USA. The environmental impacts were evaluated using three specific environmental attributes: global warming potential (GWP), photo-oxidant creation potential (POCP) and resource depletion; as well as two single point indicators: EPS2000 and EcoIndicator99. The LCA results show that for the described process, gas-fired preheating of the sludge is the major contributor to environmental impacts, and emissions from generating electricity for pumping and for oxygen production are also important. Overall, SCWO processing of undigested sewage sludge is an environmentally attractive technology, particularly when heat is recovered from the process. Energy-conserving measures and recovery of excess oxygen from the SCWO process should be considered for improving the sustainability potential.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

黄河积石峡水电站库区泥石流危险度评价

在选取一次(可能)最大冲出物方量、泥石流发生频率、流域面积、主沟长度、流域相对高差、流域切割密度、泥沙补给段长度比7个因子为泥石流沟谷危险度划分的主要因子的基础上,对评价因子隶属度的确定作了分析和阐述,并运用模糊综合评判法对黄河上游积石峡水电站库区16条泥石流沟进行了危险度划分.     

利用信息扩散模式对安徽及华东地区地震的风险分析

本文利用信息扩散模式,分别从年地震频次和年最大震级两个方面对安徽及华东地区的地震风险进行评估.结果显示:安徽地区ML≥3.0地震,年频次4次以上,约两年一遇;年发生ML≥3.9地震,则3年可能遇一次.而华东地区ML≥4.0地震,年频次4次以上,大约3年一遇;年发生ML≥4.9的地震,则可能2年遇一次.     

矿井电网动态安全分析系统的研究

随着国民经济的迅速发展,各行各业对煤矿资源的需求越来越大,然而矿难事故的频繁发生,煤矿安全已成为迫切需要解决的首要问题。笔者针对目前的矿井供电系统存在的不足而导致的安全隐患问题,进行了深入的理论研究和技术分析。根据煤矿供电系统的实际情况,对其供电系统的动态安全分析问题进行了较全面的探讨和论述;介绍了矿井电网动态安全分析系统的功能要求、主要组成部分和结构;对各部分的实现和需要注意的问题进行了分析;给出了矿井电网动态安全分析系统的框图及系统最终要反映的信息要求。     

基于模糊模式识别的模糊综合评价在高层建筑火灾危险评价中的应用

针对高层建筑火灾危险的特点,建立了高层建筑火灾危险评价的指标体系,并应用层次分析法确定了其权重。根据高层建筑火灾危险评价系统具有多因素、多层次的特点,采用模糊综合评价方法;针对模糊综合评价的不足之处,提出把权广义距离之和最小模糊模式识别运用到模糊综合评价当中,建立了基于模糊模式识别的模糊综合评价模型;该评价模型避免了单因素矩阵的确定和模糊算子的选择问题,用安全状态特征值来表征最终的评价结果,能使评价结果更加准确,可操作性强。通过对陕西某高层建筑火灾危险评价实例证明,该模型具有较好的应用价值,为日常的安全管理和性能化防火设计提供了有用依据。