基于复合指纹图谱和贝叶斯模型的茅尾海悬浮颗粒物源解析

为明确茅尾海中悬浮颗粒物的来源,采集了茅尾海流域红树林土壤、堤岸土、河口颗粒物、茅尾海沉积物以及湾外颗粒物等悬浮颗粒物潜在源样品.基于多元统计复合指纹图谱方法,筛选出最佳指纹因子组合,进而通过贝叶斯混合模型得出五种潜在源对茅尾海悬浮颗粒物的贡献率.结果表明:Mg、Al、Mn、Pb、Fe五种指纹元素可作为最佳指纹因子组合,累计判别正确率为78%.贝叶斯混合模型结果显示,茅尾海悬浮颗粒物主要来源于河口和湾外输送,贡献率最高达到58.9%和68.6%.其中,靠近河口区域主要受河流汇入影响,其贡献率达到42.2%~58.9%;靠近湾外区域则以湾外颗粒物贡献为主,贡献率达到44.9%~68.6%.各点位的沉积物贡献率均较低,红树林土壤和堤岸土的贡献率都在10%左右.总的来说,由河口汇入和潮汐作用带入的颗粒物是茅尾海悬浮颗粒物的主要来源.     

水电厂电力设备事故应急响应FPN-MC模型及效能分析

为更好地利用信息技术研究水电厂电力设备事故应急效能,提高应急救援效率和应急处置能力,综合考虑应急响应过程中各个环节时间的随机性与模糊性,运用模糊Petri网（FPN）和马尔科夫链（MC）理论,构建水电厂电力设备事故应急响应FPN-MC模型,求解模糊稳态概率值并分析系统效能指标。最后,以ZLB水电厂电力设备事故Ⅲ级应急响应作为实例,进一步剖析应急流程信息拥挤的瓶颈环节及事件应急处置的关键节点。结果表明:应急资源使用完毕、相关人员现场处置到位、确定完善的处置方案时的状态最为繁忙;利用资源实施救援、相关人员进行现场处置、完善处置方案等实施过程需要重点监督和管理。     

基于贝叶斯网络的气井井筒完整性风险评价

井筒完整性失效是气井生产中的主要风险,为有效评价井筒完整性风险,应用贝叶斯网络的推理与学习能力,建立了基于贝叶斯网络和Noisy-OR gate模型的井筒完整性失效概率计算方法和风险评价模型。由故障树分析将井筒分为管柱、水泥环密封性、井口装置、水力屏障和其他部件5个评价单元,确定了各单元的主要风险因素,建立了井筒完整性失效的贝叶斯网络拓扑结构;由Noisy-OR gate模型和历史数据,确定了贝叶斯网络的条件概率参数;将基于贝叶斯网络的失效概率与层次分析法相结合,确定了风险评价指标和等级划分标准;建立了气井井筒完整性风险评价方法。结果表明,该方法实现了井筒完整性失效概率的定量计算、风险的定量评价和主要风险因素的反向推理,可为预防和控制井筒完整性失效提供决策依据,有助于降低井筒完整性失效风险。     

基于CREAM和贝叶斯网络的航空维修人为差错概率预测

航空维修差错不仅严重威胁着飞行安全,同时也会增加航空公司的维修成本。针对航空维修人员发生差错成因的复杂性以及历史事故数据缺乏的情况下,将人因可靠性与失误分析方法（CREAM）和贝叶斯网络（BN）相结合,提出一种改进的维修差错分析模型。根据维修任务构建相应的贝叶斯网络模型,为各子节点设置条件概率表（CPT）;基于维修基地的实际维修环境,对行为形成因子（PSFs）进行评估,得到共同绩效条件（CPCs）的水平;利用各CPC因子下各个行为功能失效模式的权重因子,对各认知活动进行失效概率的修正;将修正概率作为贝叶斯网络根节点的输入,利用推理机制,得到差错发生概率。通过案例分析和计算,验证了所述方法的可行性和有效性。     

基于Bayesian网络的建筑火灾疏散条件安全性评估方法*

为了对建筑火灾疏散条件安全性进行评估,基于Bayesian网络对疏散条件重要构成要素及评估方法逻辑推理过程进行研究探讨。结果表明:评估网络结构、根节点、中间节点及目标节点之间存在因果关联关系;研究得出根节点先验概率与量化节点条件概率表设定方法;Bayesian网络将风险评估与人工智能分析方法相结合,实现对建筑火灾疏散条件的安全性评估,并可用于识别高风险建筑。     

A systems-based approach for modeling of microbiologically influenced corrosion implemented using static and dynamic Bayesian networks

Microbiologically influenced corrosion (MIC) is a microbial community assisted degradation of materials affecting chemical processing and oil and gas industries. MIC has been implicated in incidents involving loss of containment of hazardous hydrocarbons which have led to fires and explosions, economic and environmental impact. The interplay between abiotic environmental factors and dynamic biotic factors in MIC are poorly understood. There is a lack of mechanistic understanding of MIC and very few models are available to predict or assess MIC threat. Here we report on the development of a model to assess the susceptibility to MIC. The high-resolution model utilizes 60 independent nodes, including operational and historical failure analysis data, and is built by combining empirical relationships between the abiotic and biotic variables impacting MIC. Both static and dynamic Bayesian-network (BN) approaches were used to combine heuristic and quantitative states of variables to ultimately yield a susceptibility measure for MIC. A confidence-in-information metric was generated to reflect the amount of data used in the estimation. A susceptibility to MIC of 45%–60% was estimated by the model for ten different scenarios simulated using case-studies from literature. The susceptibility to MIC estimated by these scenarios was further interpreted in the context of these cases. This systems-based MIC model can be utilized as an independent estimator of susceptibility or can be incorporated as a sub-model within comprehensive safety threat assessment models currently utilized in industry.     

深水钻井隔水管紧急解脱失效动态风险分析

为了分析钻井隔水管紧急解脱失效动态风险,保证深水钻井隔水管紧急解脱安全运行,通过辨识隔水管紧急解脱相关风险因素,以及隔水管紧急解脱失效的潜在后果,采用模糊事故树和事件序列图相结合的方法,建立隔水管紧急解脱失效后果模型;基于映射准则,将模型转换成贝叶斯网络,进行深水钻井隔水管紧急解脱风险的定量分析;研究了紧急解脱动态失效概率和关键致因,并从钻井隔水管系统设计、钻井作业、紧急解脱测试和操作等方面提出预防措施,以降低紧急解脱失效概率;以南海8号钻井平台为研究对象进行案例分析。研究结果表明:1年内隔水管紧急解脱失效的概率区间为0.075 7至0.105 0;台风、不合理的解脱时刻、过提力不足、井口倾角大和内波是导致紧急解脱失效的主要原因;该模型评估结果与实际情况相符合,该方法可用于钻井隔水管紧急解脱失效风险评价。     

水市场双边叫价贝叶斯博弈模型及机制设计研究

通过水权交易提高水资源的使用效率和配置效率,实现水资源最优配置。水权和水市场理论研究是水资源可持续利用的重要研究课题,而水权交易模型是水市场理论与实践中水权交易的核心。针对水权交易市场最常见的双边交易,采用双边拍卖的交易模式,通过对水权交易市场的双边交易进行描述分析,建立了水权交易买卖双方叫价拍卖的不完全信息博弈模型,给出双方叫价拍卖的机制设计。该机制具有有效性和激励相容性,最后给出算例。     

有限供水条件下农田灌溉时量优化——以河北省运东地区为例

本文探讨了灌溉水源限定条件下,农田灌溉时量优化计算方法,并以河北省运东地区3种主要作物为例进行了系统演算。从计算结果及其分析看,时量优化的经济效益明显,时量优化模型作为一种计算方法亦具有一定的实用意义。     

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