用微生物群落评价水系的自组织人工神经网络方法

利用原生物群落在PFU上群集过程中的变化,可以评价水质和监测水污染,运用T．Kohonen自组织人工神经网络模型,根据NacArthur－Wilson平衡模型提出了3个功能参数和另外2个结构参数,对常德市16个站四季的水质进行了分析,建立了水质污染程度预测的计算机智能专家系统,预测成功率达100％。     

水利水电工程环境影响综合评价的人工神经网络专家系统

在分级加权评价模型层次结构体系基础上,以三峡工程为背景,应用人工神经网络技术,建立了一个水利水电工程环境影响综合评价的人工神经网络专家系统,该专家系统的知识获取和存贮方式与普通专家系统不同,具有较高的推理效率,较强的容错、自适应和自我更新能力。      

Water quality indices appraisal and health risk assessment of nitrate,mercury and lead in water distribution network: A case study of Robat Karim in Tehran,Iran

Groundwater is a basic source of drinking water supply for urban and rural areas. This is especially the case for communities located in arid and semi-arid regions that rely on groundwater for drinking purposes. The present study set out to assess the potential health impacts of water impurities and to investigate the qualitative status of drinking water in Robat Karim rural areas, located in southwest Tehran, Iran. A total of 66 samples were collected from the water distribution network of 11 villages (33 sampling points, on two occasions) during September 2020 and were tested in terms of the most common quality parameters such as pH, mercury (Hg), lead (Pb), copper (Cu), zinc (Zn), chloride (Cl^–), chlorate (ClO₃^–), nitrite (NO₂^–), nitrate (NO₃^–), and flouride (F^–). Multiple methods and indexes including water quality index (WQI), hazard quotient (HQ), and hazard index (HI), were worked out to assess the quality of water and health risk assessment of NO₃^– Pb²⁺ and Hg²⁺. The results revealed that 33% and 90% of sampling sites have significantly high nitrate and total hardness (TH) concentrations, exceeding the maximum permissible limits set by World Health Organization (WHO; 50 and 200 mg/L, respectively). Furthermore, five sampling points exhibited poor WQIs mainly related to NO₃^– and TH. HQ values higher than 1 for nitrate were noticed in most sampling locations. Except for one sampling point, the HQ obtained for Pb²⁺ and Hg²⁺ were below 1 indicating no obvious health hazard. This study represents that children and infants are at higher risk of chronic toxicity by excess NO₃^– intake. The health hazard that is yet imposed on the community by NO₃^– necessitates regular monitoring of drinking water, the use of advanced technologies to purify water or otherwise alternative resources should be proposed.     

压缩空气泡沫水平管路压力损失数值模拟研究

为厘清压缩空气泡沫水平管道输运压力衰减规律,考虑压缩空气泡沫实际工程运用,利用STAR-CCM软件研究泡沫液种类、混合比和管径对湿泡沫水平管网输运过程中压力衰减的影响规律,并结合理论分析建立压缩空气泡沫水平输运过程中的压力衰减预测模型。研究结果表明：管路压降与泡沫液黏度呈正相关性,在混合液流量270 L/min,气体流量1 750 L/min条件下,相同管径高黏度抗溶性水成膜泡沫(AFFF/AR)压降约为低黏度A类和水成膜泡沫(AFFF)1.3倍;对于相同类型泡沫,混合比对管路压降影响较小,100 m长90 mm管径不同混合比之间最大压降差值约为7.21 kPa;管径对压降影响较大,相同泡沫条件下,50 mm管径压降是80 mm管径压降的约9.4倍,80 mm管径压降是100 mm管径压降的约2.8倍,当管径大于80 mm时,不同泡沫对压降的影响逐步减小。压力衰减预测模型计算的压降值与模拟值较前人开展研究所得实验值误差在18%以内,研究结果可以为压缩空气泡沫水平管网设计提供一定理论参考。     

基于知识的管道系统泄漏检测方法

提出了3种基于知识的管道系统泄漏检测方法,分别是:通过对负压波波形分段符号化处理,采用上下文无关法表示波形结构模式的模式识别诊断系统;以选取合适维数的功率谱特征向量而建立的神经网络泄漏检测系统;与泄漏机理数学模型结合的泄漏诊断专家系统。     

A water quality monitoring network design methodology for the selection of critical sampling points: Part II

In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.     

基于有上下界风量约束的矿井风量极值流算法研究

为解决既有方法不能准确求出矿井最大通风量与最小配风量,从而导致矿井通风系统产生能源浪费或难以满足矿井通风需求,出现安全隐患与改造难度大、潜力低等问题,提出1种基于有上下界风量约束的矿井风量极值流算法.该算法首先利用最大流算法求解满足节点流量平衡与分支上下界容量限制条件的可行流问题,若存在可行流,在求得可行流基础上,再利...     

Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province,China

Industrial technical accidents caused by natural disasters are defined as Natech accidents, such as earthquakes and landslides, which can cause tremendous damage to industrial storage tanks, and lead to accidental leakage and even serious fire and explosion accidents. In this study, a landslide-induced storage tank accident model under earthquake disasters was proposed, and the relationship between landslide mass impact and target impact resistance was taken into account. Also, tank failure and the formation of the pool fire were considered to be the consequences of the Natech accident. Through scenario deduction, the dynamic process of landslide Natech was transformed qualitatively into a disaster chain network diagram composed of a scenario state, a disaster-causing factor and emergency management. The Bayesian network was used to learn and deduce the parameters of the network diagram, and in this process, the prior probability and conditional probability of nodes were obtained primarily by Monte Carlo simulation, and by an improved expert scoring method based on the fuzzy set theory. Through visualization software, the sensitivity analysis of landslide Natech was achieved. Finally, a case study of a liquor storage tank area in Guizhou Province, China was carried out, and the results show that a large amount of hazardous material leakage caused by buckling is key to the formation of pool fire accidents, and several prevention measures for earthquake-induced landslide Natech was proposed according to the sensitivity analysis.     

线路交换开关级联失效的评估

本文主要针对信号线路交换网络设计中的失效问题展开讨论,对输出信号在传输网络中失效性进行了评估,根据失效评估在设备可靠性设计方面做了相应的考虑。     

Approximating SWAT Model Using Artificial Neural Network and Support Vector Machine1

Abstract: With the popularity of complex, physically based hydrologic models, the time consumed for running these models is increasing substantially. Using surrogate models to approximate the computationally intensive models is a promising method to save huge amounts of time for parameter estimation. In this study, two learning machines [Artificial Neural Network (ANN) and support vector machine (SVM)] were evaluated and compared for approximating the Soil and Water Assessment Tool (SWAT) model. These two learning machines were tested in two watersheds (Little River Experimental Watershed in Georgia and Mahatango Creek Experimental Watershed in Pennsylvania). The results show that SVM in general exhibited better generalization ability than ANN. In order to effectively and efficiently apply SVM to approximate SWAT, the effect of cross‐validation schemes, parameter dimensions, and training sample sizes on the performance of SVM was evaluated and discussed. It is suggested that 3‐fold cross‐validation is adequate for training the SVM model, and reducing the parameter dimension through determining the parameter values from field data and the sensitivity analysis is an effective means of improving the performance of SVM. As far as the training sample size, it is difficult to determine the appropriate number of samples for training SVM based on the test results obtained in this study. Simple examples were used to illustrate the potential applicability of combining the SVM model with uncertainty analysis algorithm to save efforts for parameter uncertainty of SWAT. In the future, evaluating the applicability of SVM for approximating SWAT in other watersheds and combining SVM with different parameter uncertainty analysis algorithms and evolutionary optimization algorithms deserve further research.