Adaptive neuro fuzzy inference system for classification of water quality status

An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and ammonia-nitrogen. A data set (nine weeks, total 845 observations) was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model. Up to 89.59% of the data could be correctly classified using this model. Such performance was more competitive when compared with artificial neural networks. It is applicable in evaluation and classification of water quality status.     

环境监测数据审核中各类数据逻辑关系的研究

环境质量监测数据审核是环境监测的最后一步,也是最重要的一环,是质量保证工作的重要环节。文章论述了环境监测数据审核的重要性。联系工作实际通过对环境质量监测各类数据的规律性、相关性进行研究,提出数据审核应注意的问题以及需要掌握的技巧,并详细的介绍数据审核包括的内容,重点介绍数据审核中水环境质量的审核和研究。重点要说明水的多项监测数据中存在哪些逻辑关系并且用科学的方法去证明这种逻辑关系,在证明的过程中利用历年的大量监测数据去比较分析证明。     

基于置信规则的村镇应急避难场所暴雨灾害链风险诊断*

为解决村镇应急避难场所面临暴雨灾害时的风险问题,基于故障树和置信规则库推理方法,提出暴雨灾害链和村镇应急避难场所功能破坏链相结合的场所避难功能失效风险诊断模型。根据事故致因理论推理灾害节点变量,通过故障树描述灾害链,运用关联规则从历史灾害数据中挖掘规则,建立置信规则库系统,构建村镇应急避难场所功能失效风险诊断模型,并以四川省某寄宿制学校为例进行模型验证。研究结果表明:该模型可实现不同证据组合下村镇应急避难场所功能失效风险的诊断推理;实例的模型诊断结果与实际情况吻合,证实该模型能够科学地诊断村镇应急避难场所面临暴雨等恶劣自然条件时存在的风险,可为村镇应急避难场所规划设计和应急管理提供理论支撑。     

双光谱卫星云图的模糊推理云分类

基于观测事实和分类经验,在对卫星云图上云系形态特征定性分析的基础上,采用模糊推理方法,提取出云类识别的诊断判别因子和模糊推理规则。通过对判别因子的模糊化处理和隶属度函数的调制优化,建立了卫星云图定量化的模糊推理云分类模型。4种常见云系的模糊推理分类试验结果表明,模糊推理方法在定量性、客观性和自动化等方面优于传统卫星云图目视判读方法,在卫星遥感资料的分析处理和天气预报等领域有较好的实用意义。     

A counterfactual approach to measure the impact of wet grassland conservation on U.K. breeding bird populations

Wet grassland populations of wading birds in the United Kingdom have declined severely since 1990. To help mitigate these declines, the Royal Society for the Protection of Birds has restored and managed lowland wet grassland nature reserves to benefit these and other species. However, the impact of these reserves on bird population trends has not been evaluated experimentally due to a lack of control populations. We compared population trends from 1994 to 2018 among 5 bird species of conservation concern that breed on these nature reserves with counterfactual trends created from matched breeding bird survey observations. We compared reserve trends with 3 different counterfactuals based on different scenarios of how reserve populations could have developed in the absence of conservation. Effects of conservation interventions were positive for all 4 targeted wading bird species: Lapwing (Vanellus vanellus), Redshank (Tringa totanus), Curlew (Numenius arquata), and Snipe (Gallinago gallinago). There was no positive effect of conservation interventions on reserves for the passerine, Yellow Wagtail (Motacilla flava). Our approach using monitoring data to produce valid counterfactual controls is a broadly applicable method allowing large-scale evaluation of conservation impact.     

基于演化博弈的危化品安全监管情景推演研究

针对危化品安全生产监管问题,基于演化博弈理论构建危化品安全监管演化博弈模型,并将危化品事故发生率引入模型,对比分析危化品企业与地方政府监管部门行为策略的演化稳定均衡。在此基础上进行情景推演模拟仿真,研究表明:危化品事故发生率,对危化品企业和地方政府监管部门的策略选择有显著影响,当危化品事故发生概率低于某一临界值时,危化品企业和监管部门都会疏忽安全投入和监管;地方政府承受危化品事故经济损失和信誉损失增大时,危化品安全监管系统演化呈现出周期性波动;引入上级政府惩罚机制情景下,当上级政府惩罚力度高于危化品企业未投入安全生产受到的处罚和地方政府安全监管成本时,其最终都选择安全投入和严格监管策略。研究结论为政府监管危化品安全生产提供新的思路和对策建议。     

A neuro-fuzzy algorithm for assessment of health,safety, environment and ergonomics in a large petrochemical plant

Process plants such as petrochemical units have been continuously trying to improve Health, Safety, Environment and Ergonomics (HSEE) programs. This study proposes an adaptive network-based fuzzy inference system (ANFIS) for assessment of HSEE programs in a petrochemical plant. The proposed neuro-fuzzy approach is applied to a set of operators in the petrochemical unit to show its applicability and superiority. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and accomplishment of HSEE programs is used as output for the algorithm. Moreover, this algorithm is used to rank operators performance with respect to HSEE. Finally, the algorithm identifies efficient operators with respect to HSEE. This is the first study that introduces an intelligence algorithm for assessment and improvement of HSEE program in a petrochemical plant.     

Asymptotics in adaptive cluster sampling

In this article we consider asymptotic properties of the Horvitz-Thompson and Hansen-Hurwitz types of estimators under the adaptive cluster sampling variants obtained by selecting the initial sample by simple random sampling without replacement and by unequal probability sampling with replacement. We develop an asymptotic framework, which basically assumes that the number of units in the initial sample, as well as the number of units and networks in the population tend to infinity, but that the network sizes are bounded. Using this framework we prove that under each of the two variants of adaptive sampling above mentioned, both the Horvitz-Thompson and Hansen-Hurwitz types of estimators are design-consistent and asymptotically normally distributed. In addition we show that the ordinary estimators of their variances are also design-consistent estimators.