人工神经网络在水质规划和管理中的应用

对人工神经网络在水质规划与评价、给水处理与污水处理等几方面的应用研究现状、发展趋势进行了综述，并通过一些实例分析得出：人工神经网络用于水质规划和管理不但可行，而且适应性强、结果客观、合理、具有深入开发的研究价值和良好的应用前景。     

2016—2020年云南土壤放射性水平及其变化趋势分析

根据2011—2020年云南辐射环境质量土壤国省控点²³⁸U、²³²Th、²²⁶Ra、⁴⁰K、¹³⁷Cs、⁹⁰Sr的监测结果,给出云南环境土壤放射性水平,得出云南环境土壤放射性水平总体平稳;云南环境土壤国省控点²³⁸U、²³²Th、²²⁶Ra、⁴⁰K的监测结果与云南省环境天然放射性水平调查结果相近,与云南土壤²³⁸U、²³²Th、²²⁶Ra、⁴⁰K分布趋势基本吻合;云南土壤²³⁸U、²³²Th、²²⁶Ra活度浓度略低于全国平均水平;由于大气迁移、沉降作用,早期核试验、核事故释放的核素¹³⁷Cs、⁹⁰Sr在云南环境土壤均有不同程度的检出。云南属伴生放射性矿产资源大省,滇西南某地...     

云南水环境放射性水平监测结果分析

根据2013—2020年云南省河流、湖泊、饮用水和地下水省控点、国控点的水中放射性水平监测结果,分析了水中总α、总β、U、Th、²²⁶Ra、⁴⁰K、¹³⁷Cs、⁹⁰Sr的监测浓度。结果表明:六大水系监测断面水中总α、总β均小于0.5、1.0 Bq/L;九大高原湖泊水中放射性水平相对较高的是Ⅴ类水体杞麓湖、异龙湖,放射性水平相对较低的是Ⅰ类水体抚仙湖、泸沽湖,滇池内海水中U、Th浓度优于滇池外海;饮用水源地水中放射性总α、总β均显著低于《生活饮用水卫生标准》(GB 5749—2022)规定限值。     

基于案例推理的化工园区应急资源需求预测

为确定化工园区突发事故的应急资源需求,提出了一种基于案例推理的化工园区应急资源需求预测方法。该方法主要由三部分组成:(1)基于案例推理的模型构建;(2)化工园区事故的案例描述;(3)基于人工神经网络的案例适应。最后,以石化园区火灾爆炸事故的应急资源需求预测验证该方法的有效性。研究表明,该方法可以实时地对化工园区应急资源需求进行预测,为化工园区的应急资源储备和配置提供支持。     

An alternative work measurement method and its application to a manufacturing industry

Difficulties in determining the standard time justify the need to develop alternative methods to direct measurement procedures. The indirect methods which are comparison and prediction, standard data and formulation, predefined movement-time systems have several deficiencies in time measurement procedures. In this study, an alternative indirect work measurement method based on artificial neural networks (ANNs) is presented which is simple and inexpensive. For the application of the proposed method, the products that have similar production processes are selected among the whole product family produced in a manufacturing company. The standard times of the sampled products that are previously measured are used and the standard times of the remaining several products and semi-products are predicted by the proposed method. The model results show that the proposed method can be applied accurately in companies which produce similar products.