用神经网络辨识化学强化一级处理系统

运用实验室得到的数据为样本 ,选取了CODCr和絮凝剂投加量为指标 ,采用三层结构的神经网络 ,利用Matlab的神经网络工具箱中的批处理梯度下降法对CEPT系统经行辨识。辨识结果表明 :模型的预测值与实测值的平均误差在 3 .7%左右 ,具有较高的精度。同时 ,该模型还具有适应性强 ,使用方便 ,高效的特点 ,为CEPT系统的在线实时控制提供了一条有效的途径。     

Fe(Ⅲ,Ⅱ)/H2O2体系中Fe(Ⅲ)水解特征的对比

利用Fe Ferron逐时络合比色法对类Fenton与Fenton体系中Fe(Ⅲ )水解形态的转化规律进行了比较 .结果表明 ,水解度越高 ,两体系中Fe(Ⅲ )的水解速度也越快 ,但水解度相同时 ,与Fenton体系相比 ,类Fenton反应生成的Fe(Ⅲ )的水解速率要低 ,且Feb 所占比例也较少 .与Fenton体系一致 ,类Fenton体系中的Fe(Ⅲ )水解速率随H2 O2 浓度的增加而减缓     

天津地区表层土壤多环芳烃含量的中尺度空间结构特征

应用地统计学技术对全天津地区表层土壤中 16种优控多环芳烃含量和土壤理化参数进行了空间结构分析 .结果显示 ,各组分浓度均存在中尺度的空间自相关性 .多环芳烃浓度的空间结构存在明显的各向异性 .大气运移和土壤TOC含量可能是影响土壤多环芳烃浓度空间结构特征的重要环境因素 .     

三峡库区垃圾堆放场稳定化程度的模糊综合判别

从宏观和微观两个方面建立了垃圾堆放场稳定化程度的判别指标，即表观指标，垃圾堆龄，最大理论产气量，有机质含量和浸出液COD等，并且确定评价标准，稳定化程度分级体系采用稳定，基本稳定，较稳定和稳定4级，运用模糊数学的理论方法，综合判定三峡库区万州和尚桥垃圾堆放场的稳定化状态。     

极低频电磁场对健康影响的流行病学调查及人体测试研究进展

流行病学调查结果表明，环境的极低频电磁场暴露与人群某些肿瘤，如白血病、乳腺癌、脑肿瘤等，以及生殖、神经、心血管和内分泌等系统疾患的发病相关，这些结果在一定程度上得到实验室人体测试的支持。然而，极低频电磁场对健康影响的确切效应，迄今尚未能作出结论，亟等进一步开展多层次、多水平的研究。     

魔芋葡甘聚糖在污水处理中的应用

该文就魔芋葡甘聚糖的发展研究状况作了概述，并探讨其与蛋白质共混胶应用于水处理的可能性。     

Production of laccase by Coriolus versicolor and its application in decolorization of dyestuffs : (Ⅰ) Production of laccase by batch and repeated-batch processes

The production of laccase by Coriolus versicolor was studied.The effect of cultivation on laccase production by Coriolus versicolor was examined to obtain optimal medium and cultivation conditions.Both batch and repeated-batch processes were performed for laccase production.In repeated-batch fermentation with self-immobilized mycelia, total of 14 cycles were performed with laccase activity in the range between 3.4 and 14.8U/ml.     

对我国环境监测管理制度的思考

分析了我国环境监测管理制度的现状及存在的问题，提出了改革和完善我国环境监测管理制度的思路。     

滇池二维分层水质模拟研究

将三维问题“二维化”的分层迭代计算方法引入滇池水质模拟中，建立了湖泊二维分层水质模型，对滇池流场和总氮浓度场分两层进行了模拟计算，计算结果表明，该模型应用于滇池是成功的。     

Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data-A case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake

Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.