我国汽车报废回收利用体系框架初探

主要介绍了国内外废旧汽车回收处理现状,并从法制建设、回收网络构建、回收技术研究、宣传教育等方面提出了我国应对废旧汽车回收利用的对策建议。     

Prediction of the concentration of chlorophyll-α for Liuhai urban lakes in Beijing City

Introduction The eutrophication of fresh w ater has becom e a m ain w ater environm ental problem in the w orld. The m ain negative im pacts of fresh w ater eutrophication are w ater quality deterioration and the decrease of hydrophytes and aquatic specie…     

基于遗传算法的人工神经网络大气环境评价

人工神经网络模拟大脑的认知功能,通过改变连接点的权值和阈值来训练神经网络完成特定的功能。运用基于遗传算法的BP网络模型,以国家大气质量标准作为网络的输入样本对网络进行训练,对某地区大气质量进行评价,结果与综合指数法比较吻合。     

多氯酚QSAR数值模型比较研究

应用多元线性回归分析和新近发展起来的人工神经网络方法进行了一类重要环境污染物多氯酚的定量构效关系研究，并用所建立的模型进行毒性预报，计算值与实验值的比较表明，前的相关系数约为０．９２，后的相关系数约为０．９９．后的百分误差地明显小于前，后的预报能力略好于前，中还讨论了后优于前的的原因。     

Recurrence risk of neural tube defects following a miscarriage

Data from 280 sibships in three published series were used to see if the increased risk of neural tube defect (NTD) associated with having had a miscarriage in the immediately preceding pregnancy was also found in women with a previous affected pregnancy. A statistically significant relative risk of 4.0 (2-tail P=0.0111, Fisher exact test) was found among such women, and this could not be accounted for by the effect of parity or of a history of miscarriage in general. The finding may be useful when counselling patients.     

基于三层网络的SBR法深度脱氮智能控制系统的中试研究

以一座处理量为60m3·d-1的SBR法中试系统为研究对象,将三层网络智能控制技术引入SBR工艺中,并对该智能控制系统的深度脱氮效果和稳定性进行了中试研究.在SBR法硝化反硝化过程中,pH、DO、ORP曲线上会出现反映生物脱氮进程的特征点,以pH、DO、ORP为控制参数建立的智能控制策略可以准确判断反应的终点,避免了过度曝气,在保证深度脱氮的前提下节省了能耗.经过10个月的稳定运行,即使在温度较低的情况下,该SBR法智能控制中试系统出水的各项指标完全能够达到国家污水排放一级标准,并且达到了深度脱氮的效果,出水COD低于50 mg·L-1,总氮低于5 mg·L-1.     

青藏高原生态资产地域划分中的SOFM网络技术

针对目前地域划分中存在的问题,论文尝试以人工神经网络技术作为区划工作的理论支撑,构建了自组织特征映射SOFM网络,以青藏高原环境与生态系统资产作为待分客体,探索了新技术和方法在生态资产地域划分中的应用。结果表明,对于自然界中广泛存在的非线性问题,SOFM网络具有比聚类分析等线性分类器更强的适应性。应用SOFM网络在对待分客体生态资产进行类型划分的基础上,使用策略性循环尺度转换(SCS)范式对其进行了区域转换,最终完成了青藏高原范围内生态资产的地域划分。     

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。     

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.     

腹泻性贝类毒素的分析方法研究

本文描述了腹泻性贝类毒素的的特性，给出了已知的９种毒物成分的化学结构式衣不同毒物成分的毒性大小及毒理效应，对已有的该毒素的定量分析方法，包括生物分析法和化学分析法进行了剖析，重点阐述了化学分析法中的高效液相色谱分析法，介绍了法国目前使用的腹性贝毒的预警系统，并对我国该领域的研究提出了自己的建议。