基团贡献法对取代苯类化合物生物降解性的预测

测定了 47种取代苯类化合物在松花江水中的 5日生化需氧量 (BOD5) .分别采用线性基团贡献法和非线性基团贡献法(人工神经网络法 )对化合物的生物降解性BOD5 ThOD(ThOD :理论需氧量 )进行QSBR研究 .得到不同基团对生物降解性的贡献为 :C6H5>COOH >OH >CH3 O CH3 >NH2 >Cl >NO2 .线性基团贡献法对于训练组和测试组的定性预测正确率分别为72 %和 86 % ;而人工神经网络法的预测正确率分别为 92 %和 86 % .预测结果表明线性和非线性基团贡献法的预测效果都很好 ,相比而言 ,非线性方法对生物降解性的预测更准确     

Detecting neural tube defects by amniocentesis between 11 and 15 weeks' gestation

Forty-two open neural tube defects (NTDs) were identified in our series of 7440 amniocenteses tested between 11 and 15 weeks of gestation. Using a cut-off of ≥2.0 MOM, the detection rate for open NTDs was 95 per cent; 100 per cent each for anencephaly and spina bifida; and 78 per cent for encephalocele. Two encephaloceles had AFP levels less than 2.0 MOM and negative AChEs. Thirty-four (81 per cent) of these NTDs were tested between 13 and 15 weeks and 8 (19 per cent) before 13 weeks. There were 0.6 per cent false positives by AFP (excluding serious abnormalities and fetal death) and 0.1 per cent after AChE. The likelihood of an open NTD after an elevated AFP (≥2.0 MOM) was 24 and 77 per cent for any serious abnormality. These results, when combined with an earlier study, indicate that amniotic fluid AFP appears to be as sensitive a test for open NTDs between 13 and 15 weeks as between 16 and 20 weeks. Additional experience is necessary to determine this before 13 weeks.     

利用神经网络及数值模拟获取变压边力控制曲线

在应用Dynaform、Autoform等板料数值模拟软件的过程中 ,通常需要对压边力施力曲线进行各种预先的设定 ,但如何选定施力模式一直是一个比较棘手的问题 ,在文中利用数值模拟及MATLAB中的神经网络工具箱得出了压边力的最优控制曲线     

基于人工神经网络的行业无害化生产能力评价模型研究

利用BP前向人工神经网络方法 ,建立了一种全新的基于人工神经网络的行业无害化生产能力评价模型 ,该模型采用动量梯度下降反向传播和学习速率自适应调整相结合的训练学习算法。最后 ,以造纸及纸制品业为例 ,对中国各省市造纸行业的无害化生产能力进行评价 ;并进一步分析中国各省造纸行业无害化生产能力的时空分布规律 ,为我国行业规划、布局决策提供科学依据。     

建立土壤硫释放过程的人工神经网络模型

以温度、土壤含水率、胱氨酸添加量和土壤pH值作为土壤释放挥发性含硫化合物的主要影响因素,采用正交实验方法分析这些因素与土壤硫释速率的关系,利用BP神经网络算法对实验结果建模,并用模型对不同影响因素下的土壤硫释放情况进行预测。结果表明,网络模型对学习过的样本有较高预测精度,预测结果相对误差在2％以下,对未学生过的样本,误差为10％左右,表明人工神经网络方法建立的模型适用于土壤硫释放预测。     

事故出流时河流综合水质的计算机预测方法研究

河流上游的污水排放口或倒虹管等污水构筑因有可能发生事故出流而对下游的取水口存在着潜在的威胁，常规的单参数模型不能就事故出流对下游的影响作出公正评价。本文以QUAL－Ⅱ模型为骨架，以生动形象的动画形式演示出在整个排污过程中多个水质参数沿河道分布的变化全过程，并且，在模型中融入隶属度BP神经网络综合评价水质的模块，用它来对发生事故出流时下游取水口水域的水质变化进行综合评价，最后通过一个例子说明了该方法的优越性和合理性。     

Rural landscape planning case study of Nanhua State Farm

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基于神经网络的压铸合金选择

在归纳总结压铸合金选择经验和知识的基础上 ,对压铸合金性能进行评价。采用BP神经网络方法建立了快捷的压铸合金材料选择系统 ,提出了一种将模糊化性能要求量化 ,增加训练样本集的方法。     

Ecological networks and greenways in Europe: reasoning and concepts

The paper gives an overview of approaches towards ecological networks throughout Europe.It does not intend to present a complete picture,but to highlight comon developments within countries and regions and show common principles and differences between countries and regions that have to be taken into account when developing a joint European intiative,Countries or regions that have not been included can be active in the same way ,but information was not accessible to be authors for different reasons.This overview shows the comparable trends in decline of landscapes and the diversity in approaches to biodiversity conservation and nature conservation planning.Understanding the differences and common issues are of utmost imprtance to generalise common principles and to understand the way neighbours and other European partners approach problems.     

人工智能在金属塑性加工领域中的应用

概述了人工智能及其 2个主要分支 (专家系统和人工神经网络 ) ,讨论了遗传算法与专家系统集成以及神经网络与模糊逻辑、专家系统集成的必要性和集成方法 ,分别介绍了专家系统和人工神经网络在塑性加工领域中的应用现状。