Fuzzy-PID分级控制变水量空调系统温度的研究

针对变水量空调系统温度控制的时变、大滞后、非线性特点,结合模糊控制和PID控制,设计了基于模糊规则切换的Fuzzy-PID分级控制器,并在Matlab/Simulink软件上进行了仿真。仿真结果表明,控制器同时具有模糊控制超调量小、鲁棒性好和PID控制精度高、响应速度快的优点。     

基于模糊多核学习的改进支持向量机算法研究

针对传统SVM对噪声点和孤立点敏感的问题,以及不能解决样本特征规模大、含有异构信息、在特征空间中分布不平坦的问题,将模糊隶属度融入多核学习中,提出了一种模糊多核学习的方法。通过实验验证了模糊多核学习比传统SVM、模糊支持向量机以及多核学习具有更好的分类效果,从而验证了所提方法能够有效的克服传统SVM对噪声点敏感以及数据分布不平坦的问题。     

关于K-拟可加模糊积分的几点注记

在K-拟可加模糊积分定义及积分转换定理的基础上，证明这种模糊积分恰好构成K-拟可加模糊测度，并依据积分转换定理讨论这种K-拟可加模糊积分的一些补充性质。     

Evaluation of SARs for the prediction of skin irritation/corrosion potential–structural inclusion rules in the BfR decision support system†

The German Federal Institute for Risk Assessment (BfR) has developed a Decision Support System (DSS) to assess certain hazardous properties of pure chemicals, including skin and eye irritation/corrosion. The BfR–DSS is a rule-based system that could be used for the regulatory classification of chemicals in the European Union. The system is based on the combined use of two predictive approaches: exclusion rules based on physicochemical cut-off values to identify chemicals that do not exhibit a certain hazard (e.g., skin irritation/corrosion), and inclusion rules based on structural alerts to identify chemicals that do show a particular toxic potential. The aim of the present study was to evaluate the structural inclusion rules implemented in the BfR–DSS for the prediction of skin irritation and corrosion. The following assessments were performed: (a) a confirmation of the structural rules by rederiving them from the original training set (1358 substances), and (b) an external validation by using a test set of 200 chemicals not used in the derivation of the rules. It was found as a result that the test data set did not match the training set relative to the inclusion of structural alerts associated with skin irritation/corrosion, albeit some skin irritants were in the test set.     

Handling uncertainties in toxicity modelling using a fuzzy filter

A fundamental concern in the Quantitative Structure-Activity Relationship approach to toxicity evaluation is the generalization of the model over a wide range of compounds. The data driven modelling of toxicity, due to the complex and ill-defined nature of eco-toxicological systems, is an uncertain process. The development of a toxicity predicting model without considering uncertainties may produce a model with a low generalization performance. This study presents a novel approach to toxicity modelling that handles the involved uncertainties using a fuzzy filter, and thus improves the generalization capability of the model. The method is illustrated by considering a data set dealing with the fathead minnow (Pimephales promelas) toxicity of 568 organic compounds.     

分子的模糊对称性

将模糊数学方法引入对分子对称点群的研究,建立描述具有不完整分子对称性的模糊点对称群(集合).建立具有模糊对称性分子轨道的模糊表示及其模糊特征标(模糊广义宇称).通过对典型的线状分子、平面分子以及非平面的立体分子等进行分析,展示了一个新的理论化学园地.初步探讨了具有模糊对称性的动态反应体系.从模糊对称性出发,探讨了分子轨道对称守恒原理的半定量特征.     

西加毒素(CTX)的电子结构及构效关系研究

应用MNDO方法对CTX衍生物进行了量子化学计算 ,得到了它们的电子结构信息.根据构象分析研究了它们的空间结构.推测出它们的活性部位 ,探讨了与受体结合时的作用方式 ,讨论了结构 -活性关系 ,解释了活性差异的原因.研究结果表明该类化合物的D、E、F环和A环及其支链等部位的不饱和键对活性有重要影响     

辨识药物定量构效关系的模糊神经网络方法研究

提出一种基于遗传算法的新型模糊神经网络方法,用于计算Benzodiazepines(BZs)类药物的定量构效关系.这类模糊神经网络综合了神经网络、遗传算法与模糊逻辑的各自优势,具有优良的定量构效关系辨识能力,其学习速度较快,不易陷入局部最小区域;网络知识以模糊语言变量的形式加以表达,不仅易于理解,而且能有效地利用已有的专家经验.一旦通过学习获得规律后,不仅能很好地预测化合物的活性,还能对后续的药物分子设计提供有益的理论指导.     

模糊正交法用于石墨炉探针原子化测定铋条件的研究

模糊正交法是通过把正交试验结果模糊化,然后用模糊数学的理论和方法来处理实验数据。与常规正交设计相比,能在同样实验工作量的情况下获得更多的信息。本文采用模糊正交法对元素Bi的测定条件进行优化,并将其同常规正交设计方差分析的结果进行了比较,并提出一个综合评价参数,对建立的分析方法进行了综合评价。