基于MQP模型的电离图参数反演解析算法研究

针对现今普遍采用的偏导迭代电离图反演算法存在的求解依赖于初值选择的不足,给出了一种初值选择准则,保证了该算法的收敛性。同时,利用该准则,以及在对电离图虚高表达式进行合理近似的基础上,提出了一种新的电离图参数反演算法,该方法实现电离图参数反演的解析计算,较偏导迭代法计算量大大减少,更好满足工程实时性要求。     

一种基于改进支持向量机的文本倾向性分类算法

文本的倾向性分类器是文本倾向性分类的核心部分,它用于将待分类的文本映射到某一倾向性类别中去。传统支持向量机的核函数学习能力和泛化推广能力的平衡性有待提高,而且参数选择不易。对目前文本倾向性分类算法使用的传统的支持向量机进行了改进,一是构造了多核函数;二是使用粒子群算法对支持向量机的参数进行优化,平衡了核函数的全局性和局部性,更有利于对样本数据的学习和推广;最后利用改进的支持向量机构造文本倾向性分类算法。     

自适应超混沌系统修正广义同步及其电路实现

运用自适应控制方法,实现超混沌Chen系统的同结构投影同步,并能辨识出响应系统的未知参数。首先通过采用MATLAB进行数字仿真,表明该自适应控制方法的可行性以及系统的参数辨识作用。其次利用EWB仿真设计模拟电路,结果与MATLAB的仿真结果相吻合,从而进一步证明了该自适应控制方法的有效性和系统参数辨识方法。     

Computing all efficient solutions of the biobjective minimum spanning tree problem

A common way of computing all efficient (Pareto optimal) solutions for a biobjective combinatorial optimisation problem is to compute first the extreme efficient solutions and then the remaining, non-extreme solutions. The second phase, the computation of non-extreme solutions, can be based on a “k-best” algorithm for the single-objective version of the problem or on the branch-and-bound method. A k-best algorithm computes the k-best solutions in order of their objective values. We compare the performance of these two approaches applied to the biobjective minimum spanning tree problem. Our extensive computational experiments indicate the overwhelming superiority of the k-best approach. We propose heuristic enhancements to this approach which further improve its performance.     

Evaluation of neural networks-based controllers in batch polymerisation of methyl methacrylate

The importance of batch reactors in today's process industries cannot be overstated. Thus said, it is important to optimise their operation in order to consistently achieve products of high quality while minimising the production of undesirables. In processes like polymerisation, these reactors are responsible for a greater number of products than other reactor types and the need for optimal operation is therefore greater.

An approach based on an offline dynamic optimisation and online control strategy is used in this work to generate optimal set point profiles for the batch polymerisation of methyl methacrylate. Dynamic optimisation is carried out from which controller set points to attain desired polymer molecular end point characteristics are achieved. Temperature is the main variable to be controlled, and this is done over finite discrete intervals of time.

For on-line control, we evaluate the performance of neural networks in two controllers used to track the derived optimal set points for the system. The controllers are generic model control (GMC), ([P.L. Lee, G.R. Sullivan, Generic model control, Comput. Chem. Eng. 12(6) (1998) 573–580]) and the neural network-based inverse model-based control (IMBC), ([M.A. Hussain, L.S. Kershenbaum, Implementation of an inverse model based control strategy using neural networks on a partially simulated exothermic reactor, Trans. IchemE 78(A) (2000) 299–311]). Although the GMC is a model-based controller, neural networks are used to estimate the heat release within its framework for on-line control. Despite the application of these two controllers to general batch reactors, no published work exists on their application to batch polymerisation in the literature. In this work, the performance of the neural networks within each controller's algorithm for tracking and setpoint regulation of the optimal trajectory and in robustness tests on the system is evaluated.     

一类线性时变系统组合自适应迭代学习辨识

针对一类在有限时间区间上可重复运行的既含时变参数又含时不变参数的高阶线性时变系统,提出了一种模型参考组合自适应迭代学习参数辨识算法.应用Lyapunov方法,给出了时不变参数的时域自适应学习律和时变参数的迭代域自适应学习律,分析了参数估计和模型状态跟踪误差的有界性与收敛性.该算法适于时变和时不变参数并存的线性系统的参数辨识,可加快参数估计的收敛速度.仿真例子验证了所提出的辨识算法的有效性.     

Hierarchical classification of protein function with ensembles of rules and particle swarm optimisation

This paper focuses on hierarchical classification problems where the classes to be predicted are organized in the form of a tree. The standard top-down divide and conquer approach for hierarchical classification consists of building a hierarchy of classifiers where a classifier is built for each internal (non-leaf) node in the class tree. Each classifier discriminates only between its child classes. After the tree of classifiers is built, the system uses them to classify test examples one class level at a time, so that when the example is assigned a class at a given level, only the child classes need to be considered at the next level. This approach has the drawback that, if a test example is misclassified at a certain class level, it will be misclassified at deeper levels too. In this paper we propose hierarchical classification methods to mitigate this drawback. More precisely, we propose a method called hierarchical ensemble of hierarchical rule sets (HEHRS), where different ensembles are built at different levels in the class tree and each ensemble consists of different rule sets built from training examples at different levels of the class tree. We also use a particle swarm optimisation (PSO) algorithm to optimise the rule weights used by HEHRS to combine the predictions of different rules into a class to be assigned to a given test example. In addition, we propose a variant of a method to mitigate the aforementioned drawback of top-down classification. These three types of methods are compared against the standard top-down hierarchical classification method in six challenging bioinformatics datasets, involving the prediction of protein function. Overall HEHRS with the rule weights optimised by the PSO algorithm obtains the best predictive accuracy out of the four types of hierarchical classification method.     

几种PID控制器设计方法的比较

现代过程工业中PID控制器的使用仍然占据统治地位.文章针对被控对象模型未知的情况,给系统加入白噪声,测得输出数据,通过输入输出数据估计模型阶次与延迟时间,从而得到被控对象模型.仿真结果表明,辨识模型能较好地反映原过程的动态特性.在此基础上,利用内模法、直接综合法及频域法这三种方法进行了PID控制器的设计,同时用随机性能指标和确定性指标对系统性能进行了评价.根据评价结果,对这三种PID控制器设计方法的适用条件给出了一些建议.     

基于小波算法的二阶线性定常分布参数系统的辨识

本文基于正交函数逼近方法,借助于小波变换,并利用其运算矩阵及其运算性质,研究了分布参数系统的辨识问题。将Haar小波正交基应用于分布参数系统的辨识中,经正交小波逼近变换,将原偏微分描述的分布参数系统转化为代数矩阵方程,并且,考虑了初始条件和边界条件,获得了算法简单、计算方便、具有较高精度的辨识算法,简化了分布参数系统辨识的求解过程,应用在分布参数系统辨识中不失为一种有效的分析方法。仿真实例表明了本文所提出的算法的有效性。