基于GA-RBF网络的乙烯裂解炉在线操作优化

基于OPC技术实现过程数据的实时采集,并对所需变量进行数据滤波与异常检测,再利用RBF神经网络建立乙烯裂解炉过程多输入多输出(MIMO)裂解产物收率在线软测量模型以及模型校正方法,以乙烯和丙烯收率之和最大为目标,基于遗传算法对RBF神经网络模型进行操作优化,得到裂解过程的最优操作条件以指导生产.实际的工业应用表明,该方法提高了乙烯和丙烯的收率,具有良好的适应性和稳定性,对实际生产有重要的指导意义.     

乙烯热裂解炉模拟平台的开发及应用

为实现满足多种原料与多种炉型组态的乙烯热裂解模拟,本文开发了乙烯热裂解炉模拟平台。该平台基于裂解反应动力学的严格机理模型和分子反应动力学模型,支持对多种热裂解原料的裂解过程模拟。模拟平台还具有多种炉型组态建模、多周期生产模拟、原料预处理,以及重要参数的多种方法回归等功能。该平台应用于兰州石化公司乙烯裂解炉的模拟,结果准确,符合实际生产。     

基于AFSA-MVRVM的MTO反应过程双烯收率软测量

针对采用关联向量机进行软测量建模所存在的多输出建模问题,提出了一种鱼群优化算法(AFSA)—多输出关联向量机(MVRVM)软测量建模方法。通过加权组合全局性Poly核函数和局部性Gauss核函数,形成混合核函数多输出关联向量机模型,有效融合多特征数据信息;然后采用鱼群优化算法对多输出关联向量机模型的相关核参数进行优化,以进一步改善模型的输出精度和稳定性。将该建模方法应用于甲醇制烯烃生产过程(MTO)反应器出口乙烯和丙烯(简称双烯)收率软测量研究中,结果表明:采用该建模方法所建立的软测量模型能有效预测双烯收率变化,具有较高的预测精度和稳定性,这可为复杂化工过程多参数监测与控制提供有力的技术方法支持。     

模糊粒子群神经网络算法及应用

针对流程工业神经网络建模时,BP算法的局部收敛问题,采用模糊粒子群算法改进神经网络学习问题。该算法将模糊粒子群引入神经网络学习算法,使得粒子群的权重自适应更新,同时模糊粒子群自适应调整神经网络权重参数,改进网络收敛性。将算法用于建立乙烯裂解炉出口温度(COT)、裂解产品收率软测量模型,取得了较好的应用效果。     

SL-Ⅱ型乙烯裂解炉机理建模及在线应用

乙烯裂解炉产物收率的在线预报对于指导生产操作具有重要意义.针对某大型乙烯厂SL-Ⅱ型裂解炉,本文采用分子反应动力学模型,通过估算石脑油混合物性数据、调整1次反应系数,建立了该型号裂解炉辐射段的稳态工艺数学模型.采集实际操作工况数据对所建模型进行了验证,模型计算结果与装置分析值误筹在2%以内,进而将该模型用于裂解产物收率的在线预报,结果表明与色谱仪分析值的趋势一致.本文将基于分子模型和调整算法的机理建模应用于SL-Ⅱ型裂解炉产物收率的在线预报,并进一步探索长期预报的可行性,对乙烯裂解生产操作具有指导意义.     

乙烯裂解炉机理模型在线预报系统的设计与实现

乙烯裂解炉裂解产物收率的在线预报对于指导乙烯生产具有十分重要的意义.本文基于Kumar分子反应动力学模型,针对某大型乙烯厂SL-Ⅱ型裂解炉建立了该炉辐射段的裂解数学模型;采用C#和MATLAB混合编程技术开发了1套乙烯裂解炉产物收率在线预报软件系统;针对长周期运行的情况加入了模型在线调整功能,以随机搜索方式调整1次反应选择性系数,使模型能够及时与当前原料性质匹配.现场运行效果表明,系统的实时性和准确性满足生产要求,平均预报时间在10秒左右,乙烯等主要产物收率的系统预报值与工厂化验值的误差约2%:同时,系统具有良好的实用性,操作简便且运行稳定.该系统基于规范化的软件系统框架实现了乙烯裂解机理模型的实时运行和在线预报,以间接方式获得主要裂解产物收率的实时数据,为进一步指导生产过程优化、提高经济效益奠定了基础.     

基于自适应加权最小二乘支持向量机的芳烃产量软测量建模

芳烃收率是催化重整生产过程中的重要质量指标。针对其软测量建模中样本数据可能存在的测量误差对模型性能的影响,提出一种自适应加权最小二乘支持向量机(AWLSSVM)回归建模方法。该方法基于最小二乘支持向量机模型,根据样本拟合误差,并结合改进的指数分布加权规则,为每个建模样本分配不同的权值,以降低测量误差对建模精度的影响;同时提出一种全局优化算法—混沌粒子群模拟退火(CPSO-SA)算法对最小二乘支持向量机的模型参数进行优化选择,以提高模型的泛化能力。仿真实验表明,AWLS-SVM模型的预测精度及鲁棒性能优于LS-SVM和WLS-SVM。最后,应用AWLS-SVM方法建立催化重整生产过程芳烃收率的软测量模型,获得了较好的效果。     

基于KICA-TSVR方法乙烯裂解产物分布软测量

针对乙烯裂解关键质量指标乙烯裂解产物分布难以实时测量的问题,提出一种基于核独立成分分析与孪生支持向量回归机(KICA-TSVR,Kernel Independent Component Analysis-twin Support Vector Regression)软测量建模方法.该方法首先采用KICA(Kernel Independent Component Analysis)算法在非线性高维空间中进行样本特征提取,解决了TSVR因缺少结构风险最小化除噪能力差的问题,提高了模型预测精度.由于TSVR只需求解2个小规模的QP问题且其对偶问题中没有约束条件,使模型具有较快的训练速度.将KICA-TSVR用于乙烯裂解产物分布软测量建模,实验结果表明,同标准SVR(Support Vector Regression)和KICA-SVR方法相比,KICA-TSVR具有更好的模型预测效果和更快的训练速度.     

基于QGA-LSSVM的醋酸乙烯聚合率软测量建模

针对最小二乘支持向量机(LS-SVM)在建立醋酸乙烯(VAC)聚合率软测量模型过程中最优模型参数的选择问题,提出了利用一种量子遗传算法来自动选取LS-SVM模型正则化参数和核函数参数的方法;把LS-SVM模型参数的选择问题转化为优化问题,利用全局搜索能力强的量子遗传算法优化LS-SVM建模过程的重要参数,建立了基于QGA-LSSVM方法的VAC聚合率软测量模型;仿真结果表明:与已有的神经网络和支持向量机软测量方法相比,该模型泛化能力强,精度高,更有利于醋酸乙烯聚合率测量工程实际运用。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.