基于神经网络和遗传算法的锅炉燃烧建模与优化

通过对影响锅炉效率的物理量的分析,建立了以神经网络表示主要物理量之间关系的锅炉燃烧系统模型,并采用遗传算法对模型进一步优化,从而实现了对锅炉燃烧的优化.仿真结果表明,通过调整锅炉燃烧系统优化模型参数,该模型能够同时满足锅炉燃烧效率和降低污染物排放的要求,从而实现锅炉的节能低污.     

基于Silverlight的海洋环境监测信息平台设计与实现

遵循完整性、先进性和开放性的系统开发原则,系统采用VS.NET开发平台,利用微软最新的Silverlight 技术以及其核心的Deep Zoom图像处理技术,以电子海图为基础,设计实现了全新的海洋环境监测信息平台.该系统已成功应用于南通市海洋与渔业信息系统中,实际应用表明该系统运行稳定可靠,在行业中具有较好的应用推广价值.     

高边界精度和抗噪的均值漂移图像分割算法

Mean shift(均值漂移)算法核函数窗口的带宽目前仍没有一个统一的确定标准.对整体图像根据Canny算子提取的边缘方向信息分成3类子图,一类是规则边缘子图,由规则边缘像素组成;第2类为非规则边缘子图,由边界方向变化剧烈的边缘像素组成;第3类是非边缘子图,由区域内部平坦区域和噪声区域组成.规则边缘子图和非边缘子图采用大窗口使区域内部更为平滑,并使噪声区域达到更高的抗噪性能,非规则边缘子图用小窗口可保持更高的边界精度.实验采用金属断口图像进行分割,结果表明,针对不同子图采用不同核函数带宽的方法使分割后的金属断口图像边界更准确,抗噪性能也更强.     

基于NPDM的保障系统顶层数据模型研究

介绍了北约产品数据模型(NPDM)的三层体系结构和EXPRESS数据建模语言,着重分析了NPDM顶层数据模型与产品寿命周期的关系,模型中各模式记录的信息内容和模式之间的关系.依据NPDM思想建立了保障系统顶层数据模型,阐述了模型中各模式记录的信息内容,给出了人力与人员、保障设备和保障设施等保障要素的数据结构,为进一步建立保障系统数据模型的打下了基础.     

微处理器VRM的滑模控制技术研究

为了改善微处理器VRM(电压调节模块)输出电压的动态响应特性和稳态纹波及精度,简化VRM滑模控制器的设计过程,通过深入研究滑模控制VRM的相关文献,全面评述了VRM的滑模控制技术应用及研究,重点分析了系统抖振削弱,稳态误差减小或消除、瞬态响应速度提高、开关频率的固定和降低、切换面的构造和滑模系数的选取方法以及滑模控制器设计方法的研究现状和取得的研究成果.实验分析结果表明,滑模控制器是最适合电压调节模块的控制器,VRM未来的工作重点是滑模控制器的设计与实现.     

具有人机交互接口的家庭安全报警系统设计

针对市场上各类家庭报警系统没有为用户提供人机交互接口的弊端,在传统报警系统的基础上对其功能进行了有意义的扩展,既实现了对非法侵入、火灾、煤气泄漏等各类家庭紧急情况的及时报警,又为用户提供了人机交互功能,解决了用户不能自行修改报警号码的问题,使整个系统设计更加人性化.给出了整个系统的硬件结构框图和软件设计流程图.     

应用带补偿的机会约束规划策略优化精馏过程的研究

精馏过程优化存在许多不确定变量,其对优化结果的影响是不可忽略的,所以需要找到真实反映不确定变最的数学模型,找到最优的求解方法得到精确解,进而得到最优的优化结果.本研究通过分析随机规划策略和不确定因素的特性及其对精馏优化过程的影响,对不确定因素进行分类,应用带补偿的随机规划和机会约束规划实现不确定因素对优化目标和约束的影响.对于模型中的机会约束,由于不确定输入变量和不确定输出变量间存在单调关系,所以可以通过对不确定输入变量的多重积分将机会约束转化为等价地确定性非线性约束,此时模型转化为含有非线性约束的带补偿的随机规划模型,此模型通过改进的蒙特卡罗(Monte Carlo)积分和含有序列2次规划(SQP)的Benders分解相结合的混合算法有效的求解.所提出的求解方法借助于Matlab软件能够得到比较精确的结果.采用本文所提出的模型及求解方法对精馏塔操作的模拟实验过程进行优化研究,可以看出带补偿的机会约束规划模型能够很好地反映不确定变量对优化过程的影响.所以本文提出的模型和求解方法是有效可行的,且对于以后的不确定优化研究具有很好的指导意义.     

Labeling design documents based on operators’ consensus—A case study of robotic design

Designers usually begin with a database to look for historical design solution, available experience and techniques through design documents, when initiating a new design. This database is a collection of labeled design documents under a few of predefined categories. However, little work has been done on labeling a relatively small number of design documents for information organization, so that most of design documents in this database can be automatically categorized.This paper initiates a study on this topic and proposes a methodology in four steps: design document collection, documents labeling, finalization of documents labeling and categorization of design database. Our discussion in this paper focuses on the first three steps. The key of this method is to collect relatively small number of design documents for manual labeling operation, and unify the effective labeling results as the final labels in terms of labeling agreement analysis and text classification experiment. Then these labeled documents are utilized as training samples to construct classifiers, which can automatically give appropriate labels to each design document.With this method, design documents are labeled in terms of the consensus of operators’ understanding, and design information can be organized in a comprehensive and universally accessible way. A case study of labeling robotic design documents is used to demonstrate the proposed methodology. Experimental results show that this method can significantly benefit efficient design information search.     

Short text similarity based on probabilistic topics

In this paper, we propose a new method for measuring the similarity between two short text snippets by comparing each of them with the probabilistic topics. Specifically, our method starts by firstly finding the distinguishing terms between the two short text snippets and comparing them with a series of probabilistic topics, extracted by Gibbs sampling algorithm. The relationship between the distinguishing terms of the short text snippets can be discovered by examining their probabilities under each topic. The similarity between two short text snippets is calculated based on their common terms and the relationship of their distinguishing terms. Extensive experiments on paraphrasing and question categorization show that the proposed method can calculate the similarity of short text snippets more accurately than other methods including the pure TF-IDF measure.     

Simple procedures of choice in multicriteria problems without precise information about the alternatives’ values

The additive model of multiattribute value theory is widely used in multicriteria choice problems. But often it is not easy to obtain precise values for the scaling weights or the alternatives’ value in each function. Several decision rules which require weaker information, such as ordinal information, have been proposed to select an alternative under these circumstances. We propose new decision rules and test them using Monte-Carlo simulation, considering that there is ordinal information both on the scaling weights and on the alternatives’ values. Results show the new rules constitute a good approximation. We provide guidelines about how to use these rules in a context of selecting a subset of the most promising alternatives, considering the contradictory objectives of keeping a low number of alternatives yet not excluding the best one.