基于证据熵对不确定性度量的决策表约简

知识约简是粗糙集理论的核心内容之一,产生的粗糙决策规则往往具有一定的不确定性.在变精度粗糙集的基础上,本文构造了符合证据理论框架的一组焦元,利用基本概率分配函数计算了证据的总体信息熵,度量了决策表的不确定性;以该度量作为启发信息,给出了决策表的启发式知识约简算法.计算实例表明了本文方法的有效性.     

A misclassification cost‐minimizing evolutionary–neural classification approach

Machine learning algorithms that incorporate misclassification costs have recently received considerable attention. In this paper, we use the principles of evolution to develop and test an evolutionary/genetic algorithm (GA)‐based neural approach that incorporates asymmetric Type I and Type II error costs. Using simulated, real‐world medical and financial data sets, we compare the results of the proposed approach with other statistical, mathematical, and machine learning approaches, which include statistical linear discriminant analysis, back‐propagation artificial neural network, integrated cost preference‐based linear mathematical programming‐based minimize squared deviations, linear integrated cost preference‐based GA, decision trees (C 5.0, and CART), and inexpensive classification with expensive tests algorithm. Our results indicate that the proposed approach incorporating asymmetric error costs results in equal or lower holdout sample misclassification cost when compared with the other statistical, mathematical, and machine learning misclassification cost‐minimizing approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

信息化知识表征的理论及方法

为了探讨信息时代里认知科学领域知识表征的特点和作用,通过梳理知识表征的发展过程,讨论信息化知识表征的理论和方法,分析了文字表征、图式表征、超文本表征、多媒体及虚拟现实表征的特点及其在认知中的作用。     

Modeling of unsupervised knowledge graph of events based on mutual information among neighbor domains and sparse representation

Text event mining, as an indispensable method of text mining processing, has attracted the extensive attention of researchers. A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper, i.e. UKGE-MS. Specifically, UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information, and solves the problems of traditional unsupervised feature selection methods, which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples. Firstly, considering the influence of local information of samples in feature correlation evaluation, a feature clustering algorithm based on average neighborhood mutual information is proposed, and the feature clusters with certain event correlation are obtained; Secondly, an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation, so as to enhance the generalization ability of the selected feature items. Finally, the events knowledge graph is constructed by means of sparse representation and l₁ norm. Extensive experiments are carried out on five real datasets and synthetic datasets, and the UKGE-MS are compared with five corresponding algorithms. The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection, and has some advantages over other methods in text event recognition and discovery.     

论道德教育对亲社会行为的培养作用——以“向陈洲贵同志学习”为例

亲社会行为具有无私增进他人利益的道德属性.亲社会行为与道德的这种特殊关系,决定了亲社会行为培养离不开道德教育的作用.事实上,道德教育对亲社会行为培养具有诸多正向作用.如道德榜样教育激发亲社会行为模仿,道德知识传授解释亲社会行为的合理性,道德舆论宣传创设亲社会行为的情境氛围等,通过考察这些正向作用,为亲社会行为的伦理培养提供有益思考.     

新疆中小学双语教师专业标准的实然性建构

自新疆推行双语教育以来,先后有14余万人跻身新疆双语教师行列,但始终没有一个统一的标准和基本规范来保障这一支庞大队伍的发展和进步。在经济快速发展和社会转型时期,构建科学而实用的双语教师标准对于新疆双语教育事业发展和进步有着重要的意义。在新教师专业标准的要求下,应基于自身教育身份的双重性和特殊性制定出满足国家和自身需要的行业规范和准则。在此,依据新疆中小学双语教师专业发展的实际情况并结合相关理论,提出建立中小学双语教师专业标准的方法和框架,为新疆双语教师专业标准的出台架构专业标准体系指标和拟案。     

L1-analysis稀疏重构在阵列信号恢复及波达角估计中的应用

通过适当的空域稀疏化构造了可对阵列接收信号进行冗余稀疏表示的阵列流形矩阵,建立了相应的L1-analysis稀疏重构模型用于恢复阵列接收信号,重点证明了该流形矩阵是满足L1-analysis 稀疏重构条件的紧框架,从理论上保证了将L1-analysis 稀疏重构用于阵列接收信号恢复及波达角估计问题的合理性,并推导出信号恢复误差的理论上界。利用在微波暗室环境中采集的实测数据,结合MUSIC算法进行实验验证,结果表明基于L1-analysis 稀疏重构的信号恢复对提高低信噪比环境下的波达角估计性能是有效的。     

SAR微动目标的稀疏贝叶斯成像方法

SAR微动信息能够反映出目标的属性信息,其微动图像可作为雷达目标识别的一种重要手段。基于SAR微动目标回波的稀疏特性,建立了在过完备词典下的稀疏表示模型,提出一种新的稀疏贝叶斯重构方法——方差成分扩张压缩,该方法仅赋予有重要意义的信号元素不同的方差分量,拥有更少的参数。仿真结果表明,方差成分扩张压缩方法能较精确地估计出SAR目标微动参数,同时能够获得低信噪比条件下较好的微动目标像。     

合同战术级军事专家系统研制

文中以合同战术级军事专家系统的实践为基础,以逻辑型语言为主要实现语言,描述基于黑板模型的问题求解策略,使用框架与产生式规则相结合的知识表示方法,以及运用基于预制文本与模糊文法的解释机制等。应用表明,本文提出和采用的方法与技术取得了明显的效益。     

故障诊断专家系统的知识处理

通过对航空火力控制系统故障诊断知识的分析,提出了将其分为精确知识、不全面知识和模糊知识的处理方法,对它们在故障诊断专家系统中的表示和实现形式进行了讨论和研究。通过利用人工智能语言Ｔｕｒｂｏｐｒｏｌｏｇ编程运行,表明这种知识处理方法,在表示能力、可理解性、可访问性、可扩充性方面都有较好的特性。