基于粗糙集方法的产业技术创新能力评价指标约简

粗糙集理论在对不精确、不确定和不完全的数据进行分类分析和知识获取中具有突出的优势,但标准粗糙集的约简只适用于将系统连续属性值或描述性语言转化为离散属性值。针对目前产业技术创新能力评价指标冗余繁杂且相关性较大的缺陷,以装备制造业为例,提出了一种无需将系统原始连续属性值离散化即可有效运用粗糙集进行约简的方法。     

基于粗糙集的决策树旅游景点信用评估模型的设计与实现

旅游景点信用评估是一种典型的分类问题,本文概述了粗糙集和决策树的理论,基于这两种理论,提出了一个基于数据挖掘粗糙集理论与决策树分类技术相结合的信用评估方法来建立旅行景点的信用评估模型,利用粗糙集的知识约简的概念,对样本数据进行预处理,去除冗余属性对分类模型的影响,然后用决策树方法建立分类模型.最后通过Pawlak重要度的属性约简算法和ID3决策树算法实现了该模型.     

高阶统计安全的隐写算法

近年来利用载体高阶统计特征进行隐写分析的各种算法大量出现,对隐写算法的存在安全性能构成了较大挑战.鉴于此,隐写研究者开始着眼于研究高阶统计安全的各种隐写算法.文章对目前二阶统计安全的隐写算法的研究成果进行了综述,并实验说明典型算法的效果.进而提出更高阶统计安全隐写算法的研究思路.     

改进的粗糙集方法与稀土产业可持续发展评价

针对稀土产业可持续发展,提出了一种新的评价模型。该模型的不同在于首先采用模糊C均值聚类算法对数据进行预处理,然后再基于粗糙集的属性约简以及属性重要度思想,做出改进,对现有指标进行精简并确定约简后各指标的权重,从而形成综合测评。最后还通过包头市高新区的稀土产业进行了实证研究,说明了该评估模型优于现有评价方法避免了主观性,同时相比原始粗糙集方法,进一步简化了评估过程,提高了工作效率,具有一定的理论意义与实践意义。     

粗糙集在房地产项目投资决策中的应用

房地产项目投资决策的成败直接关系到房地产企业的未来发展,如何在多方案中选择综合效益最好的方案是决策者关心的问题。本文利用粗糙集理论中的知识约简算法对影响房地产项目决策的指标进行约简,提取影响项目评价的主要指标,然利用熵权模型对约简后的指标体系进行赋权,对各方案进行综合评价。     

基于粗糙集的客户细分研究

粗糙集理论正被广泛运用于不确定环境下的信息处理中。当要从大量复杂的数据中发现知识时,属性约简和规则约简是两个关键问题。本文运用了基于可辨识矩阵的属性约简与值约简算法在简化信息系统后,提取最简决策规则,并结合客户细分的实例来说明该算法的有效性。     

基于粗糙集理论的电子商务消费行为预测研究

为了解决传统电子商务知识获取瓶颈问题,本文提出了一种改进的基于差别矩阵的属性约简算法,将其应用于电子商务消费行为预测条件属性集约简中,并对产生的规则进行提取和约简,得到了一种新的基于粗糙集理论的电子商务消费行为预测方法。算例表明该方法预测效果良好。     

离散周期Wigner-Hough变换及其检测性能分析

分析了周期Wigner-Hough变换(PWHT)进行离散化计算时,对线性调频连续波（LFMCW）信号 的检测性能 。通过推导高斯白噪声中LFMCW信号经离散化PWHT后信噪比处理增益表达式,分析了离散PWH T的弱信号检测性能。通过推导离散PWHT较离散Wigner-Hough变换(WHT)的检测性能优势表 达式,比较了离散PWHT与离散WHT算法的检测性能。仿真实验验证了离散PWHT的信噪 比处理增益具有准相干积累的效果,PWHT较WHT更优的检测性能。     

面向用户的最佳属性约简算法在客户分类中的应用

本文研究了基于粗集理论的面向用户的最佳约简算法应用于客户关系管理的方法,通过建立客户价值决策表、属性的最佳约简和规则提取,实现了对客户关系的最佳管理。     

基于图形链的冗余多指标集比较删余缩减算法

在指标权重及冗余指标检测的基 础上,采用链状结构对相关指标集合进行图形描述,提出了基于图形链的冗余指标比 较缩减算法。该方法进一步考虑了指标冗余的非传递性,并有效发挥了指标权重在综合评价 中的作用。实验结果表明,该方法可显著改善删余评价方法的公正性,避免了评价指标的过 度 删余,对有效完成评价指标的鉴别与客观筛选有着重要意义。     

基于灰色关联算法的雷达反隐身性能评估

雷达反隐身的性能评估对现代空防战争具有重要意义。在深入分析雷达反隐身技术及相关基础理论基础上建立了雷达反隐身性能指标体系,提出了采用基于自适应熵权的灰色关联算法来进行雷达反隐身性能评估,解决了评价权重模糊问题,并结合经典最小二乘法和拉格朗日函数建立了优化评估模型,最后通过算例分析给出了该算法模型的应用过程,分析结果表明该算法能有效实现对雷达反隐身性能的排序和优选。     

The influence of thematic product displays on consumers: An elaboration‐based account

Marketers commonly adopt a theme to unify their design of an environment in which their products are displayed. A thematic display environment can be congruent with or unrelated to the concept of a product on display. The elaboration likelihood model and the knowledge activation literature suggest that conceptual congruence between the thematic display context and the product could affect product evaluation by a cue‐based mechanism and an elaboration‐based mechanism. First, the positive feeling associated with conceptual congruence serves as a peripheral cue, making product evaluation favorable. Second, the congruence provokes thoughts about the product's attributes, and these attribute‐related thoughts affect product evaluation. Whether the evaluation is dominated by the affective cue or attribute thoughts depends on the consumer's shopping motivation (planned purchase vs. browsing), because the motivation affects the consumer's elaboration likelihood. The results of three experiments support these propositions. The results indicated that under planned purchase motivation, the congruence effect on purchase intention through attribute‐related thoughts was observed. In contrast, under browsing, the congruence effect on purchase intention was dominated by a direct positive effect that reflected the influence of the affective cue. Implications of the findings for visual merchandising are discussed.     

The effects of online shopping attributes on satisfaction–purchase intention link: a longitudinal study

Attributes of online satisfaction are dynamic. Specifically, it remains to be examined how online shopping attributes empirically affect changes in satisfaction that leads to repurchase behaviours over time and why. The present study develops a theoretical framework for conceptualizing satisfaction with temporal effects and empirically tests it using longitudinal data from 219 online customers. The results indicate that the relationship between attribute‐level evaluations and satisfaction, which has only been examined in terms of predictors of satisfaction in prior literature, is dynamic and changes over time. Changed attributes (particularly convenience and site design) might signal an opportunity to capture the dynamics of attribute‐level evaluations over time. Furthermore, the findings reveal significant temporal effects of satisfaction and purchase intention at time point T on satisfaction and purchase intention at time point T + 1. The results suggest that temporal effects occur as a diagnostic function of a previous attribute rating of a subsequent satisfaction evaluation and the consumer's level of subjective knowledge.     

一种考虑稳定性的动态综合评价新模型

针对动态综合评价需要考虑被评对象的稳定性问题,提出了一种综合考虑指标权重、时间权 重和稳定性的动态综合评价模型。定义了稳定因子来表征被评对象指标的稳定程度,采用离 差最大化的方法确定指标权重,提出了一种基于极小范数时间权重确定方法。将所提模型应 用于军事IP网络评价,结果表明该模型能够把被评对象的稳定性反映到评价结果中。     

Search for the underlying mechanism of framing effects in multi-alternative and multi-attribute decision situations

This paper extends previous research on the framing effect from single-alternative and single-attribute to multi-alternative and multi-attribute situations. Two experimental studies demonstrate that attribute framing and goal framing influence consumer decision-making in multi-attribute and multi-alternative situations. The results indicate that attribute framing influences only the perceived evaluation of the specific alternatives along a framed attribute, in that the perceived evaluation of the framed attribute is higher in the positive attribute framing condition than in the negative. On the other hand, goal framing influences only the weight of a framed attribute. Specifically, the weight of the framed attribute becomes more important in the positive goal framing condition than in the negative. Further, the results suggest that the attribute framing effects are attributable to the changes in mental representation in the encoding stage of the decision, rather than in the judgment stage.     

基于多源数据融合技术的情报侦察系统效能评估体系

多源数据融合技术因具有多类数据源,可多层次、全方位感知信息,已被广泛应用于 军事领域。但目前缺少一个统一的评价体系,用于指导和规范多源数据融合情报侦察系统的 效能评估。为了全面评价和比对多源信息融合情报侦察系统各方面的性能,在分析相关理论 的基础上,建立了一个合理的且相对全面的评价指标体系,覆盖了多源数据融合情报侦 察系统各方面的属性,并分析了评价体系与指标体系之间的关系。该项研究丰富了多源数据 融合效能评估理论和方法,可用于指导和规范多源数据融合情报侦察系统的效能评估工作, 并有效地提高了系统的综合作战能力。     

When and why attribute sorting affects attribute weights in decision-making

Information about alternatives often appears in a multi-option multi-attribute table, with the alternatives hierarchically sorted on attribute levels. This research shows that the choice of the primary sorting attribute can affect peoples' evaluations. Three studies show that the attribute on which options are primarily sorted becomes more important in preference formation, but only if this attribute is hard to evaluate. This sorting effect disappears if attribute level evaluation is rendered easier. Eye-movement data further show that the time to evaluate a given attribute level, a proxy for evaluation effort, mediates the effect of choice of sorting attribute on attribute weight in option evaluation.     

The existence and perception of redundancy in consumer information environments

Two studies are reported which examine the existence of attribute redundancy as well as consumers' ability to perceive attribute redundancy in consumer information environments. The results of the first study suggest that attribute redundancy varies widely from product category to product category. The results of the second study suggest that consumers' ability to perceive attribute relationships improves with product knowledge. Unexpected was an observed U-shaped relationship between consumers' perceptions of attribute redundancy and attribute knowledge. Together the results suggest a number of policy implications regarding the value of consumer information programs.     

A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring

Data mining techniques have numerous applications in credit scoring of customers in the banking field. One of the most popular data mining techniques is the classification method. Previous researches have demonstrated that using the feature selection (FS) algorithms and ensemble classifiers can improve the banks' performance in credit scoring problems. In this domain, the main issue is the simultaneous and the hybrid utilization of several FS and ensemble learning classification algorithms with respect to their parameters setting, in order to achieve a higher performance in the proposed model. As a result, the present paper has developed a hybrid data mining model of feature selection and ensemble learning classification algorithms on the basis of three stages. The first stage, as expected, deals with the data gathering and pre-processing. In the second stage, four FS algorithms are employed, including principal component analysis (PCA), genetic algorithm (GA), information gain ratio, and relief attribute evaluation function. In here, parameters setting of FS methods is based on the classification accuracy resulted from the implementation of the support vector machine (SVM) classification algorithm. After choosing the appropriate model for each selected feature, they are applied to the base and ensemble classification algorithms. In this stage, the best FS algorithm with its parameters setting is indicated for the modeling stage of the proposed model. In the third stage, the classification algorithms are employed for the dataset prepared from each FS algorithm. The results exhibited that in the second stage, PCA algorithm is the best FS algorithm. In the third stage, the classification results showed that the artificial neural network (ANN) adaptive boosting (AdaBoost) method has higher classification accuracy. Ultimately, the paper verified and proposed the hybrid model as an operative and strong model for performing credit scoring.     

改进AHM-CRITIC赋权的雷达装备保障性灰色综合评估

针对雷达装备保障性评估指标的不确定性与多层次性问题，在梳理整合雷达装备保障性评估内容构成要素的基础上，构建了雷达装备保障性评估指标体系，改进了标准间冲突性相关性（Criteria Importance Through Intercriteria Correlation,CRITIC）赋权法，结合属性层次模型（Attribute Hierarchy Model,AHM），提出了AHM-CRITIC综合赋权法，设计了基于改进AHM-CRITIC赋权的雷达装备保障性灰色综合评估模型及算法，通过实例验证了该方法的合理性和有效性。