粗糙集理论和遗传算法在预防城市道路交通拥堵中的应用

建立了反映道路拥堵原因与道路拥堵类型之间的关系决策表,利用粗糙集理论和遗传算法相结合的属性约简方法,去除决策表中冗余的规则,从而找到了造成道路交通拥堵的主要因素.试验结果表明,此算法可高效分析交通拥堵原因,为预防城市道路交通拥堵提供科学的决策依据.     

基于粗糙集理论属性重要性的离散化算法

本文主要研究了粗糙集理论在决策表离散化中的应用,提出了一种基于粗糙集理论属性重要性的决策表离散化算法。该算法首先使用依赖度来定义属性的重要性,并据此对条件属性按照重要性由小到大排序,然后按排序后的顺序,考察每个条件属性的所有断点,将冗余的断点去掉,从而将条件属性离散化。     

组合预测误差的原因分析

首次提出信息量、独有信息量、公有信息量的概念及其计算方法。通过对各单项预测方法的权重与其独有信息量的比较，分析了导致组合预测误差的各种原因。     

基于并行计算的模糊粗糙集属性约简

启发式方法是模糊粗糙集属性约简的有效手段之一,大多基于贪心策略的启发式方法以串行方式运行,这限制了属性约简的规模。为了解决该问题,提出一种基于并行计算的模糊粗糙集属性约简算法,该算法通过调用多个处理器来协同寻找对分类任务最具影响的最小属性子集,从而扩大了可约简数据的规模。在10组UCI数据集上的实验结果表明,基于并行计算的模糊粗糙集属性约简方法相比传统的启发式属性约简方法而言,在时间开销上能有很大程度的缩减。     

基于粗糙集理论的评价指标属性约简

粗糙集理论是一种对数据进行约简的有效工具。文章运用粗糙集理论对评价指标进行了属性约简,并根据各指标包含信息量的大小确定权重,构建了基于粗糙集理论的指标综合评价模型。     

一种新的面向对象概念格属性约简方法

为了研究概念格的属性约简方法，提出了面向对象概念格的可简化属性和不可简化属性，并研究相关性质。给出了面向对象概念格知识约简的判定定理，及相应的面向对象概念格约简方法。本文提出的属性约简方法，不用建立在差别矩阵上面，便可得到形式背景的约简集。     

启发式属性约简研究与算法设计

基于Rough Set理论的属性约简,提出分2步求得属性约简的新算法:第1步利用二进制辨识矩阵计算出属性约简集;第2步利用可辨识矩阵以及属性的重要性启发地求属性约简,并检查此约简是否属于第1步求出的约简集,以确定此约简是否为较佳的属性约简.理论分析和实验表明,该算法是一种直观、有效的属性约简算法.     

一种基于SQL的用户自定义精度的粗糙集属性约简算法

将数据库的关系运算运用于粗糙集的属性约简,引入用户自定义精度,改进基于SQL的属性约简算法。仿真实验结果表明,该方法与经典粗糙集相关方法相比,有更高的执行效率和抗噪性,为粗糙集理论更广泛地应用于海量数据的数据挖掘提供了一种方法。     

基于粗糙集理论和系统信息覆盖率最大化原则的白酒香型识别

以低分子有机酸、酯作为条件属性,白酒香型作为决策属性建立了一个知识评判系统,利用粗糙集理论方法讨论了低分子有机酸、酯在白酒各类香型中的重要性,并采用基于属性重要性的约简算法对系统进行了属性简化。结合信息覆盖率最大的原则,选择了一组最佳的简化方案,通过规则约简从而得到了白酒香型的最小决策算法,确定了低分子有机酸酯的含量与各类白酒香型的关系,只需提供较少的属性值就能判别出白酒的香型。     

粗糙集与软集合在临床诊断中约简及决策分析

总结了医学领域中用粗糙集进行属性约简的算法，并且进一步修正了运用可辩识矩阵的属性约简算法．另外，利用软集合知识进一步简化了多目标决策的过程．     

强协调决策形式背景的概念格属性约简

运用概念的闭标记研究了强协调决策形式背景的核心属性问题。通过概念的闭标记得到了判定强协调决策形式背景的协调集的方法,并且定义了计算约简集的函数,从而得到了约简集,最后通过简单的集合运算得出协调决策形式背景的核心属性。     

定量型多指标决策的层次分析法探讨

采用等级标度与层次分析相结合的方法对定量型多指标决策问题进行讨论，提出了一种按等级标度构造排序指数及其修正，并进一步构造判断矩阵的方法．它既是层次分析法在定量型多指标决策中的合理推广，同时也为定量型多指标决策问题提供了一种行之有效的方法．     

Consumer acceptance measurement focusing on a specified sensory attribute of products: Can the attribute-specified degree of satisfaction-difference (DOSD) method replace hedonic scaling?

A specific attribute can play an important role in determining consumers’ perceived quality and acceptance of a product. Kim, van Hout, Dessirier, and Lee (2018) proposed a new affective method, the degree of satisfaction-difference (DOSD) method, to study consumer acceptance in terms of overall satisfaction with products. In the present study, this DOSD method was further developed to assess satisfaction for a specified attribute of products rather than overall satisfaction, and this modification is referred to as the attribute-specified DOSD method. To test its applicability, 11 bouillon products (including a reference product) varying in viscosity were used as stimuli. Satisfaction with the perceived mouthfeel thickness, which is a viscosity-related sensory attribute, was evaluated with the attribute-specified DOSD method and with a 10-point category scale for overall liking as the control method. Two groups of consumers performed either the attribute-specified DOSD method or hedonic scaling over two repeated sessions. Results showed that the satisfaction patterns of the attribute-specified DOSD method were similar to those of the hedonic scaling across products, confirming that the mouthfeel thickness was a determinant of consumer acceptance for bouillon products. Examining the test reliability in terms of consistency of consumers’ responses for the same stimulus in different sessions, both groups showed consistent results. The subjects who performed the attribute-specified DOSD method were also segmented based on the degree of satisfaction with the reference product. Here, each consumer sensory segment showed different patterns on satisfaction with other test products. These findings demonstrate the potential of the attribute-specified DOSD method for measuring the consumer responses to the level/quality of an important attribute/dimension and highlight its usefulness for consumer sensory segmentation.     

一个连续型不确定集结算子及其在多属性决策中的应用

将连续区间有序加权平均（C-OWA）算子与广义平均算子相结合,提出了一个连续型不确定的集结算子,广义连续区间数据有序加权平均（GC-OWA）算子.给出了基于此算子的不确定多属性决策方法,最后的实例说明方法的有效性和合理性.     

What does it mean to check-all-that-apply? Four case studies with beverages

The use of check-all-that-apply (CATA) questions in product-focused consumer research on foods and beverages is now common, and the method is known to provide valid sensory product characterisations. Extensive methodological research has been conducted and has supported uptake, but understanding of how consumers complete CATA questions is incomplete, particularly with regard to their decision to select or not a term to describe the sensory properties of products. The present research was situated within this gap, and using open-ended questions participants (n = 636) were asked to describe how they perceived a pair of samples with regard to an attribute and link this to CATA term selection. The results, obtained for taste (‘sweet’ and ‘sour/acidic’) and flavour (‘cinnamon’ and ‘smoky’) confirmed consumers’ ability to accurately perform sensory characterisation tasks. In particular, it was found that: i) the great majority of the consumers accurately used the CATA terms for describing the sensory characteristics they perceived in a sample, ii) when a term was not selected for describing samples, the majority of the consumers indicated that the corresponding sensory attribute was not perceived, iii) when a term was selected for describing only one of the samples in a pair, consumers reported to have perceived a difference in attribute intensity between the samples. Thus, CATA questions remain a desirable option for sensory product characterisation tasks with consumers, but should be selected with thought as they may not always be able to achieve desired sample discrimination due to the binary nature of the responses.     

基于属性识别模型的包装经济性成本研究

探讨了包装经济性评价内容,给出了其多层次评价指标体系,并利用属性数学理论建立了包装经济性评价的属性识别模型。通过运用实例说明属性识别模型在实际应用中具有有效性和可操作性。     

Application of portfolio theory in decision tree analysis

A general application of portfolio analysis for herd decision tree analysis is described. In the herd environment, this methodology offers a means of employing population-based decision strategies that can help the producer control economic variation in expected return from a given set of decision options. An economic decision tree model regarding the use of prostaglandin in dairy cows with undetected estrus was used to determine the expected return of the decisions to use prostaglandin and breed on a timed basis, use prostaglandin and then breed on sign of estrus, or breed on signs of estrus. The risk attributes of these decision alternatives were calculated from the decision tree, and portfolio theory was used to find the efficient decision combinations (portfolios with the highest return for a given variance). The resulting combinations of decisions could be used to control return variation.     

用于织机评判的灰色关联决策

借助灰色关联决策理论,对几种新型织机的性能作出了评价.结果表明,对于白坯织物生产,喷气织机是最好的选择.这种方法对设备的造型和工艺的优化非常有用.     

黄瓜贮藏中微生物信息三维荧光判别及其数量监控模型构建

为实现黄瓜贮藏过程中基于微生物内源荧光信息的微生物数量变化情况的快速实时监控,并为腐败预判提供依据,在不同贮藏时间对黄瓜表面进行三维荧光信息采集。运用多项式插值方法去除原始光谱中的瑞利散射,并进行Savitzky-Golay多项式平滑降噪处理。采用核心一致诊断（core consistency diagnostic,CORCONDIA）法对组件数进行估计,以避免黄瓜在贮藏过程中表面微生物自身的代谢作用对样本荧光信号的分析造成干扰。运用交替三线性分解（alternating trilinear decomposition,ATLD）算法,按该组件数对三维荧光矩阵进行分解,获得不同组件的相对激发强度光谱、相对发射强度光谱和相对浓度阵。解析结果表明：通过CORCONDIA法在函数值大于60%的前提下,确定组件数为4。以ATLD算法分解出的4 个组件中,组件1和组件3呈现特殊双峰结构,其特征激发-发射光谱与微生物主要内源荧光物质,即类色氨酸和类酪氨酸的荧光指纹图谱吻合,且组件1所代表的类色氨酸具有较高的荧光量子产率。运用荧光区域积分法对组件1的特征光谱中高激发类色氨酸和低激发类色氨酸区域的荧光总量进行定量分析,并用多元逐步回归方法构建了标准化区域积分值与微生物数量间的函数关系。回归分析结果显示,采用二元四次逐步回归方法构建的回归模型决定系数R2可达98.309 8%。采用1 个未参与模型建立的样本对预测模型进行检测,获得微生物数量的相对误差为1.037 1%。结论：在对黄瓜表面荧光光谱中微生物信息判别的基础上,可以实现黄瓜贮藏过程中基于微生物三维荧光信息的微生物数量变化监控模型的构建,为实时监控腐败进程提供依据。