属性和专家客观权重未知的区间数群决策方法

针对偏好信息为区间数形式、属性和专家客观权重未知的多属性群决策问题,提出通过属性评价值之间偏离程度的熵值分析和建立目标最小化的非线性规划模型确定属性客观权重,并结合属性主观权重获得属性综合权重;通过灰色关联法分析专家综合评价和群体综合评价之间一致性程度确定专家客观权重,并利用自适应迭代法求得稳定的专家权重;构造了一个新的区间数比较的可能度公式,并基于此公式,给出了方案排序问题的解决方法。通过算例分析及与其他方法对比,验证了所提出方法的可行性和有效性。最后,分析了相关参数对决策结果的影响。     

基于改进遗传模拟退火 K-means的心电波形的分类研究

针对心电图自动诊断困难这一问题,提出了一种新的聚类算法：基于均方差属性加权的遗传模拟退火K-means改进聚类算法,用于改进心电图（ECG）信号的自动识别技术。利用小波变换的多分辨率和抗干扰能力好的特点,检测QRS波、P波、T波,提高了特征检测的准确性;利用聚类分析具有较好的鲁棒性和适合于大数据量分析的特点,对心电信号进行波形分类。采用MIT-BIH标准心电数据库中的部分数据对识别结果进行判断,改进后的K-means聚类算法的准确率高于传统的K-means聚类算法,实验表明该算法对心电信号可以进行有效分类。     

三次有理Bézier曲线的形状调整方法

给出了两类调整三次有理Bézier曲线形状的方法。一类方法是使曲线通过给定的插值点,从而实现曲线的形状调整。另一类方法是将曲线上的点作为控制多边形两边连线段上的分点,通过调整分线段的比例,实现对曲线的形状调整。针对不同情况,分别给出了权因子的计算公式。计算方法简单,使用方便,并使三次有理Bézier曲线的形状调整更加具体和明确。同时,由计算结果得到了任意三次有理Bézier曲线不相交的充分必要条件。     

Score normalization in multimodal biometric systems

Multimodal biometric systems consolidate the evidence presented by multiple biometric sources and typically provide better recognition performance compared to systems based on a single biometric modality. Although information fusion in a multimodal system can be performed at various levels, integration at the matching score level is the most common approach due to the ease in accessing and combining the scores generated by different matchers. Since the matching scores output by the various modalities are heterogeneous, score normalization is needed to transform these scores into a common domain, prior to combining them. In this paper, we have studied the performance of different normalization techniques and fusion rules in the context of a multimodal biometric system based on the face, fingerprint and hand-geometry traits of a user. Experiments conducted on a database of 100 users indicate that the application of min–max, z-score, and tanh normalization schemes followed by a simple sum of scores fusion method results in better recognition performance compared to other methods. However, experiments also reveal that the min–max and z-score normalization techniques are sensitive to outliers in the data, highlighting the need for a robust and efficient normalization procedure like the tanh normalization. It was also observed that multimodal systems utilizing user-specific weights perform better compared to systems that assign the same set of weights to the multiple biometric traits of all users.     

Internet网络新闻文本自动摘要的研究

给出了Internet网络新闻中文文本自动摘要的基本思路和基本步骤,讨论了断句、分词算法.针对自动摘要中新闻文本的4种形式特征,提出了一套新的自动摘要方案:首先综合新闻文本的4种形式特征对词汇和句子赋予不同的权值,然后根据权值大小按给定的比例挑选句子,并进行平滑处理,生成文字流畅且具备一定质量的摘要.最后实验分析表明效果较好.     

Choosing OWA operator weights in the field of Social Choice

One of the most important issues in the theory of OWA operators is the determination of associated weights. This matter is essential in order to use the best-suited OWA operator in each aggregation process. Given that some aggregation processes can be seen as extensions of majority rules to the field of gradual preferences, it is possible to determine the OWA operator weights by taking into account the class of majority rule that we want to obtain when individuals do not grade their pairwise preferences. However, a difficulty with this approach is that the same majority rule can be obtained through a wide variety of OWA operators. For this reason, a model for selecting the best-suited OWA operators is proposed in this paper.     

Weighted dynamic time warping for time series classification

Dynamic time warping (DTW), which finds the minimum path by providing non-linear alignments between two time series, has been widely used as a distance measure for time series classification and clustering. However, DTW does not account for the relative importance regarding the phase difference between a reference point and a testing point. This may lead to misclassification especially in applications where the shape similarity between two sequences is a major consideration for an accurate recognition. Therefore, we propose a novel distance measure, called a weighted DTW (WDTW), which is a penalty-based DTW. Our approach penalizes points with higher phase difference between a reference point and a testing point in order to prevent minimum distance distortion caused by outliers. The rationale underlying the proposed distance measure is demonstrated with some illustrative examples. A new weight function, called the modified logistic weight function (MLWF), is also proposed to systematically assign weights as a function of the phase difference between a reference point and a testing point. By applying different weights to adjacent points, the proposed algorithm can enhance the detection of similarity between two time series. We show that some popular distance measures such as DTW and Euclidean distance are special cases of our proposed WDTW measure. We extend the proposed idea to other variants of DTW such as derivative dynamic time warping (DDTW) and propose the weighted version of DDTW. We have compared the performances of our proposed procedures with other popular approaches using public data sets available through the UCR Time Series Data Mining Archive for both time series classification and clustering problems. The experimental results indicate that the proposed approaches can achieve improved accuracy for time series classification and clustering problems.     

带权定性影响图

定性影响图是具有精确概率和效用的影响图的定性抽象。在定性影响图中,节点之间的影响关系使用定性符号描述,这种符号描述简化了不确定知识的表示,降低了影响图建模的难度,加速了不确定知识的推理。但是,定性影响图在抽象过程中损失了部分信息,导致定性影响图在评价过程中会产生不确定结果,阻碍了定性影响图的广泛应用。以加权的思想扩展定性影响图,使扩展的定性影响图中每个定性影响都带有一个表示节点间影响强弱的数值权值,在评价过程中根据定性影响权值的比较来减少不确定结果的产生,从而扩大定性影响图的应用范围。     

计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

混合分布估计算法求解考虑同步性和准时性的三阶段装配集成调度问题

本文研究以加工–运输–装配同步性和交货准时性的加权和为优化目标的三阶段装配集成调度问题(3sAISP_SP),并基于问题特点设计混合分布估计算法(HEDA)进行求解.首先,分别建立3sAISP SP的数学规划模型和排列模型.其次,在对问题模型特点分析的基础上,设计合理的编码和解码规则,同时利用HEDA中基于概率模型的全局搜索以发现问题解空间存在优质解的区域.然后,为进一步提高算法性能,设计3种局部搜索策略对优质解区域进行细致搜索.进而,在小规模问题下,将HEDA得到的较优解与优化求解器GUROBI得到的最优解进行比较,验证HEDA的求解结果接近最优解;在较大规模问题下,将HEDA与其他有效智能优化算法进行比较,验证HEDA的求解性能.最后,通过对优化目标中不同权重设置的实验分析,给出加工–运输–装配同步性和交货准时性权重设置的合理范围,并得到考虑装配同步性有利于降低中间库存的结论.