基于改进的DTW算法的仿真与分析   总被引：2，自引：0，他引：2  

崔光照  吴晓平  路康 《福建工程学院学报》2004,2(2):149-151,175

传统的DTW算法着重于时间规整和间距测量的概念，对数据的可靠性没有进行有效的分析，且对连续词的识别效果不明显。基于松弛起始点和分段思想的改进DTW算法，可以改善明阿算法的缺陷。通过对语音样本0．9在MATLAB6．5上的仿真实现与分析表明，采用改进后的DTW算法具有良好的语音识别效果。  相似文献   

Unsupervised word sense disambiguation for Korean through the acyclic weighted digraph using corpus and dictionary     

Yeohoon Yoon  Choong-Nyoung Seon  Songwook Lee  Jungyun Seo 《Information processing & management》2006

Word sense disambiguation (WSD) is meant to assign the most appropriate sense to a polysemous word according to its context. We present a method for automatic WSD using only two resources: a raw text corpus and a machine-readable dictionary (MRD). The system learns the similarity matrix between word pairs from the unlabeled corpus, and it uses the vector representations of sense definitions from MRD, which are derived based on the similarity matrix. In order to disambiguate all occurrences of polysemous words in a sentence, the system separately constructs the acyclic weighted digraph (AWD) for every occurrence of polysemous words in a sentence. The AWD is structured based on consideration of the senses of context words which occur with a target word in a sentence. After building the AWD per each polysemous word, we can search the optimal path of the AWD using the Viterbi algorithm. We assign the most appropriate sense to the target word in sentences with the sense on the optimal path in the AWD. By experiments, our system shows 76.4% accuracy for the semantically ambiguous Korean words.  相似文献   

购并目标公司预测模型实证研究   总被引：3，自引：0，他引：3  

苟开红  谷伟 《预测》2003,22(5):49-52,65

本文以我国2001年公司购并活动为研究对象，选取75家上市公司为样本，利用Logistic回归建立预测模型，对目标公司的回判准确率为77．33％。文章发现，非完全市场化的上市制度和过小的市场容量是导致目标公司质量低下的主要原因，上市公司控制权的出售仍然是为处置不良资产，还没有被看作整合内外资源、提高核心竞争力的手段。本文的研究支持A股市场半强式有效假说。  相似文献   

北魏“手铸金人”制试探     

苗霖霖 《哈尔滨学院学报》2011,32(11):109-112

＂手铸金人＂是北魏王朝对国家大事进行预测的一种方式,皇帝将铸金人的成败视为事件吉凶的预兆。最初该方式只用于对皇后选立的预测,北魏后期,这项制度走出了后宫,成为鲜卑贵族对皇位继承进行预测的一种重要方式。  相似文献   

基于PSO和多元线性回归的奥运会奖牌预测分析     

秦瑞瑞 《实验室研究与探索》2011,(10)

针对传统奥运会成绩预测模型中存在的不足,提出一种将PSO和多元线性回归分析相结合的预测模型。分析多元线性回归和PSO算法后,结合体育比赛的特点,通过PSO优化迭代计算,确定奖牌统计模型中各回归系数,建立了奥运会参赛国成绩与回归系数之间复杂的非线性关系。利用Matlab对建立奖牌模型进行了验证,预测精度高。  相似文献   

基于随机游走增强型矩阵分解的混合服务预测     

林坚  李俊 《教育技术导刊》2019,18(12):82-88

随着Web服务数量的急剧增长,如何在大量功能相似但非功能属性各异的服务中选择满足用户个性化需求的服务是亟需解决的问题。基于QoS（Quality of Service）预测的服务推荐方法成为研究热点。然而, QoS数据的稀疏性和“冷启动”问题阻碍其发展。针对当前主流的QoS预测模型预测精度不高和收敛速度较慢等问题,提出一种基于随机游走模型和矩阵分解技术的混合QoS预测方法。该方法首先基于矩阵分解获得用户及服务的潜因子矩阵,并将用户潜因子矩阵转化为用户相似度矩阵;然后基于用户相似度矩阵并结合Web服务的网络位置信息,使用随机游走模型提高用户相似度矩阵的准确性;最终结合协同过滤方法与矩阵分解模型进行QoS预测。在真实数据集上实验,结果表明,与当前主流的QoS预测方法相比,该方法具有更高的预测精度和效率。  相似文献   

基于灰色模糊理论的河南省城镇居民收入结构关系及预测研究     

张艳清 《南阳师范学院学报》2011,10(6):14-17

城镇居民收入是衡量一个国家或地区经济竞争力的一个重要标准,如何提高居民收入是提高经济实力的重要方面.通过基于灰色理论方法的计算得来的河南省居民收入结构关联度显示：居民工薪收入和转移性收入是影响居民可支配收入的主导因素,所以要提高居民收入就主要从这两个方面着手.最后利用EXCEL表格通过编程预测出了2009～2013年河南省可支配收入和转移性收入的情况,数据显示：参差〈0.35,精度〉0.8,预测合格.  相似文献   

基于局部信息相似性的学科引证知识扩散动态链路预测研究     

岳增慧  许海云  王倩飞 《情报理论与实践》2020,43(2):84-91,99

在知识经济时代,学科知识的传播与扩散促进了学科的协同、交叉、融合、发展与创新。文章利用复杂网络算法对学科引证知识扩散时序演化网络进行动态链路预测分析,以期探索学科知识流动结构变化及演进态势,为学科知识管理及决策制定提供可资借鉴的理论和实践参考。文章以学科引证知识扩散时序演化网络结构信息为基础,采用10项基于局部信息的相似性指标分别对无权和加权知识扩散网络进行动态链路预测分析,并将各指标的预测性能进行了对比。最后,利用无权RA指标和加权AA指标对学科引证知识扩散态势进行了预测。研究表明:不同指标的预测精度在不同的时间段内会动态变化;在学科引证知识扩散网络中,存在一定程度的弱连接效应;不同链路预测指标在无权和加权学科引证知识扩散网络中的适用性存在一定差异。  相似文献   

Predicting future dynamics from short-term time series using an Anticipated Learning Machine     

Chuan Chen  Rui Li  Lin Shu  Zhiyu He  Jining Wang  Chengming Zhang  Huanfei Ma  Kazuyuki Aihara  Luonan Chen 《国家科学评论(英文版)》2020,7(6):1079

Predicting time series has significant practical applications over different disciplines. Here, we propose an Anticipated Learning Machine (ALM) to achieve precise future-state predictions based on short-term but high-dimensional data. From non-linear dynamical systems theory, we show that ALM can transform recent correlation/spatial information of high-dimensional variables into future dynamical/temporal information of any target variable, thereby overcoming the small-sample problem and achieving multistep-ahead predictions. Since the training samples generated from high-dimensional data also include information of the unknown future values of the target variable, it is called anticipated learning. Extensive experiments on real-world data demonstrate significantly superior performances of ALM over all of the existing 12 methods. In contrast to traditional statistics-based machine learning, ALM is based on non-linear dynamics, thus opening a new way for dynamics-based machine learning.  相似文献   

Low-achieving (learning disabled) pupils in year 2 of the primary school in Hungary     

Marta Zsoldos 《欧洲特需教育杂志》2013,28(2):243-250

We selected 60 low-achieving children from a sample of 263 pupils in Year 2 of the primary school in order to analyse the problems of learning disabilities. We explored two questions: whether teachers evaluate the pupils' school performances correctly; and what kind of relationship exists between the low-achieving pupils' cognitive abilities and their school performance. Methods used were questionnaires, pedagogical tests and traditional psychological tests. We obtained the following results: the teachers generally evaluate the pupils' school performance fairly well, but they are inclined to assume a close correlation between the achievements in different subjects, and the teachers' knowledge of the low-achieving children is more reliable regarding the group of pupils as a whole rather than each pupil individually; and the low-achieving pupils' cognitive learning abilities prove to be significantly weaker than their general intellectual abilities.  相似文献