灰色预测法在情报研究中的应用研究综述     

张晶晶  李泽霞 《图书情报工作》2021,64(24):106-114

[目的/意义] 灰色预测法可有效处理情报研究中广泛存在的小样本数据，通过对灰色预测法在情报研究中的应用情况进行梳理，总结其在应用过程中存在的不足，为灰色预测法在情报研究中的进一步应用提供参考。[方法/过程] 通过综述情报研究中涉及灰色预测法的相关文献，从数据选取、模型构建和解决的问题等方面对情报研究中灰色预测法的应用进行概述，总结当前情报研究中灰色预测法的应用所存在的问题，并提出改进建议。[结果/结论] 在方法应用上，已有研究主要采用数列灰预测，且模型集中在单变量灰色预测模型，根据预测对象不同，灰色预测法已经在包括期刊分析、图书馆运行管理、热点主题分析及科研机构评价方面得到了很好的应用，未来可根据预测对象特点及研究目标尝试不同的灰色预测方法，扩宽灰色预测法在其他方面的情报研究问题中的应用。  相似文献   

身体关怀:徐英超体质教育思想的形成动因、内在逻辑与当代启示     

邵天逸  李启迪 《沈阳体育学院学报》2020,(3):23-28

徐英超是"体质教育思想"的首创者,这一思想在我国学校体育发展史中具有重要的地位。运用文献资料法、逻辑分析法,通过不同的视角深度剖析徐英超体质教育思想,旨在呈现徐英超体质教育思想的形成动因与内在逻辑,并挖掘体质教育思想对当前学校体育的启示。研究认为徐英超体质教育思想的成因在于反思体育的概念,内在逻辑包含3个方面:体育教学的视点应从技术传习回归身体教育,实证调研是揭示与掌握体质变化规律的关键,良好的心态与生活方式是促进体质健康的外部保障。徐英超体质教育思想的当代启示:正视增强体质与技术教学之关系;参考体测结果调整体育教学方向;建构面向生活的体育健康教育观。  相似文献   

Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws     

Edgardo Ferretti  Leticia Cagnina  Viviana Paiz  Sebastián Delle Donne  Rodrigo Zacagnini  Marcelo Errecalde 《Information processing & management》2018,54(6):1169-1181

In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.  相似文献   

基于DE-SVM的船舶航迹预测模型     

刘娇  史国友  杨学钱  朱凯歌 《上海海事大学学报》2020,41(1):34-39

为提高船舶航迹预测精度,解决准确建模难度大和神经网络易陷入局部最优的问题,考虑实时获取目标船AIS数据较少的特点,提出一种基于支持向量机(support vector machine,SVM)的航迹预测模型。选择AIS数据中的航速、航向和船舶经纬度作为样本特征变量;采用小波阈值去噪的方法处理训练数据;采用差分进化(differential evolution,DE)算法对模型内部参数寻优以提高模型收敛速度和预测精度。选取天津港实船某段航迹的AIS数据,比较基于DE-SVM与基于BP神经网络的航迹预测模型的仿真结果。结果表明,基于DE-SVM的航迹预测模型具有更高的预测精度,简单、可行、高效,且耗时少。  相似文献   

基于隐马尔科夫模型的VLCC目的港预测     

杨春  王一丹  徐晖  胡勤友  潘亚兰 《上海海事大学学报》2020,41(4):42-49

超大型油船(very large crude carrier，VLCC)目的港预测对海运原油流向预测以及货源地未来运力估计具有重要作用。针对VLCC的AIS目的港信息存在缺失、更新不及时、不准确等现象，提出一种基于隐马尔科夫模型的VLCC目的港预测方法。分析船舶AIS轨迹数据，得到油船历史停靠港口序列；根据VLCC轨迹提取习惯航路，以航路中的交叉点为依据设置观测线；利用船舶航行轨迹数据判断船舶是否经过观测线以及经过观测线的方向，对不同方向分别计算船舶在挂靠港间的转移概率矩阵和船舶挂靠港与观测线间的输出概率矩阵，建立VLCC目的港预测模型并进行预测。研究结果表明：在大多数情况下VLCC目的港预测的准确率可以达到70%以上；航线越固定、运行越规律的船舶，预测准确率越高；船舶越靠近目的港，预测越准确；重载状态下的船舶目的港预测更准确。  相似文献   

大学生孤独感对手机成瘾倾向的影响:生命意义感的调节作用     

陆娟  宫火良 《保定学院学报》2020,(3):95-100

为了探究大学生孤独感、手机成瘾倾向和生命意义感之间的关系,采用UCLA孤独量表、大学生手机成瘾倾向量表、人生意义感问卷,选取408名大学生作为被试进行问卷调查。结果发现:(1)孤独感与手机成瘾倾向呈显著性正相关,生命意义感与手机成瘾倾向呈显著性负相关,孤独感和生命意义感相关性不显著;(2)孤独感和生命意义感都显著预测手机成瘾倾向,生命意义感在孤独感和手机成瘾倾向之间的调节效应显著,低生命意义感大学生的孤独感对手机成瘾倾向的预测力更强。因此,大学生的孤独感能正向预测手机成瘾倾向,生命意义感能调节二者之间的关系,低水平的生命意义感会加剧孤独感对手机成瘾倾向的预测作用,而高水平的生命意义感会使孤独感对手机成瘾倾向的影响较小。  相似文献   

Extended Validation of the Korean Version of the Quality of Life Survey     

SeYun Park  Erin Reifsteck  Diane L. Gill 《Measurement in physical education and exercise science》2019,23(2):110-117

In this study, we examined the factor structure and reliability of the Korean Quality of Life (KQoL) survey and compared the KQoL survey to both the World Health Organization Quality of Life-Brief Version (WHOQOL-BREF) and the Satisfaction with Life Scale (SWLS). We also assessed associations between KQoL scores and physical activity (PA) participation. Participants were 557 (male = 281, female = 276) healthy Korean adults with ages between 18 and 71 years (M = 33.2, SD = 14.2). Results of confirmatory factor analyses confirmed the 7-subscale model and indicated acceptable values supporting convergent validity (χ² = 1,678.758, df = 443, p < .001, RMSR = .045, RMSEA = .071, TLI = .880, CFI = .892). Correlations of KQoL subscales with similar subscales of WHOQOL-BREF and with SWLS supported concurrent validity. Results confirm that the KQoL survey can assess multidimensional aspects of quality of life (QoL), including spiritual, physical, social, and psychological. KQoL scores were positively related to PA participation, in line with previous research supporting the positive association of PA with QoL.  相似文献   

Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods     

《International Journal of Information Management》2019

Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).  相似文献   

基于因子分析和曲线拟合的集装箱吞吐量预测     

贾飞跃  韩晓龙 《上海海事大学学报》2019,40(2):18-22

为提高集装箱吞吐量的预测精度,提出基于因子分析和曲线拟合的集装箱吞吐量预测模型。以上海港为例,通过因子分析,分析影响集装箱吞吐量的主要因素,筛选出主因子,得到不同年份的综合经济发展值;再运用曲线拟合方法,建立以综合经济发展值为自变量,以集装箱吞吐量为因变量的三次曲线模型;运用自回归积分移动平均(autoregressive integrated moving average,ARIMA)模型预测2016—2020年的综合经济发展值,进而求得2016—2020年上海港集装箱吞吐量预测值。结果表明:该模型的拟合效果和预测精度均较高,可以运用到集装箱吞吐量预测中。给出上海港在国内经济新常态下转型升级的建议。  相似文献   

基于二模复杂网络的隐性知识发现方法研究——以潜在药物靶点挖掘为例     

李东巧  陈芳  韩涛  杨艳萍  王学昭  王燕鹏  Cynthia Liu  Yingzhu Li 《图书情报工作》2020,64(21):120-129

[目的/意义] 通过构建二模复杂网络模型，揭示隐藏在海量文献中的隐性知识。[方法/过程] 通过NetworkX复杂网络工具包，依据任意两个节点的共现关系构建二模复杂网络模型；对网络模型中节点的共现关系进行加权，计算网络的拓扑信息并进行AP聚类，提取节点间的直接关系；采用AUC方法对AA、JC、加权改进的wAA和wJC等4种链路预测算法进行评价，遴选出最合适的预测算法，并对复杂网络的隐性关系进行预测分析。[结果/结论] 以潜在药物靶点挖掘为例进行的实证研究结果表明，wAA链路预测算法为最优的链路预测算法；二模复杂网络模型、指标和方法体系在美国化学文摘社数据库中的药物靶点挖掘中具有一定的有效性。下一步计划在其他数据库中或其他研究领域中进行尝试，以进一步验证该模型的通用性和有效性。  相似文献