Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the scoring functions under high dimensional cases.We study the construction of confidence regions for the parameters in spatial autoregressive models with spatial autoregressive disturbances(SARAR models)with high dimension of parameters by using the NBEL method.It is shown that the NBEL ratio statistics are asymptoticallyχ^(2)-type distributed,which are used to obtain the NBEL based confidence regions for the parameters in SARAR models.A simulation study is conducted to compare the performances of the NBEL and the usual EL methods.
Accurate lateral state estimation is crucial for ensuring the stability and safety of vehicles.The Kalman filter is widely utilized to estimate the lateral state of vehicles.However,vehicle state measurement suffers from inherent time delays and model discrepancies.The existence of fractional and random delays necessitates long sampling periods for the inputs of the Kalman filter,leading to update mismatch and deterioration of the accuracy of the estimation.This situation poses a threat to driving safety.In addition,the tire cornering stiffness,a critical model parameter,exhibits nonlinear and dynamic variations that cannot be measured in real time.This inherent variability significantly affects the accuracy of lateral state estimation.Considering internal and external uncertainties,an observer framework for vehicle lateral state estimation based on the Kalman filter was designed in this work.First,a modified delayed Kalman filter method that considers the random fractional delays was developed.The relationship correlation between the delayed measurement and the prior state was constructed based on a likelihood algorithm.Then,the tire cornering stiffness was estimated online by an algorithm based on recursive least squares.This parameter was used to dynamically adjust the vehicle model for the Kalman filter.Finally,two simulations and a real vehicle experiment were performed to verify the effectiveness of the proposed method.In particular,the root mean squared error(RMSE)of the slip angle decreased by 30.70%,and that of the yaw rate decreased by 61.03%in the double lane change scenario.Actual vehicle experiments demonstrated that the algorithm can be effectively applied in real situations.
Chao YANGRuixin ZHANGWeida WANGYuhang ZHANGJiayi FANGQi WANGShouwen YAO
为探究电商带货短视频的内容与信源对用户购买行为的影响,本研究基于详尽分析可能性模型(ELM),以信息质量为中心路径,以信源质量为边缘路径,预设并检验用户对电商短视频的信任意愿模型。研究发现:信息质量显著正向影响用户的感知有用性和感知信任行为;信源质量显著正向影响用户的感知信任意愿,但对信息的感知有用性影响并不显著;信息的感知有用性与感知信任呈正向相关。基于数据分析,研究提出坚持内容导向、优化信息呈现以及搭建信息与用户行为的反馈循环机制的针对性建议。To explore the impact of content and source credibility on user purchase behavior in e-commerce short videos, this study employs the Elaboration Likelihood Model (ELM), focusing on information quality as the central route and source credibility as the peripheral route. The research develops and tests a model of user trust intentions toward e-commerce short videos. The findings reveal that information quality significantly and positively affects users’ perceived usefulness and trust behavior. Source credibility, while having a significant positive impact on perceived trust intentions, shows no significant influence on perceived usefulness. Additionally, perceived usefulness is positively correlated with trust intentions. Based on the data analysis, this study provides targeted recommendations, including maintaining content quality, optimizing information presentation, and establishing feedback loops between information and user behavior.
土地利用变化是指由于自然或人为因素引起的土地覆盖和土地利用方式的变化。现有研究多集中于人类活动的影响,而对自然环境驱动的土地利用变化的探讨较少。本研究聚焦青藏高原南部,利用Landsat卫星数据,采用最大似然法(Maximum Likelihood Classification, MLC)对1985~2005年间的遥感影像进行了监督分类。结果显示,模型在耕地、水体和冰川及永久性积雪等特征明显的类别上表现出较高的准确率、精确率、召回率和F1分数,而对于林地和湿地等光谱特性相似或内部异质性较高的类别,分类精度略有下降。总体而言,二十年间模型的分类性能稳定且可靠,显示出随着时间推移逐步优化的能力。研究表明:1) 基于MLC的方法依然在自然环境驱动区域的土地利用变化监测中具有较好的应用前景;2) 通过对1985~2005年间研究区土地利用转移矩阵的分析,揭示了该时期内土地利用类型的显著动态变化,耕地、草地、林地的变化体现了生态恢复政策的有效实施,冰川和永久积雪、湿地的变化则反映了气候变化对自然环境的影响。未来的研究可以通过引入更多样化的样本和改进模型参数来进一步提升分类精度,并探索结合多时相影像和其他遥感源以增强不同类别之间的可分性。Land use change refers to the change of land cover and land use mode caused by natural or human factors. Most existing studies focus on the effects of human activities and less on natural environment-driven land use change. This study focused on the southern Qinghai-Xizang Plateau and used Landsat satellite data and Maximum Likelihood Classification (MLC) to supervise and classify remote sensing images between 1985 and 2005. The results showed that the model showed high accuracy, precision, recall and F1 scores in the categories well characterized by cultivated land, water, glaciers and permanent snow, while the classification accuracy decreased slightly fo
