An information retrieval model based on vector space method by supervised learning

This paper proposes a method to improve retrieval performance of the vector space model (VSM) in part by utilizing user-supplied information of those documents that are relevant to the query in question. In addition to the user's relevance feedback information, information such as original document similarities is incorporated into the retrieval model, which is built by using a sequence of linear transformations. High-dimensional and sparse vectors are then reduced by singular value decomposition (SVD) and transformed into a low-dimensional vector space, namely the space representing the latent semantic meanings of words. The method has been tested with two test collections, the Medline collection and the Cranfield collection. In order to train the model, multiple partitions are created for each collection. Improvement of average precision of the averages over all partitions, compared with the latent semantic indexing (LSI) model, are 20.57% (Medline) and 22.23% (Cranfield) for the two training data sets, and 0.47% (Medline) and 4.78% (Cranfield) for the test data, respectively. The proposed method provides an approach that makes it possible to preserve user-supplied relevance information for the long term in the system in order to use it later.     

量子力学表象与群表示中线性代数方法的应用

对表象变换,群表示与线性代数中n维矢量空间中坐标变换的相似性进行了类比分析,结果表明：线性代数是二者的数学基础。物理规律对应着确定的群,群的不可约表示对H空间的态矢分类可方便地决定一个量子系统的结构。并对H2O的电子态进行了分析。     

Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model

INTRODUCTION In recent years, research on nonlinear model predictive control has attracted significant attention because most practical processes are nonlinear. In industry process control, model predictive controllers based on linear models (LMPC) are often used to control nonlinear systems. When the operating con- ditions undergo significant changes, the performance of LMPC can deteriorate drastically. Under such conditions, predictive control based on nonlinear models (NMPC) shoul…     

《线性规划》课程改革的方案与实践

提出线性规划课程改革的方案：一个确保，两个面向。并付诸于教学实践。收到了很好的效果。     

地级市创新能力影响因素的分层线性模型研究

以2018年我国30个省份及其对应的280个地级市为研究对象,利用分层线性模型分析省域层面、地级市层面的因素以及二者的交互作用对地级市创新能力的影响。结果显示,我国地级市创新能力的差异中有57.6%可以由省域层面的影响因素解释;地级市自身的经济水平、产业结构、R&D经费支出可以提升其创新能力;省域层面的财政科技支出对其下辖地级市创新能力有正向影响,其他省域层面因素与地级市层面因素存在交互效应。