A mixed-effects least square support vector regression model for three-level count data

Hierarchical study design often occurs in many areas such as epidemiology, psychology, sociology, public health, engineering, and agriculture. This imposes correlation in data structure that needs to be account for in modelling process. In this study, a three-level mixed-effects least squares support vector regression (MLS-SVR) model is proposed to extend the standard least squares support vector regression (LS-SVR) model for handling cluster correlated data. The MLS-SVR model incorporates multiple random effects which allow handling unequal number of observations for each case at non-fixed time points (a very unbalanced situation) and correlation between subjects simultaneously. The methodology consists of a regression modelling step that is performed straightforwardly by solving a linear system. The proposed model is illustrated through numerical studies on simulated data sets and a real data example on human Brucellosis frequency. The generalization performance of the proposed MLS-SVR is evaluated by comparing to ordinary LS-SVR and some other parametric models.     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

20世纪五六十年代中国重型机械技术发展初探

20世纪五六十年代,中国优先发展重工业和国防工业,重型机械制造业随之成为发展迅速的新兴产业。一系列举措促使重型机械技术的发展经历了从修配、仿制、自主研发重大产品的三个阶段。苏联援助、自力更生和“三线建设”等若干因素影响重型机械的技术发展。在此期间,国家强有力的政策指向、薄弱的工业基础、较强的技术引进和消化吸收的能力,决定了中国重型机械技术发展所走的道路。     

中国高速铁路是否显著影响城市土地利用——来自站点、线路和典型城市土地利用变化的回答

当前中国高速铁路正处于快速、全面发展阶段,研究高速铁路对城市土地利用的影响,对城市规划、城市与高速铁路的协调发展等均具有重要意义。利用GIS等技术提取已开通高速铁路站点周边、线路两侧土地利用数据以及部分城市高铁站点周边建设用地重心,从不同空间、城市类型、开通时间等角度对提取结果进行统计分析和图形对比。结果表明：高速铁路能通过促进各类型土地向建设用地转移来影响城市土地利用;高速铁路对站点周边土地利用的影响要大于对线路两侧的影响;高速铁路对城市土地利用的影响因城市规模类型不同而不同,对站点周围土地利用的影响总体有城市规模越大影响越大的特征,对特大城市、超大城市和县线路两侧土地利用的影响大于大中城市;高速铁路对城市土地利用的影响在时间上有递延性,在空间上有衰减性。     

百科方法:人类知识脉络的启示

文章通过对人类知识脉络的思考,从历史纵向的百科全书的发展特质和现代横向的知识平台的建立,提出运用百科方法作为研究知识脉络的手段,主张建立现代“人机知识平台”,作为实践百科方法的基础,以迎接２１世纪知识社会的挑战。     

基于系统动力学的高速铁路人才支撑体系的构建

人才是支持高速铁路发展和平稳运行的关键性因素,加强人才管理和开发对于高铁建设发展具有决定性作用。本文从人力资源管理相关理论入手,结合国内外高速铁路发展现状,运用系统动力学相关方法,构建了高速铁路人才支撑体系框架,为加强高速铁路人才的开发和管理提出了新思路。     

汉英商务信函缩略语块提取方法研究

基于汉英商务信函缩略语块的概念界定和分类,设计了"文本预处理"、"缩略语块识别"、"缩略语块全称识别"、"后期处理"四种模块,从未经词性标注的生语料文本中提取汉英商务信函缩略语块及其全称对,取得了较好的提取效果。     

基于舞弊三角理论的财务舞弊识别模型研究——支持向量机与Logistic回归的耦合实证分析

文章基于舞弊三角理论,对舞弊风险因素进行T检验,选取显著特征运用支持向量机算法和Logistic回归分析方法构建了舞弊识别模型,并进行比较。研究结果表明,财务稳定性越差、监督部门的监督积极性越低、曾经获得非标准审计意见次数越多,公司发生财务舞弊可能性越高。应制定合理的报酬激励机制,降低报酬契约冲突带来的舞弊压力;建立健全内部控制和风险管理评价,减少舞弊的机会;加强内外监督机制,杜绝舞弊的借口。     

普通院校“机械类”专业毕业设计存在的问题与对策

文章阐述了毕业设计在人才培养方面的重要作用,指出普通院校“机械类”专业毕业设计存在的问题,提出了改善毕业设计题目的合理性、充分调动学生的积极性、提高教师的业务素质与责任心、严格控制毕业设计成绩等对策。通过实践,学生完成毕业设计的积极性明显提高,毕业设计质量也有较大提高。     

基于机器视觉的人体尺寸识别系统

提出了一种基于机器视觉的人体尺寸识别系统的技术思路,系统将机器终端获取的人体图像信息,利用图像处 理技术和人体关键尺寸的生理位置特征,实现人体关键尺寸的识别。该系统中需要获取人体正面的手臂水平图像以及 人体侧面图像,2张图像必须在同一相对位置下获取,以保证参考点的一致,在参考被测用户的实际身高下,系统通过计 算可实时给出被测用户的颈部、胸部、腰部、臀部等的正侧面宽度,同时给出各对应部分的所在位置。这种模式可以给出 用户的基本尺寸信息,从而可以为用户实现模拟试衣等仪器提供软件支持。