Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

站在人类先进文化发展的潮头

该文以唯物史观为指导,阐明了马克思主义文化理论、中国现代文化的形成和中国先进文化的发展方向.作者认为文化是人类社会在经济、政治、精神上的反映,包括意识形态和其他一切精神活动及其产物,对经济、政治又具有强大的反作用.中国现代社会主义文化是由农业封建主义文化在近百年的经济、政治发展的基础上逐渐演变而成的,它的前进方向是面向现代化、面向世界、面向未来的民族的、科学的、大众的社会主义文化.     

我国《合同法》应将损害赔偿规定为违约救济的首要方式

对于违约案件 ,法院在选择对受害人的救济方式时 ,应首先考虑损害赔偿 ,还是实际履行 ?西方国家多优先适用损害赔偿 ,因为市场主体的交易目的是赢利 ,而损害赔偿能以最快速度填补受害方的利益 ,且无需违约方配合 ,便于法院执行。但我国现行《合同法》却置实际履行于首位 ,损害赔偿于末位 ,这不符合事理、法理和国际惯例 ,应予修正。     

刚体转动渐进跟踪控制的逆系统方法

逆系统方法是以非线性控制为目的,以直接分析为途径,以动态系统的逆概念为核心。该文将逆系统方法应用于刚体动力学中,运用非线性控制的逆系统方法设计Euler动力学方程的控制器,通过对一个陀螺的外力矩进行实施控制,使刚体在动坐标系下的角速度稳定跟踪指令,来实现对刚体转动的渐进跟踪控制。     

知识型企业结构、特征及报酬递增效应分析

在市场经济条件下,知识已经成为企业竞争力的源泉.知识经济、知识管理、知识型企业等思想被越来越多的人所接受.和传统企业相比,知识型企业的结构及特征有它特定的一面.文章在分析知识型企业内外部结构的基础上,对知识型企业的特征进行了分析,进而探讨了由其特征所决定的知识型企业生产函数及报酬递增效应.     

试论“思想家的小说”的作者吴敬梓的思想

吴敬梓的思想内涵十分丰赡 ,传统思想中的儒家思想和魏晋六朝风尚对他的影响至大 ,而时代思潮中的颜李学说以及自然科学学风也同样影响了他。吴敬梓之所以受到这些思想的影响 ,是与他的家庭传统和生活实践密切相关的。而研究他的思想必须从他所创造的艺术形象着手 ,重视形象思维的特性。     

唐代洛阳的水害

洛阳有伊、洛、、涧、谷等数条河流。唐代东都洛阳水灾频繁发生 ,共 35次之多 ,平均不足 1 0年一次 ,给洛阳城及沿岸造成严重破坏和损失。洛阳水灾发生多为五至八月份。唐代洛阳河流具有明显的季节性 ,雨季流量大 ,便于行舟 ,旱季水少河浅难以行船。针对频发的水灾 ,唐政府采取了一系列救助灾民的措施 ,同时还采取了加固堤坝、疏浚河道等防治措施     

论环境侵权中风险责任的确立

基于环境侵害具有潜伏性和不可逆转性的特点,以损害实际发生为归责前提的过错责任和无过错责任原则在环境侵权中的适用无法体现环境保护“预防为主”的思想。风险责任进入环境侵权归责体系则可以较好地解决这一问题,但风险责任的适用必须解决权利主体和义务主体的特定化问题、损害预防和经济发展的矛盾问题以及风险责任本身在侵权行为法中的立法体例问题。     

个人数据损害的类型及其确定

依告知同意原则构建的个人数据保护制度面临着过度收集、擅自披露与滥用等问题的严重挑战。公权保护路径存在监管力度、范围及效力的局限性,而传统侵权法上的损害观念架空了数据主体的私法救济权利。因此,为保障数字经济的健康发展,必须扩张侵权法上损害的含义。法律上可予赔偿的个人数据损害应延及两类新型损害：数据主体遭受次生损害的风险,以及社会分选歧视、数据监控、自动化决策等造成的人格利益减损。在确定具体赔偿数额时,为解决风险与人格利益减损所产生的经济量化与举证责任之困境,《个人信息保护法》应采用知识产权法中广泛适用的法定赔偿制度。