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排序方式: 共有711条查询结果,搜索用时 15 毫秒
1.
Dennis Wagenaar Tiaravanni Hermawan Marc J. C. van den Homberg Jeroen C. J. H. Aerts Heidi Kreibich Hans de Moel Laurens M. Bouwer 《Risk analysis》2021,41(1):37-55
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. 相似文献
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Social Indicators Research - Debates about the appropriate role of markets and governments are often shaped by sharply contrasting opinions. Based on individual data from the World Values Survey... 相似文献
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Christian P. Robert Xiao-Li Meng Jesper Møller Jeffrey S Rosenthal C Jennison M. A Hurn F Al-Awadhi Peter McCullagh Christophe Andrieu Arnaud Doucet Petros Dellaportas Ioulia Papageorgiou Ricardo S Ehlers Elena A Erosheva Stephen E Fienberg Jonathan J Forster Roger C Gill Nial Friel Peter Green David Hastie R King Hans R Künsch N. A. Lazar C Osinski 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2003,65(1):39-55
7.
Franses Philip Hans 《Econometric Reviews》1995,14(1):55-63
In this paper it is shown that several models for a bivariate nonstationary quarterly time series are nested in a vector autoregression with cointegration restrictions for the eight annual series of quarterly observations. Or, the Granger Representation Theorem is extended to incorporate, e.g., seasonal and periodic cointegration. 相似文献
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Statistical Papers - 相似文献
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In this paper, we propose to detect seasonal unit roots within the context of a structural time series model. Such a model is often found to be useful in practice. Using Monte Carlo simulations, we show that our method works well. We illustrate our approach for several quarterly macroeconomic time series variables. 相似文献
10.
Dramatically reducing cycle times through flash development 总被引:1,自引:0,他引:1
Mark VandenboschAuthor VitaeTom CliftAuthor Vitae 《Long Range Planning》2002,35(6):567-589
The reduction of cycle time has emerged as a fundamental element of new product development strategy. Many companies look solely at speed enhancement and increase the human, capital and technical resources allocated to development projects. However, additional resources do not guarantee significant reductions in cycle time. As well as speed enhancement activities, there exist two other sets of activities that are key to shortening the development cycle: those that act to prevent delays (friction) in the development process and those that define the scope of the final outcome (direction). This paper describes flash development as an alternative approach to reducing product development cycle times. Flash development works by creating a process that focuses on speed, friction and direction. The process is illustrated through an analysis of the Galileo Project at Nortel Networks. 相似文献