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Titlebook: Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height; Erik Vanem Book 2013 Springer-Verlag Berlin Heidelber

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樓主: concord
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發(fā)表于 2025-3-25 03:36:39 | 只看該作者
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發(fā)表于 2025-3-25 08:14:51 | 只看該作者
Introduction and Background,bout the environmental operating conditions for ships and other marine structures is emphasized. Furthermore, it is argued that climate change may have an effect on future ocean wave climate and that this needs to be taken into account already in the design process. Integrated sea state parameters s
23#
發(fā)表于 2025-3-25 13:57:16 | 只看該作者
Literature Survey on Stochastic Wave Models,nd sea states as well as a review of alternative approaches from other areas of application. A review of wave climate projections is also included. Efforts have been made to include all relevant and important work to make this literature survey as complete as possible, which has resulted in a rather
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發(fā)表于 2025-3-25 16:42:20 | 只看該作者
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發(fā)表于 2025-3-25 22:18:08 | 只看該作者
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發(fā)表于 2025-3-26 02:48:31 | 只看該作者
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發(fā)表于 2025-3-26 08:11:18 | 只看該作者
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發(fā)表于 2025-3-26 10:55:21 | 只看該作者
Application: Impacts on Ship Structural Loads,oad calculations can be updated to take future projections of the ocean wave climate into account. The potential impact of the estimated long-term trends of significant wave height on the wave-induced structural loads of an oil tanker will be discussed and illustrated by an example. For the purpose
29#
發(fā)表于 2025-3-26 14:24:17 | 只看該作者
,Case Study: Modeling the Effect of Climate Change on the World’s Oceans, the same stochastic Bayesian hierarchical space-time model with regression on atmospheric levels of . in order to estimate the expected long-term trends and make future projections toward the year 2100. The model was initially developed for an area in the North Atlantic Ocean, and has been found to
30#
發(fā)表于 2025-3-26 19:16:23 | 只看該作者
Summary and Conclusions,h as it is a scientific question. Nevertheless, an important prerequisite for making well-founded decisions is a reliable prediction of the future effect of climate change. The stochastic model presented in this monograph aims at contributing to this discussion by providing a model for predicting th
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