MODELING OF SNOW LOAD USING FILTERED POISSON PROCESS

机译：基于泊松过程的雪荷载建模

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Stochastic process modeling of snow loads has been applied in structural reliability analysis. However, the snow load is usually modeled by a random variable with a specific distribution (e.g., Lognormal distribution) in combination with a Bernoulli pulse process. In this paper, the Filtered Poisson Process (FPP) is used to model the snow load. Simulated records are compared with weather records of Stampede Pass, WA and Buffalo, NY, obtained from the National Climatic Data Center (NCDC). The FPP model is demonstrated to be versatile for both heavy and light snow load areas.

机译：雪荷载的随机过程建模已应用于结构可靠性分析中。然而，雪荷载通常由具有特定分布（例如，对数正态分布）的随机变量与伯努利脉冲过程结合来建模。在本文中，过滤泊松过程（FPP）用于模拟雪荷载。将模拟记录与从美国国家气候数据中心（NCDC）获得的西澳大利亚州Stampede Pass和纽约州布法罗的天气记录进行比较。 FPP模型被证明在大雪负荷地区和轻雪负荷地区均具有通用性。

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来源
《Cold regions engineering 2009 : Cold regions impact on research, design, and construction》|2009年|P.618-626|共9页
会议地点 Duluth MN(US)
作者
Y. J. Yin; W. M. Bulleit; Y. Li;
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作者单位

Department of Civil and Environmental Engineering, Michigan Technological University;

rnDepartment of Civil and Environmental Engineering, Michigan Technological University;

rnDepartment of Civil and Environmental Engineering, Michigan Technological University;

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会议组织
原文格式 PDF
正文语种 eng
中图分类冰冻与严寒地区筑路;
关键词
numerical models; genetic algorithm; snow load; stochastic processes;

机译：数值模型遗传算法雪荷载随机过程;

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专利

1. Stochastic Modeling of Snow Loads Using a Filtered Poisson Process [J] . Yue-Jun Yin, Yue Li, William M. Bulleit Journal of Cold Regions Engineering . 2011,第1期

机译：使用滤波泊松过程的雪荷载的随机建模
2. Modeling and forecasting river flows by means of filtered Poisson processes [J] . Mario Lefebvre, Fatima Bensalma Applied Mathematical Modelling . 2015,第1期

机译：通过滤波的泊松过程对河流流量进行建模和预测
3. DISCRETE TIME FILTERS FOR DOUBLY STOCHASTIC POISSON PROCESSES AND OTHER EXPONENTIAL NOISE MODELS [J] . JONATHAN H. MANTON, VIKRAM KRISHNAMURTHY, ROBERT J. ELLIOTT International Journal of Adaptive Control and Signal Processing . 1999,第5期

机译：双随机泊松过程和其他指数噪声模型的离散时间滤波器
4. Robust detection filters for jump Markov systems with doubly stochastic Poisson process models [C] . Malcolm W.P., Elliott R.J. Information, Decision and Control, 2002. Final Program and Abstracts . 2002

机译：具有双重随机Poisson过程模型的跳跃Markov系统的鲁棒检测滤波器
5. ESTIMATION OF THE INTENSITY OF A FILTERED POISSON PROCESS AND ITS APPLICATION TO ACOUSTIC ASSESSMENT OF MARINE ORGANISMS. [D] . EHRENBERG, JOHN EDWARD. 1973

机译：泊松过程强度的估计及其在海洋生物声学评估中的应用。
6. Assessing Performance of Bayesian State-Space Models Fit to Argos Satellite Telemetry Locations Processed with Kalman Filtering [O] . Mónica A. Silva, Ian Jonsen, Deborah J. F. Russell, -1

机译：评估适合卡尔曼滤波处理的Argos卫星遥测位置的贝叶斯状态空间模型的性能
7. Modelling and Evaluation of Generally Corroded Surface by Filtered Poisson Process [O] . Kohei TSUJI, Toshiaki HISADA, Hideo KITAGAWA 1984

机译：滤波泊松工艺一般腐蚀表面的建模与评价
8. Identification d'une Classe de Processus de Poisson Filtres (Identification of a Class of Filtered Poisson Processes) [R] . Brucq, D. 1983

机译：鉴定一类滤波泊松过程（确定一类过滤泊松过程）

MODELING OF SNOW LOAD USING FILTERED POISSON PROCESS

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