Error-in-variables model of Malacca wind direction data with the von Mises distribution in southwest monsoon

2021 ◽  
Vol 15 (9) ◽  
pp. 471-479
Author(s):  
Nurkhairany Amyra Mokhtar ◽  
Basri Badyalina ◽  
Kerk Lee Chang ◽  
Fatin Farazh Ya'acob ◽  
Ahmad Faiz Ghazali ◽  
...  
Keyword(s):  
Wind Direction ◽  
Southwest Monsoon ◽  
Von Mises Distribution ◽  
Error In Variables ◽  
Von Mises

scholarly journals Modelling wind direction data of Langkawi Island during Southwest monsoon in 2019 to 2020 using bivariate linear functional relationship model with von Mises distribution

2021 ◽  
Vol 1988 (1) ◽  
pp. 012097
Author(s):  
Nurkhairany Amyra Mokhtar ◽  
Yong Zulina Zubairi ◽  
Abdul Ghapor Hussin ◽  
Basri Badyalina ◽  
Ahmad Faiz Ghazali ◽  
...  
Keyword(s):  
Wind Direction ◽  
Linear Functional ◽  
Functional Relationship ◽  
Southwest Monsoon ◽  
Von Mises Distribution ◽  
Relationship Model ◽  
Von Mises

scholarly journals Understanding the Behaviour of Wind Direction in Malaysia during Monsoon Seasons using Replicated Functional Relationship in von Mises Distribution

2021 ◽  
Vol 50 (7) ◽  
pp. 2035-2045
Author(s):  
Nor Hafizah Moslim ◽  
Nurkhairany Amyra Mokhtar ◽  
Yong Zulina Zubairi ◽  
Abdul Ghapor Hussin
Keyword(s):  
Simulation Study ◽  
Wind Direction ◽  
Functional Relationship ◽  
Wind Data ◽  
Likelihood Method ◽  
Von Mises Distribution ◽  
Northeast Monsoon ◽  
Relationship Model ◽  
Von Mises ◽  
Relationship Of

In studies of potential wind energy, knowing statistical distribution of wind direction provides useful information in making predictions and gives a better understanding of the behavior of the wind direction. Malaysia experiences two monsoon seasons per year, namely Southwest Monsoon and Northeast Monsoon and in this paper, our interest is to investigate whether the direction of wind data in monsoon seasons can be modelled using replicated LFRM with von Mises distribution. The beauty of this model is that it considers the error terms in both x and y variables. This study considers the bivariate relationship of directional wind data where errors are present in both. Here, we propose a replicated functional relationship model, with the von Mises distribution to describe the relationship of the wind direction data. In the parameter estimation, maximum likelihood method is considered with pseudo-replicated group of the replicated form of the functional relationship. The novelty of this approach is that assumption on the ratio of concentration parameters is no longer deemed necessary. Also, we derive the covariance matrix of the parameters based on Fisher Information. From the Monte Carlo simulation study, small bias measures were obtained, suggesting the viability of the model. Based on the simulation study, it can be concluded that the wind direction of the two monsoons in Malaysia can be modelled using replicated linear functional relationship model.

An extension of the von mises distribution

1982 ◽  
Vol 11 (15) ◽  
pp. 1695-1706 ◽  
Author(s):  
E.A. Yfantis ◽  
L.E. Borgman
Keyword(s):  
Von Mises Distribution ◽  
Von Mises

scholarly journals STATISTICAL MODEL FOR THE RELATIONSHIP BETWEEN MAIZE KERNEL ORIENTATION AND SEED LEAF AZIMUTH

2015 ◽  
Vol 52 (3) ◽  
pp. 359-370
Author(s):  
ADRIAN KOLLER ◽  
GUILHERME TORRES ◽  
MICHAEL BUSER ◽  
RANDY TAYLOR ◽  
BILL RAUN ◽  
...  
Keyword(s):  
Simulation Models ◽  
Circular Statistics ◽  
Von Mises Distribution ◽  
Canopy Closure ◽  
Canopy Architecture ◽  
Maize Kernel ◽  
Angular Data ◽  
Significant Yield ◽  
Von Mises ◽  
The Relationship

SUMMARYHand-planted plots of across-row-oriented corn seeds (Zeamays L.) produce highly structured leaf canopies and have shown significant yield advantage over randomly planted plots in prior studies. For further investigation of the phenomenon by simulation, the objective of this study was to develop a probabilistic model for the correlation between seed orientation and initial plant orientation. In greenhouse trials, the azimuthal orientation of kernels of four different hybrids was recorded at planting. At collar setting of the seed leaf, the orientation of the seed leaf was determined and the angular data subjected to the analytical methods of circular statistics. The results indicate that the correlation between seed azimuth and seed leaf azimuth can be described by a von Mises distribution. The probabilistic seed to seed leaf azimuth model described herein may be implemented in simulation models to investigate the effect of canopy architecture, canopy closure and light interception efficiency of corn under conditions of seed oriented planting.

scholarly journals Influence of Wind Speed, Wind Direction and Turbulence Model for Bridge Hanger: A Case Study

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1633
Author(s):  
Yang Ding ◽  
Shuang-Xi Zhou ◽  
Yong-Qi Wei ◽  
Tong-Lin Yang ◽  
Jing-Liang Dong
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Wind Field ◽  
Solid Mechanics ◽  
Von Mises Stress ◽  
Long Span Bridges ◽  
High Rise ◽  
Long Span ◽  
Cfd Models ◽  
Von Mises

Wind field (e.g., wind speed and wind direction) has the characteristics of randomness, nonlinearity, and uncertainty, which can be critical and even destructive on a long-span bridge’s hangers, such as vortex shedding, galloping, and flutter. Nowadays, the finite element method is widely used for model calculation, such as in long-span bridges and high-rise buildings. In this study, the investigated bridge hanger model was established by COMSOL Multiphysics software, which can calculate fluid dynamics (CFD), solid mechanics, and fluid–solid coupling. Regarding the wind field of bridge hangers, the influence of CFD models, wind speed, and wind direction are investigated. Specifically, the bridge hanger structure has symmetrical characteristics, which can greatly reduce the calculation efficiency. Furthermore, the von Mises stress of bridge hangers is calculated based on fluid–solid coupling.

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