Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model

Baiyu Chen; Guilin Liu; Liping Wang

doi:doi:10.11648/j.ijees.20170206.11

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Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model

Baiyu Chen, Guilin Liu, Liping Wang

Published in International Journal of Energy and Environmental Science (Volume 2, Issue 6)

Received: 7 October 2017 Accepted: 8 November 2017 Published: 11 December 2017

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Abstract

In this paper, we proposed a novel 2-dimensional (2D) distribution model based on the maximum-entropy (ME) principle to predict the joint return period under ocean extremes. In detail, we first derive the joint probability distribution of the extreme wave heights and the extreme water-levels during a typhoon by using the maximum-entropy principle, and then we nest this distribution with the maximum-entropy distribution of discrete variables to form such a maximum-entropy 2-dimensional (ME 2D) compound distribution model. To evaluate the performance of our model, we conduct experiments to predict the N-year joint return-periods of the extreme wave heights and the extreme water levels in two areas of the East China Sea. According to the experimental results, our model performs better in predicting in the highly unpredictable joint probability of extreme wave heights and water levels in typhoon affected sea areas, compared with the widely-used Poisson-Mixed-Gumbel model in ocean engineering design. This ascribes to the fact that unlike other models whose corresponding parameters are arbitrarily assigned, our model utilizes both the new 2D distribution and the discrete distribution which are based on the ME principle.

Published in	International Journal of Energy and Environmental Science (Volume 2, Issue 6)
DOI	10.11648/j.ijees.20170206.11
Page(s)	117-126
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Maximum Entropy Principle, 2D Compound Distribution Model, Extreme Wave Height, Extreme Water Level, Optimization, Climate Change

References

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APA Style

Baiyu Chen, Guilin Liu, Liping Wang. (2017). Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model. International Journal of Energy and Environmental Science, 2(6), 117-126. https://doi.org/10.11648/j.ijees.20170206.11

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ACS Style

Baiyu Chen; Guilin Liu; Liping Wang. Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model. Int. J. Energy Environ. Sci. 2017, 2(6), 117-126. doi: 10.11648/j.ijees.20170206.11

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AMA Style

Baiyu Chen, Guilin Liu, Liping Wang. Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model. Int J Energy Environ Sci. 2017;2(6):117-126. doi: 10.11648/j.ijees.20170206.11

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@article{10.11648/j.ijees.20170206.11,
  author = {Baiyu Chen and Guilin Liu and Liping Wang},
  title = {Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model},
  journal = {International Journal of Energy and Environmental Science},
  volume = {2},
  number = {6},
  pages = {117-126},
  doi = {10.11648/j.ijees.20170206.11},
  url = {https://doi.org/10.11648/j.ijees.20170206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijees.20170206.11},
  abstract = {In this paper, we proposed a novel 2-dimensional (2D) distribution model based on the maximum-entropy (ME) principle to predict the joint return period under ocean extremes. In detail, we first derive the joint probability distribution of the extreme wave heights and the extreme water-levels during a typhoon by using the maximum-entropy principle, and then we nest this distribution with the maximum-entropy distribution of discrete variables to form such a maximum-entropy 2-dimensional (ME 2D) compound distribution model. To evaluate the performance of our model, we conduct experiments to predict the N-year joint return-periods of the extreme wave heights and the extreme water levels in two areas of the East China Sea. According to the experimental results, our model performs better in predicting in the highly unpredictable joint probability of extreme wave heights and water levels in typhoon affected sea areas, compared with the widely-used Poisson-Mixed-Gumbel model in ocean engineering design. This ascribes to the fact that unlike other models whose corresponding parameters are arbitrarily assigned, our model utilizes both the new 2D distribution and the discrete distribution which are based on the ME principle.},
 year = {2017}
}

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TY  - JOUR
T1  - Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model
AU  - Baiyu Chen
AU  - Guilin Liu
AU  - Liping Wang
Y1  - 2017/12/11
PY  - 2017
N1  - https://doi.org/10.11648/j.ijees.20170206.11
DO  - 10.11648/j.ijees.20170206.11
T2  - International Journal of Energy and Environmental Science
JF  - International Journal of Energy and Environmental Science
JO  - International Journal of Energy and Environmental Science
SP  - 117
EP  - 126
PB  - Science Publishing Group
SN  - 2578-9546
UR  - https://doi.org/10.11648/j.ijees.20170206.11
AB  - In this paper, we proposed a novel 2-dimensional (2D) distribution model based on the maximum-entropy (ME) principle to predict the joint return period under ocean extremes. In detail, we first derive the joint probability distribution of the extreme wave heights and the extreme water-levels during a typhoon by using the maximum-entropy principle, and then we nest this distribution with the maximum-entropy distribution of discrete variables to form such a maximum-entropy 2-dimensional (ME 2D) compound distribution model. To evaluate the performance of our model, we conduct experiments to predict the N-year joint return-periods of the extreme wave heights and the extreme water levels in two areas of the East China Sea. According to the experimental results, our model performs better in predicting in the highly unpredictable joint probability of extreme wave heights and water levels in typhoon affected sea areas, compared with the widely-used Poisson-Mixed-Gumbel model in ocean engineering design. This ascribes to the fact that unlike other models whose corresponding parameters are arbitrarily assigned, our model utilizes both the new 2D distribution and the discrete distribution which are based on the ME principle.
VL  - 2
IS  - 6
ER  -

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Author Information

Baiyu Chen

College of Engineering, University of California Berkeley, Berkeley, USA
Guilin Liu

College of Engineering, Ocean University of China, Qingdao, China
Liping Wang

School of Mathematical Sciences, Ocean University of China, Qingdao, China

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Plain Text BibTeX RIS

APA Style

Baiyu Chen, Guilin Liu, Liping Wang. (2017). Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model. International Journal of Energy and Environmental Science, 2(6), 117-126. https://doi.org/10.11648/j.ijees.20170206.11

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ACS Style

Baiyu Chen; Guilin Liu; Liping Wang. Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model. Int. J. Energy Environ. Sci. 2017, 2(6), 117-126. doi: 10.11648/j.ijees.20170206.11

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AMA Style

Baiyu Chen, Guilin Liu, Liping Wang. Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model. Int J Energy Environ Sci. 2017;2(6):117-126. doi: 10.11648/j.ijees.20170206.11

Copy | Download

@article{10.11648/j.ijees.20170206.11,
  author = {Baiyu Chen and Guilin Liu and Liping Wang},
  title = {Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model},
  journal = {International Journal of Energy and Environmental Science},
  volume = {2},
  number = {6},
  pages = {117-126},
  doi = {10.11648/j.ijees.20170206.11},
  url = {https://doi.org/10.11648/j.ijees.20170206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijees.20170206.11},
  abstract = {In this paper, we proposed a novel 2-dimensional (2D) distribution model based on the maximum-entropy (ME) principle to predict the joint return period under ocean extremes. In detail, we first derive the joint probability distribution of the extreme wave heights and the extreme water-levels during a typhoon by using the maximum-entropy principle, and then we nest this distribution with the maximum-entropy distribution of discrete variables to form such a maximum-entropy 2-dimensional (ME 2D) compound distribution model. To evaluate the performance of our model, we conduct experiments to predict the N-year joint return-periods of the extreme wave heights and the extreme water levels in two areas of the East China Sea. According to the experimental results, our model performs better in predicting in the highly unpredictable joint probability of extreme wave heights and water levels in typhoon affected sea areas, compared with the widely-used Poisson-Mixed-Gumbel model in ocean engineering design. This ascribes to the fact that unlike other models whose corresponding parameters are arbitrarily assigned, our model utilizes both the new 2D distribution and the discrete distribution which are based on the ME principle.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Predicting Joint Return Period Under Ocean Extremes Based on a Maximum Entropy Compound Distribution Model
AU  - Baiyu Chen
AU  - Guilin Liu
AU  - Liping Wang
Y1  - 2017/12/11
PY  - 2017
N1  - https://doi.org/10.11648/j.ijees.20170206.11
DO  - 10.11648/j.ijees.20170206.11
T2  - International Journal of Energy and Environmental Science
JF  - International Journal of Energy and Environmental Science
JO  - International Journal of Energy and Environmental Science
SP  - 117
EP  - 126
PB  - Science Publishing Group
SN  - 2578-9546
UR  - https://doi.org/10.11648/j.ijees.20170206.11
AB  - In this paper, we proposed a novel 2-dimensional (2D) distribution model based on the maximum-entropy (ME) principle to predict the joint return period under ocean extremes. In detail, we first derive the joint probability distribution of the extreme wave heights and the extreme water-levels during a typhoon by using the maximum-entropy principle, and then we nest this distribution with the maximum-entropy distribution of discrete variables to form such a maximum-entropy 2-dimensional (ME 2D) compound distribution model. To evaluate the performance of our model, we conduct experiments to predict the N-year joint return-periods of the extreme wave heights and the extreme water levels in two areas of the East China Sea. According to the experimental results, our model performs better in predicting in the highly unpredictable joint probability of extreme wave heights and water levels in typhoon affected sea areas, compared with the widely-used Poisson-Mixed-Gumbel model in ocean engineering design. This ascribes to the fact that unlike other models whose corresponding parameters are arbitrarily assigned, our model utilizes both the new 2D distribution and the discrete distribution which are based on the ME principle.
VL  - 2
IS  - 6
ER  -

Copy | Download