Intelligent Methods Used for Obtaining Weather Derivatives: A Review

Gujanatti Rudrappa; Nataraj Vijapur

doi:doi:10.11648/j.eas.20190406.12

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Intelligent Methods Used for Obtaining Weather Derivatives: A Review

Gujanatti Rudrappa, Nataraj Vijapur

Published in Engineering and Applied Sciences (Volume 4, Issue 6)

Received: 24 July 2019 Accepted: 31 October 2019 Published: 6 December 2019

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Abstract

Weather is the condition of the atmosphere and forecasting is predicting the condition of the atmosphere in near future. Weather forecasting is a formidable challenge as weather is a multi- dimensional, continuous and chaotic process. The distinct nature of the model forecasting in all situations accurately is challenging. Presently weather conditions are being obtained from satellites, Doppler radar, radio sounds, observations from aircraft and ground. Collected data is subjected to various statistical and machine learning techniques. These techniques can incorporate relatively simple observation of the sky to highly complex computerized mathematical models. Weather forecasting still remains a challenging issue, due to unpredictable and chaotic nature of weather. Even with present methods the weather forecasting system may still fail to predict weather attribute, therefore there is still scope left to improve these systems. The objective of carrying out the survey is to look forward on how machine learning can help us to improve weather parameter estimation. In this paper we report the different methods carried out by leading researchers, formidable challenges and present our views on development of efficient weather forecasting system. Also, we propose a method which makes use image processing and neural networks to achieve the weather parameter estimation.

Published in	Engineering and Applied Sciences (Volume 4, Issue 6)
DOI	10.11648/j.eas.20190406.12
Page(s)	144-148
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), 2024. Published by Science Publishing Group

Keywords

Weather, Weather Forecasting, Weather Forecasting Systems, Artificial Intelligence, Machine Learning, Image Processing

References

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APA Style

Gujanatti Rudrappa, Nataraj Vijapur. (2019). Intelligent Methods Used for Obtaining Weather Derivatives: A Review. Engineering and Applied Sciences, 4(6), 144-148. https://doi.org/10.11648/j.eas.20190406.12

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ACS Style

Gujanatti Rudrappa; Nataraj Vijapur. Intelligent Methods Used for Obtaining Weather Derivatives: A Review. Eng. Appl. Sci. 2019, 4(6), 144-148. doi: 10.11648/j.eas.20190406.12

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AMA Style

Gujanatti Rudrappa, Nataraj Vijapur. Intelligent Methods Used for Obtaining Weather Derivatives: A Review. Eng Appl Sci. 2019;4(6):144-148. doi: 10.11648/j.eas.20190406.12

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@article{10.11648/j.eas.20190406.12,
  author = {Gujanatti Rudrappa and Nataraj Vijapur},
  title = {Intelligent Methods Used for Obtaining Weather Derivatives: A Review},
  journal = {Engineering and Applied Sciences},
  volume = {4},
  number = {6},
  pages = {144-148},
  doi = {10.11648/j.eas.20190406.12},
  url = {https://doi.org/10.11648/j.eas.20190406.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eas.20190406.12},
  abstract = {Weather is the condition of the atmosphere and forecasting is predicting the condition of the atmosphere in near future. Weather forecasting is a formidable challenge as weather is a multi- dimensional, continuous and chaotic process. The distinct nature of the model forecasting in all situations accurately is challenging. Presently weather conditions are being obtained from satellites, Doppler radar, radio sounds, observations from aircraft and ground. Collected data is subjected to various statistical and machine learning techniques. These techniques can incorporate relatively simple observation of the sky to highly complex computerized mathematical models. Weather forecasting still remains a challenging issue, due to unpredictable and chaotic nature of weather. Even with present methods the weather forecasting system may still fail to predict weather attribute, therefore there is still scope left to improve these systems. The objective of carrying out the survey is to look forward on how machine learning can help us to improve weather parameter estimation. In this paper we report the different methods carried out by leading researchers, formidable challenges and present our views on development of efficient weather forecasting system. Also, we propose a method which makes use image processing and neural networks to achieve the weather parameter estimation.},
 year = {2019}
}

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TY - JOUR
T1 - Intelligent Methods Used for Obtaining Weather Derivatives: A Review
AU - Gujanatti Rudrappa
AU - Nataraj Vijapur
Y1 - 2019/12/06
PY - 2019
N1 - https://doi.org/10.11648/j.eas.20190406.12
DO - 10.11648/j.eas.20190406.12
T2 - Engineering and Applied Sciences
JF - Engineering and Applied Sciences
JO - Engineering and Applied Sciences
SP - 144
EP - 148
PB - Science Publishing Group
SN - 2575-1468
UR - https://doi.org/10.11648/j.eas.20190406.12
AB - Weather is the condition of the atmosphere and forecasting is predicting the condition of the atmosphere in near future. Weather forecasting is a formidable challenge as weather is a multi- dimensional, continuous and chaotic process. The distinct nature of the model forecasting in all situations accurately is challenging. Presently weather conditions are being obtained from satellites, Doppler radar, radio sounds, observations from aircraft and ground. Collected data is subjected to various statistical and machine learning techniques. These techniques can incorporate relatively simple observation of the sky to highly complex computerized mathematical models. Weather forecasting still remains a challenging issue, due to unpredictable and chaotic nature of weather. Even with present methods the weather forecasting system may still fail to predict weather attribute, therefore there is still scope left to improve these systems. The objective of carrying out the survey is to look forward on how machine learning can help us to improve weather parameter estimation. In this paper we report the different methods carried out by leading researchers, formidable challenges and present our views on development of efficient weather forecasting system. Also, we propose a method which makes use image processing and neural networks to achieve the weather parameter estimation.
VL - 4
IS - 6
ER -

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Author Information

Gujanatti Rudrappa

Department of Electronics and Communication, KLE Dr. M. S. Sheshgiri College of Engineering and Technology, VTU, Belgaum, India
Nataraj Vijapur

Department of Electronics and Communication, KLE Dr. M. S. Sheshgiri College of Engineering and Technology, VTU, Belgaum, India

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Gujanatti Rudrappa, Nataraj Vijapur. (2019). Intelligent Methods Used for Obtaining Weather Derivatives: A Review. Engineering and Applied Sciences, 4(6), 144-148. https://doi.org/10.11648/j.eas.20190406.12

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ACS Style

Gujanatti Rudrappa; Nataraj Vijapur. Intelligent Methods Used for Obtaining Weather Derivatives: A Review. Eng. Appl. Sci. 2019, 4(6), 144-148. doi: 10.11648/j.eas.20190406.12

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AMA Style

Gujanatti Rudrappa, Nataraj Vijapur. Intelligent Methods Used for Obtaining Weather Derivatives: A Review. Eng Appl Sci. 2019;4(6):144-148. doi: 10.11648/j.eas.20190406.12

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@article{10.11648/j.eas.20190406.12,
  author = {Gujanatti Rudrappa and Nataraj Vijapur},
  title = {Intelligent Methods Used for Obtaining Weather Derivatives: A Review},
  journal = {Engineering and Applied Sciences},
  volume = {4},
  number = {6},
  pages = {144-148},
  doi = {10.11648/j.eas.20190406.12},
  url = {https://doi.org/10.11648/j.eas.20190406.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eas.20190406.12},
  abstract = {Weather is the condition of the atmosphere and forecasting is predicting the condition of the atmosphere in near future. Weather forecasting is a formidable challenge as weather is a multi- dimensional, continuous and chaotic process. The distinct nature of the model forecasting in all situations accurately is challenging. Presently weather conditions are being obtained from satellites, Doppler radar, radio sounds, observations from aircraft and ground. Collected data is subjected to various statistical and machine learning techniques. These techniques can incorporate relatively simple observation of the sky to highly complex computerized mathematical models. Weather forecasting still remains a challenging issue, due to unpredictable and chaotic nature of weather. Even with present methods the weather forecasting system may still fail to predict weather attribute, therefore there is still scope left to improve these systems. The objective of carrying out the survey is to look forward on how machine learning can help us to improve weather parameter estimation. In this paper we report the different methods carried out by leading researchers, formidable challenges and present our views on development of efficient weather forecasting system. Also, we propose a method which makes use image processing and neural networks to achieve the weather parameter estimation.},
 year = {2019}
}

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