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Examination of Water Temperature Accuracy Improvement Method for Forecast

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1371))

Abstract

In aquaculture, fishery workers and researchers attach great importance to water temperature. This is because knowing the water temperature makes it possible to take measures against fish diseases and predict the occurrence of red tide. In collaboration with fishery researchers, we constructed a multi-depth sensor network consisting of 16 water temperature observation devices over the Uwa Sea in Ehime Prefecture. In addition, we developed a Web system that can instantly visualize the water temperature measured on this network and provide it to fishery workers in the Uwa Sea. However, the water temperature information provided by this Web system is only current or past information, and fishery workers are requiring the provision of near-future water temperature forecasts for a week or two weeks. Therefore, in this research, as a new function of this Web system, we will implement a function to predict the water temperature in the near future from the past water temperature information and provide the forecast information. This paper examines the steps to be solved for the prediction of seawater temperature, which is the current problem in this system. Moreover, among the steps, this paper reports on the solution method and its evaluation experiment for improving the accuracy of water temperature information.

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Correspondence to Yu Agusa .

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Agusa, Y., Endo, K., Kuroda, H., Kobayashi, S. (2021). Examination of Water Temperature Accuracy Improvement Method for Forecast. In: Hong, TP., Wojtkiewicz, K., Chawuthai, R., Sitek, P. (eds) Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2021. Communications in Computer and Information Science, vol 1371. Springer, Singapore. https://doi.org/10.1007/978-981-16-1685-3_2

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  • DOI: https://doi.org/10.1007/978-981-16-1685-3_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1684-6

  • Online ISBN: 978-981-16-1685-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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