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- TAKAHASHI Shinnosuke
- National Institute of Technology, Yonago College
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- GONDA Eiko
- National Institute of Technology, Yonago College
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- MIYATA Hitoshi
- National Institute of Technology, Yonago College
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- MAEDA Akihiro
- Environmental Sanitation Research Center, Tottori Prefecture
Bibliographic Information
- Other Title
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- 自己組織化マップを用いた湖山池の水質状況の予測
- ジコ ソシキカ マップ オ モチイタ コサンチ ノ スイシツ ジョウキョウ ノ ヨソク
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Description
<p> In recent years, in the Koyama-Lake in Tottori, the outbreak of the red tide becomes the problem that a sea mingled with fresh water.As a means to grasp the causal relation of the water quality condition of a lake, there is a method using a numerical model, but water quality simulation using numerical models requires understanding of factors that govern phenomena to be studied, and good results cannot be obtained unless an appropriate model is selected according to flow / water quality characteristics.In addition to this, there are few data on characteristics such as pressure and disturbance and it is difficult to handle, so if you are planning to use a numerical model, new facilities and capital investment may be necessary. Therefore, in is study, we classify the quality of the water and predict the quality of the water situation using Self-Organizing Maps.In this way, we can expect to help solution of the red tide outbreak mechanism, and expect to restrain damage of the red tide in predict the outbreak of the red tide beforehand.In the Self-Organizing Maps method, since new facilities and advanced mathematical knowledge are not required, it is possible to analyze the water quality situation from a comprehensive viewpoint simply by inputting the water quality data that has been acquired so far.</p>
Journal
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- Proceedings of the Fuzzy System Symposium
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Proceedings of the Fuzzy System Symposium 34 (0), 628-630, 2018
Japan Society for Fuzzy Theory and Intelligent Informatics
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Details 詳細情報について
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- CRID
- 1390001288107774976
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- NII Article ID
- 130007554350
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- NII Book ID
- AA12165648
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- ISSN
- 18820212
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- NDL BIB ID
- 029269868
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed