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  6. [We accept inquiries for development] Development of cloud sea forecasting using AI technology.

[We accept inquiries for development] Development of cloud sea forecasting using AI technology.

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last updated:Feb 09, 2023

山口ティー・エル・オー
山口ティー・エル・オー
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"Will the sea of clouds be visible tomorrow?" Automatic forecast at least the day before.

The "sea of clouds," which can only be seen when multiple conditions such as weather conditions, humidity in the atmosphere, temperature changes, mainly during early morning hours, and elevation are met, lacks established prediction technology, making it difficult to witness even when one actually goes to the location. Therefore, we have developed a technology that utilizes AI (machine learning), which has rapidly advanced in recent years, to predict sea of clouds at local tourism spots. This technology can predict sea of clouds using only weather data from the Japan Meteorological Agency's AMeDAS, making it applicable anywhere in the country as long as there is an AMeDAS observation point nearby. Please feel free to consult us first. ■ Features - Predicts the probability of sea of clouds occurring over a relatively wide area (region) - Predictions can be made based solely on data publicly available from the Japan Meteorological Agency - A system equipped with weather data acquisition means and sea of clouds prediction means - Utilizes machine learning by computers - The prediction accuracy for model cases has a hit rate of up to 81.8%

    Prototype Services
理大雲海 メイン画像3.png

[We accept inquiries for development] Development of cloud sea forecasting using AI technology.

理大雲海 メイン画像3.png
理大雲海 メイン画像3.png
  • Related Link - https://renkei.office.ous.ac.jp/

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【University-initiated Business Partner Recruitment - Feel free to consult with us】 ■Okayama University of Science, Faculty of Biological and Earth Sciences ■Patent Pending - Cloud formation prediction system, cloud formation prediction method, and cloud formation prediction program (Patent Application No. 2022-080258) ■Prediction Accuracy of Model Case - The prediction area is the city of Miki in Hiroshima Prefecture and its surroundings, with Takaya Mountain Observatory as the observation point. - A trained model was created based on weather data from the Miki Regional Weather Observatory and Takano Regional Weather Observatory, as well as live camera data from Takaya Mountain Observatory. - The average prediction accuracy rate is approximately 77.9%, the median is approximately 78.4%, the first quartile is approximately 76.9%, the third quartile is approximately 80.4%, the minimum is 69.6%, and the maximum is 81.8%.

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Local governments, related facilities, travel agencies, rental car companies, railway and bus companies, and enthusiasts of climbing, photography, and travel, please feel free to contact us.

Detailed information

  • 理大雲海 スライド1.png

    Developed a method for automatically forecasting the occurrence of sea of clouds using AI (machine learning).

  • 理大雲海 2サブ画像1.png

    The mechanism of cloud sea forecasting.

  • 理大雲海 3サブ画像2.png

    Forecast results for the probability of cloud sea occurrence.

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Development of Cloud Sea Forecasting Using AI Technology [Research Material]

Development of Cloud Sea Forecasting Using AI Technology [Research Material]

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山口ティー・エル・オー

山口ティー・エル・オー

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Yamaguchi TLO Co., Ltd. is a TLO approved by the Ministry of Education, Culture, Sports, Science and Technology and the Ministry of Economy, Trade and Industry based on the Act on the Promotion of Technology Transfer from Universities, established in November 1999 with investments from 50 faculty members of Yamaguchi University (capital of 4 million yen) before incorporation. It is a liaison-type technology transfer organization that bridges people. We return the research results from the university to society in the form of technology transfer and other means. Additionally, we are actively recruiting member companies to prioritize the disclosure of invention information and contribute to the development of the local economy through these efforts.

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