@article{oai:niit.repo.nii.ac.jp:00000995,
 author = {飯野, 秋成 and 廣井, 俊介},
 journal = {新潟工科大学研究紀要, Bulletin of Niigata Institute of Technology},
 month = {Mar},
 note = {We investigated how to visualize and categorize hourly temperature and precipitation data nationwide using the past annual meteorological data observed by AMeDAS. First, by imaging the annual meteorological data of AMeDAS meteorological data, the features that can be visually read were organized. Next, based on the idea of a deep neural network, a concrete method for dimensionally compressing the imaged meteorological data using auto encoder was shown. Furthermore, we showed the process of cluster analysis of the results of dimensional compression, visualized the similarity of data between measurement points nationwide, and evaluated its validity.},
 pages = {26--33},
 title = {ニューラルネットワークを用いたアメダス気象データの類型化の試み},
 volume = {26},
 year = {2022}
}