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In the numerical forecasting system, there are calculation errors caused by both the physical modeling and estimation of initial values. Because numerical forecast data have two-dimensional spatial information, convolution with a convolutional neural network (CNN) is used to grasp and correct the two-dimensional features of errors contained in the forecast data. In the simulations, several MSM-GPV data used for the input data and various correction models are prepared and compared with the results of a fully connected neural network from the viewpoints of the error improvement rate and error distribution.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Research Institute of Signal Processing","subitem_publisher_language":"en"}]},"item_10001_source_id_9":{"attribute_name":"収録物ID","attribute_value_mlt":[{"subitem_source_identifier":"18801013","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_1715043197608":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open 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