A method of water resources accounting based on deep clustering and attention mechanism under the background of integration of public health data and environmental economy.

ABSTRACT: Water resource accounting constitutes a fundamental approach for implementing sophisticated management of basin water resources. The quality of water plays a pivotal role in determining the liabilities associated with these resources. Evaluating the quality of water facilitates the computation of water resource liabilities during the accounting process. Traditional accounting methods rely on manual sorting and data analysis, which necessitate significant human effort. In order to address this issue, we leverage the remarkable feature extraction capabilities of convolutional operations to construct neural networks. Moreover, we introduce the self-attention mechanism module to propose an unsupervised deep clustering method. This method offers assistance in accounting tasks by automatically c

SUBMITTER: Zhou S 

PROVIDER: S-EPMC10557482 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature