Hydrogen storage material database construction method based on artificial intelligence technology

Abstract

The invention discloses a hydrogen storage material database construction method based on an artificial intelligence technology. The method is realized through the following nine steps: 1, query and arrangement of papers; 2, downloading and filing the papers; 3, text format conversion; 4, text preprocessing; 5, chemical named entity recognition; 6, text classification; 7, text relation extraction; 8, performing ternary filing; and 9, multi-terminal storage. Compared with the prior art, the method solves the following problems: 1, the problem that the database data source is single is solved, that is, the data is obtained from the public papers; 2, the problem that database data collection depends on manpower is solved, that is, automatic data extraction is realized through an artificial intelligence technology; and 3, the problem of single database application is solved.

Description

technical field [0001] The invention relates to the technical field of database maintenance, in particular to a method for constructing a database of hydrogen storage materials based on artificial intelligence technology. Background technique [0002] With the introduction of the concept of material genetic engineering and the development of modern artificial intelligence technology, the combination of big data, machine learning and material science has become a hot research topic at home and abroad in recent years; a large amount of research data can be obtained from scientific research papers. Manual data extraction is time-consuming, labor-intensive and error-prone, and it is necessary to use machines instead of manual labor; therefore, we have developed an artificial intelligence-based automated extraction tool for paper data, and proposed a method that can automatically supplement rich data The method is used to construct and improve the database of hydrogen storage mat...

AI Technical Summary

Problems solved by technology

[0023] Use artificial intelligence technology to extract valuable high-quality data from hydrogen storage material papers to build a hydrogen storage material database to solve the problem that the original hydrogen storage material database relies on manual collection, which is time-consuming and laborious and is affected by subjective factors, resulting in a low correct rate and, on this basis, use the big data machine learning method based on artificial intelligence technology to predict the performance parameters of hydrogen storage materials and shorten the research and development cycle of new hydrogen storage materials

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