A shield intelligent auxiliary selection system and method based on a large language model

Abstract

The application provides a shield intelligent auxiliary selection system and method based on a large language model. The selection system comprises a data input module, a rule knowledge base module, a large model reasoning module and a result generation module. The application is aimed at the real problems in shield construction, such as complex geological conditions, multiple constraints, high dependence on experts and the like, and an integrated decision system is constructed by combining a rule knowledge base, a deep learning model and expert system logic. The system combines structured selection rules and historical case data, has intelligentization, standardization and self-learning capability, solves the problems of low efficiency, strong subjectivity and insufficient intelligence in the existing shield machine selection which depends on artificial experience and part of standardized guidelines, and can promote the transformation of shield construction management from artificial experience to intelligent decision.

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