Five-layer hierarchical network(5-HiNet)of geospatial information service for AIGC of geographic analysis model
Within the context of artificial intelligence generation(AIGC)and large language model(LLM),improving the in-telligence level of generating geographic analysis models has gained widespread attention in the field.This paper proposes a geospatial information service hierarchical network model,named 5-HiNet.This model allows for a step-by-step description of heterogeneous geographic analysis models based on the five-layer hierarchical sub-network structure of demand description,ab-stract model,functional module,service interface,and functional instance,which depicts the realization process of geographic analysis models from the general to the specific.Within the five-layer hierarchical sub-network structure,the 5-HiNet can in-tegrate massive expert knowledge embedded in the geographic analysis models and thus form a well-rounded domain knowledge system.Furthermore,the 5-HiNet can be coupled with the LLM to generate geographic analysis models automatically.A pro-totype system with a case study is developed in this paper to demonstrate the feasibility of the proposed 5-HiNet,and several research directions and insights for future study are provided.
geospatial information servicegeographic analysis modelhierarchical networkdomain knowledgeintelligent generation
万方数据
维普
