Decision support system architecture and method based on water conservancy knowledge-fact coupling network

Abstract

The invention discloses a decision support system architecture and method based on a water conservancy knowledge-factorial coupling network. The system comprises an inference mechanism module, a factorial map module, a rule base module and a water conservancy knowledge map module. Firstly, a water conservancy knowledge graph module and a related monitoring database are constructed; the rule base construction module comprises a rule base of an inference rule, an object rule and an attribute rule; the cause map module realizes cause maps associated with an inference rule base, an object rule base and an attribute rule base; the reasoning mechanism module realizes establishment of a reasoning framework running on a coupling network formed by combining a water conservancy knowledge graph and afact graph based on a rule base, reasoning is performed on a reasoning target on the reasoning framework, and finally decision support information pushing is completed; according to the method, causeanalysis and decision support are carried out on the target event in real time, and a real-time, accurate and efficient reasoning effect can be achieved.

Description

technical field [0001] The invention belongs to the application of knowledge graph, and in particular relates to a decision support system architecture and method based on water conservancy knowledge-event coupling network. Background technique [0002] The analysis of hydrological events and the calculation of hydrological elements have always been the key issues related to decision-making. At present, decision support methods generally use a single hydrological model for calculation, that is, given specific boundary conditions and calibration related model parameters, the values ​​of hydrological elements of the target entity and the state of the target event are estimated. This type of method assumes that under ideal conditions, various hydrological-related objects preset in the model are functioning normally, and the calculation results are determined by variable boundary conditions. However, hydrological events are complex and difficult to control, and the actual evolu...

AI Technical Summary

Problems solved by technology

The event map in this structural form can only show the probability of occurrence between events, and cannot accurately describe the evolution path and degree of quantification of events, which does not conform to the real situation.

For example, according to the existing knowledge, it can be obtained that regional rainfall causes urban waterlogging, but the existing reasoning method of event map cannot analyze the mechanism of regional rainfall impact and the degree of quantification, so it is difficult to make a decision support plan for the cause of urban waterlogging

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