Intelligent forecasting system for multi-factor karst collapse

Abstract

The invention discloses an intelligent forecasting system for multi-element karst collapse, which relates to the technical field of measurement and control and comprises a multi-element fusion module, a data dimension reduction module, a search module, a Bayesian classifier, a forecasting diagnosis module and an early warning output module. The input end of the multi-element fusion module is connected with the output end of a basic factor database, an induction factor database, a covering layer database, a dynamic condition database or an acid and alkali solution corrosion database through a data interface, and the output end of the multi-element fusion module is connected with the input end of the data dimension reduction module. The output end of the data dimension reduction module is connected with the input end of the search module, the output end of the search module is connected with the input end of the Bayesian classifier, the output end of the Bayesian classifier is connected with the input end of the forecast diagnosis module, and the output end of the forecast diagnosis module is connected with the input end of the early warning output module. According to the invention, the analysis capability of different geological data information is greatly improved.

Description

technical field [0001] The invention relates to the technical field of measurement and control, and more specifically to an intelligent forecasting system for multi-element karst collapse. Background technique [0002] Karst collapse refers to karst caves, overlying sediments and groundwater, which constitute a three-phase mechanical equilibrium system of solid, liquid and gas. Large and small conical collapse pits. Karst ground collapse is the main type of ground deformation and failure, and it mostly occurs in areas where soluble rocks such as carbonate rocks, calcareous clastic rocks and salt rocks are distributed. In addition to natural factors such as rainfall, floods, droughts and earthquakes, the direct causes of subsidence activities are often closely related to human factors such as pumping, drainage, water storage and other engineering activities. just big. Karst ground collapse is found in carbonate rock distribution areas, and its formation is influenced by bo...

AI Technical Summary

Problems solved by technology

[0004] How to realize the analysis of multiple elements and intelligent early warning has become a technical problem to be solved urgently. In the existing technology, the early warning of karst collapse is mostly analyzed manually and empirically. In factor analysis, how to quickly analyze specific factors from different factors and how to realize the classification of intelligent early warning is still not mentioned

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