CN-122022063-A - Multi-disaster coupled geological disaster emergency collaborative decision and resource scheduling optimization system

CN122022063ACN 122022063 ACN122022063 ACN 122022063ACN-122022063-A

Abstract

The invention discloses a multi-disaster coupled geological disaster emergency collaborative decision and resource scheduling optimization system, which belongs to the technical field of emergency management and disaster decision, and comprises a disaster chain time-space evolution deduction module, a multi-objective collaborative optimization scheduling module, a closed-loop feedback dynamic correction module, a situation awareness visualization decision module and a multi-dimensional visualization interface support cross-department flattened collaborative command, wherein the disaster chain time-space evolution deduction module is used for constructing a disaster chain topological graph based on a multi-disaster coupled relation, outputting a time-space evolution track and a cascade influence range of a disaster chain through a time-space Bayesian deduction method, the multi-objective collaborative optimization scheduling module is used for carrying out multi-objective collaborative optimization solution by combining a plurality of constraint conditions such as a rescue time window, road traffic capacity, resource point distribution, disaster point demand urgency and the like, the closed-loop feedback dynamic correction module is used for fusing the multi-source real-time feedback data dynamic correction influence range and a scheduling scheme, and the situation awareness visualization decision module is used for generating a multi-dimensional visualization interface support cross-department flattened collaborative command.

Inventors

ZHANG YUTING
KONG FANYE
LI SHIXIANG
HUANG LI
SU LILAN
LI YE
LI SHUHUI
ZHANG HONGYU

Assignees

中国地质大学（武汉）

Dates

Publication Date: 20260512
Application Date: 20260224

Claims (10)

1. The multi-disaster coupled geological disaster emergency collaborative decision and resource scheduling optimization system is characterized by comprising the following steps: The disaster chain space-time evolution deduction module is used for receiving multi-source disaster condition data, constructing a disaster chain topological graph based on multi-disaster type coupling relation, calculating triggering probability and propagation delay among various disaster types through a space-time Bayesian deduction method, and outputting a space-time evolution track and a cascade influence range of the disaster chain; The multi-target collaborative optimization scheduling module is used for receiving the space-time evolution track and the cascade influence range, and carrying out multi-target collaborative optimization solution by combining multi-constraint conditions, wherein the multi-constraint conditions comprise rescue time windows, road traffic capacity, resource point distribution and disaster point demand urgency, and outputting dynamic scheduling schemes of personnel, materials and equipment; The closed-loop feedback dynamic correction module is used for receiving and fusing multi-source real-time feedback data, dynamically correcting the cascade influence range and the loss evaluation according to real-time disaster variation, and feeding the correction result back to the disaster chain space-time evolution deduction module and the multi-target collaborative optimization scheduling module to realize the dynamic update of a scheduling scheme; and the situation awareness visualization decision module is used for receiving the dynamic scheduling scheme and the correction result, generating a multidimensional visualization interface comprising a disaster situation map, a resource deployment map and a rescue progress map, and supporting cross-department and cross-level flattened collaborative command.
2. The system of claim 1, wherein in the disaster chain space-time evolution deduction module, nodes of the disaster chain topological graph represent different disaster types, edges represent trigger relations among disaster types, and weights of the edges comprise trigger probability and propagation delay parameters.
3. The system of claim 1, wherein the rescue time window employs a soft time window constraint in the multi-objective co-optimized scheduling module comprising three time thresholds of earliest response time, expected completion time, and maximum tolerated time.
4. The system of claim 1, wherein in the closed-loop feedback dynamic correction module, the correction period is adaptively adjusted according to the emergency degree of the disaster, the value range is 5min to 15min when the disaster is in a rapid evolution stage, and the value range is 30min to 60min when the disaster is stabilized.
5. The system of claim 1, wherein the disaster chain space-time evolution deduction module calculates occurrence probability of the secondary disaster through conditional probability propagation by using a space-time bayesian network model, and determines a time delay parameter and a space expansion coefficient of disaster propagation based on statistical data of a historical case base.
6. The system of claim 1, wherein in the multi-objective collaborative optimization scheduling module, the urgency of the disaster point demand is quantified by an exponential decay function based on a time window, and the urgency decay coefficient is dynamically adjusted according to disaster type and number of people suffering from the disaster.
7. The system of claim 1, wherein the multi-objective collaborative optimization scheduling module employs an improved NSGA-III algorithm for multi-objective solution, balancing rescue response time, rescue coverage, resource utilization balance, and urgency weighted response with reference point adaptive adjustment policies.
8. The system of claim 1, wherein the closed-loop feedback dynamic correction module fuses multi-source feedback data from social media, unmanned aerial vehicle images, and field personnel reporting using D-S evidence theory, and incrementally updates the cascade impact range by correction factors.
9. The system of claim 1, wherein the closed loop feedback dynamic correction module comprises a multi-source data fusion engine for performing space-time alignment, conflict resolution, and confidence assessment processing on multi-source real-time feedback data.
10. The system of claim 1, wherein the situational awareness visualization decision module comprises a cross-department collaboration interface supporting data exchange and instruction delivery with emergency management, transportation, health, communications security departments.

Description

Multi-disaster coupled geological disaster emergency collaborative decision and resource scheduling optimization system Technical Field The invention relates to the technical field of emergency management and disaster decision, in particular to a multi-disaster-coupled geological disaster emergency collaborative decision and resource scheduling optimization system. Background The geological disasters have the characteristics of strong burst, large destructive power and multiple secondary disasters, and particularly in mountain areas, single geological disasters often cause chain reactions to form complex disaster chains. For example, heavy rainfall can induce landslide, a landslide body forms a barrier lake after blocking a river channel, the barrier lake breaks down to cause downstream flood to flood, and the cascade effect of multi-disaster coupling enlarges the disaster influence range and the loss degree in geometric progression. Therefore, how to quickly and scientifically generate an emergency plan and efficiently schedule rescue resources after a disaster occurs has become a key technical problem to be solved in the field of emergency management. The Chinese patent with the publication number of CN119741180A discloses a disaster prevention emergency communication command management system based on a lead-through technology, which comprises a data acquisition and fusion module, a disaster evolution prediction module, a resource scheduling optimization module, a command decision module and a communication guarantee module. The system processes multi-source data by adopting a dynamic weighted fusion algorithm, predicts disaster evolution trend by adopting an NSGA-II multi-objective optimization algorithm, and generates a resource scheduling scheme based on a double-objective optimization model. However, the prior art has the following defects that firstly, disaster evolution prediction is only carried out on a single disaster, coupling relation and cascading effect among multiple disasters are not considered, space-time evolution tracks of a disaster chain cannot be accurately deduced, secondly, resource scheduling optimization adopts a simple double-target model, only two targets of scheduling time and benefits are considered, multiple practical constraint conditions such as rescue time window constraint, road traffic capacity dynamic change, disaster point demand urgency difference and the like cannot be comprehensively considered, thirdly, an effective closed loop feedback mechanism is lacked, influence range assessment and resource scheduling scheme cannot be dynamically corrected according to real-time disaster feedback, and fourth, visual decision support functions are limited, so that the actual requirements of cross-department and cross-level flattening collaborative command are difficult to meet. In addition, in the prior art, a static optimization model is mostly adopted for the research on emergency resource scheduling, and the disaster information is assumed to be completely known and not changed with time, which is not in accordance with the characteristics of dynamic evolution of the disaster and gradual clear information in the actual disaster scene. The existing researches have the defect in the aspect of road traffic capacity evaluation, and most of the researches assume that the road network state is fixed and the damage of disasters to road infrastructure and the influence of rescue activities to road congestion conditions cannot be considered. In summary, the prior art has obvious technical blank in aspects of multi-disaster coupling deduction, multi-constraint collaborative optimization, closed-loop dynamic correction, cross-department collaborative visualization and the like, and is difficult to meet the actual requirements of emergency collaborative decision and resource scheduling in complex geological disaster scenes. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a multi-disaster coupled geological disaster emergency collaborative decision and resource scheduling optimization system, which forms a deep coupled closed loop collaborative system by constructing a disaster chain space-time evolution deduction module, a multi-target collaborative optimization scheduling module, a closed loop feedback dynamic correction module and a situation awareness visualization decision module, and solves the technical problems of insufficient deduction of multi-disaster cascade effect, insufficient optimization of multi-constraint conditions, insufficient dynamic feedback correction and difficult cross-department collaboration in the prior art. The technical scheme adopted by the invention is as follows: The multi-disaster-coupled geological disaster emergency collaborative decision and resource scheduling optimization system comprises a disaster chain space-time evolution deduction module, a multi-target collaborative optimization scheduling module, a cl