A method for multi-hazard coupling model simulation driven by event chain

Abstract

The present invention discloses a method for deducing a multi-hazard coupling model driven by an event chain, comprising the following steps: S1, constructing event factors and event factor spectra including a three-level structure of disaster-causing factors, disaster-bearing carriers, and disaster-pregnant environments; S2, constructing a multi-hazard coupling model library; S3, determining the dangerous omen factors of the multi-hazard coupling event chain; S4, determining the utility relationship between each dangerous omen factor in the multi-hazard coupling event chain; S5, calculating the coupling degree between dangerous omen factors; S6, drawing a multi-hazard coupling event chain; S7, calculating the joint conditional probability distribution of the multi-hazard coupling event chain, establishing a multi-hazard coupling event chain reasoning principle, and completing the deduction of the multi-hazard coupling model. The present invention adopts an event chain approach to realize the deduction of the evolution process of the coupling of multiple primary disasters, and then predict the risk of multi-hazard coupling events.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-hazard coupling risk prediction, and in particular to a multi-hazard coupling model deduction method driven by an event chain. Background Art

[0002] There are cases where natural disasters trigger industrial disasters, which in turn lead to serious and major safety accidents. In 2008, a magnitude 8.0 earthquake occurred in Wenchuan, and the production and storage facilities of a large number of chemical companies were severely damaged. The sulfur settling tank of a fertilizer plant in Shifang City was damaged, causing the sulfur to catch fire and release a large amount of toxic SO2 smoke. More seriously, during this period, the bottom pipe of the spherical tank storing liquid ammonia in the plant area ruptured, causing about 400 tons of liquid ammonia to leak. In 2005, Hurricane Katrina landed in the southwestern United States, killing at least 1,833 people and severely damaging more than 400 factories. The leaked dangerous and toxic substances caused serious pollution to the environment. From these major accidents, it can be seen that the coupling of natural disasters with industrial and technological disasters such as fires, explosions, and poisoning often causes harm and losses far exceeding the natural disasters themselves.

[0003] The event chain reflects the homology, chain and rhythm between disaster events, and forms them into a whole of mutual relationship and interaction. The event chain method is applied to deal with various natural disaster accidents. David used the event chain to conduct a system dynamics analysis of the mining disaster in Nova Scotia, Canada in 1992, and described the causal structure and the relationship between the conditional elements that caused the mining disaster. Shi Peijun regards the disaster chain as a series of disaster phenomena caused by disaster factors. The disaster factors here may be natural causes (such as earthquakes, rainstorms, typhoons, etc.), human abnormalities (such as improper operation, deliberate destruction, etc.), or technical abnormalities (such as machine failure, parameter errors, etc.) and political and economic changes (such as financial crises, food crises, etc.). Wen Chuanjia believes that the disaster chain must be composed of more than two disasters, and there must be a causal relationship between the disasters. The disaster that serves as a guide or trigger in the front is defined as the starting disaster loop, and the disaster that is triggered later is defined as the passive disaster loop. Liu Wenfang studies the disaster nodes in the disaster chain as disaster subsystems and believes that the formation of the disaster chain is due to a series of interactions between disaster subsystems, and these interactions occur continuously on their own. Han Jinliang et al. classified and graded geological disaster chains, and divided geological disaster chains into internal dynamic geological disaster chains, external dynamic geological disaster chains, human engineering activities geological disaster chains, and composite geological disaster chains from the perspective of inducing factors. It can be seen from the existing literature that the application research on disaster chains is now mainly focused on natural disasters, and it is used in the deduction of the coupling relationship between multiple disasters. At present, there is still a lack of discussion on the dynamic coupling mechanism of natural disasters leading to industrial disasters. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for deducing a multi-hazard coupling model driven by an event chain. By adopting the event chain approach, the deduction of the evolution process of the coupling of multiple primary disasters is realized, and the risk of multi-hazard coupling events is predicted.

[0005] To achieve the above object, the technical solution provided by the present invention is: a multi-hazard coupling model deduction method driven by an event chain, comprising the following steps:

[0006] S1. Obtain a variety of typical natural disaster events, including rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accident events, decompose the above-mentioned typical natural disaster events into granularity, and construct event factors and event factor spectra with three-level structures including disaster-causing factors, disaster-bearing carriers, and disaster-pregnant environments;

[0007] S2. According to the event factors obtained in step S1, a multi-hazard coupling model library is constructed, including a vibration model, a rainstorm-waterlogging dynamics model, a soil consolidation settlement dynamics model, and a rigid body fatigue fracture and corrosion brittle fracture dynamics model;

[0008] S3, according to the multi-hazard coupling model library constructed in step S2, determining the dangerous omen factors in the multi-hazard coupling event chain consisting of rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accident events;

[0009] S4, determining the utility relationship between each dangerous omen factor in the multi-hazard coupling event chain according to the multi-hazard coupling model library constructed in step S3 and in combination with environmental parameters;

[0010] S5, calculating the coupling degree between the near-miss factors according to the utility relationship between the near-miss factors determined in step S4;

[0011] S6, according to the coupling degree between the dangerous factors determined in step S5, combined with the event factor spectrum obtained in step S1, determine the correlation between the dangerous factors, draw a multi-hazard coupling event chain, and determine the multi-hazard coupling event chain and the situation scenario units therein;

[0012] S7. According to the utility relationship of dangerous factors and based on the state transition theory, the state transition probability of the situation scenario unit is obtained, and then the joint conditional probability distribution of the multi-hazard coupling event chain is obtained, the reasoning principle of the multi-hazard coupling event chain is established, and the multi-hazard coupling model deduction is completed.

[0013] Further, in step S1, the following operations are specifically performed:

[0014] Obtain a variety of typical natural disaster events such as rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accidents, decompose the above-mentioned typical natural disaster events into granularity, determine the hazard factors and disaster carriers of each disaster event, and construct a disaster factor {S1…S i}、Disaster-bearing carrier {S1…S j} and disaster-prone environment {S1…S k The event factors and event factor spectrum of the three-level disaster structure of {S i ,S j ,S k}, where S i represents the ith disaster factor, S j represents the jth disaster-bearing carrier, S k represents the kth disaster event.

[0015] Further, in step S2, the following operations are specifically performed:

[0016] According to the event factors obtained in step S1, based on the principles of fluid mechanics, electricity, soil mechanics, and structural mechanics, a multi-hazard coupling model library is constructed, including a vibration model, a rainstorm-waterlogging dynamics model, a soil consolidation settlement dynamics model, a rigid body fatigue fracture and corrosion brittle fracture dynamics model.

[0017] Further, in step S3, the following operations are specifically performed:

[0018] Using semantic search to find the event factor spectrum of the three-level disaster structure i ,S j ,S k}, where S i represents the ith disaster factor, S j represents the jth disaster-bearing carrier, S k Represents the kth disaster event. When the event factor exists in both the disaster-causing factor and the disaster-bearing carrier, it is determined to be a dangerous omen factor R ij , R ij ∈{S i ,S j ,S k}, where ij represents the number of the near-miss factor, and a near-miss factor set {R ij}.

[0019] Further, in step S4, the following operations are specifically performed:

[0020] Based on the multi-hazard coupling model library in step S3, including the vibration model, the rainstorm-waterlogging dynamics model, the soil consolidation settlement dynamics model, the rigid body fatigue fracture and corrosion brittle fracture dynamics model, and the environmental variables, including temperature, humidity, rainfall, wind force, thunderstorm and earthquake intensity, the utility relationship between each dangerous omen factor in the multi-hazard coupling event chain is determined:

[0021]

[0022] Among them, u ij is the efficacy between the near-miss factors; is the ith disaster factor S calculated by the dynamic model i The jth disaster-bearing carrier S j The near miss factor R ij The coupling force of ij , α ij The upper and lower critical point limits of the preset dangerous sign factor.

[0023] Further, in step S5, the following operations are specifically performed:

[0024] According to the utility relationship between each dangerous sign factor, the coupling degree C between dangerous sign factors is calculated by referring to the coupling concept and model in physics. ij ,

[0025]

[0026] Among them, C ij u is the contribution of the first-coming scene unit to the later-coming scene unit, representing the coupling degree between dangerous omen factors; ij is the efficacy between the near-miss factors; i is the sequence number of the i-th near-miss factor in the first scenario unit, and j is the sequence number of the j-th near-miss factor in the second scenario unit.

[0027] Further, in step S6, the following operations are specifically performed:

[0028] According to the coupling degree between the dangerous factors determined in step S5, combined with the event factor spectrum obtained in step S1, the correlation between the dangerous factors is determined. When the coupling degree C between the relevant natural disaster events is ij If the value is greater than the standard value α, it is determined that there is a chain relationship between related natural disaster events, thus drawing a multi-hazard coupling event chain {A1, A2, …, A n}, determine the multi-hazard coupled event chain and the situation scenario unit A n , where A n Represents the nth situation scenario unit.

[0029] Further, in step S7, the following operations are specifically performed:

[0030] S701. Obtain the initial probability of the current environmental situation scenario unit according to the initial value of the disaster factor parameter Where R ij,0 Represents the initial hazard factor parameter of the nth situation scenario unit;

[0031] S702, according to the initial probability of the situation scenario unit and the utility relationship between the dangerous omen factors, the state transition probability P(A n |A n-1 ,…,A1),

[0032]

[0033] in, R represents the disaster factor ij After being affected by the utility relationship, the nth situation scenario unit A n The probability of occurrence, P(A n |A n-1 ,…,A1) represents the state transition probability of the nth situation scenario unit;

[0034] S703, according to the state transition probability of the situation scenario unit, calculate the joint conditional probability distribution P(A1,…,A n ), that is, the comprehensive risk of multi-hazard coupled event chains,

[0035] P(A1,…,A n )=∏ n P(A2|A1)P(A3|A2,A1)…P(A n |A1,…,A n-1 ),

[0036] According to the joint conditional probability distribution of multi-hazard coupling event chains, the reasoning principle of multi-hazard coupling event chains is established to complete the deduction of the multi-hazard coupling model.

[0037] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0038] The present invention adopts an event chain approach to target multi-disaster coupled events, realizes the deduction of the evolution process of the coupling of multiple primary disasters, predicts the development outcomes of multi-disaster coupled events, and completes real-time, online multi-disaster coupled event chain deduction, making it convenient to prepare for and respond to disasters that may be induced by various natural disasters in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flowchart of the present invention.

[0040] Figure 2This is the event factor spectrum of heavy rain events.

[0041] Figure 3 This is the event factor spectrum of geological disaster events.

[0042] Figure 4 This is the event factor spectrum of lightning events.

[0043] Figure 5 This is the event factor spectrum of urban flood disaster events.

[0044] Figure 6 This is the event factor spectrum of urban lifeline infrastructure accidents.

[0045] Figure 7 This is a schematic diagram of the situation scenario unit under the multi-hazard coupled event chain. DETAILED DESCRIPTION

[0046] The present invention is further described below in conjunction with specific embodiments, but the use of the present invention is not limited thereto.

[0047] like Figures 1 to 7 As shown, the event chain driven multi-hazard coupling model deduction method described in this embodiment includes the following steps:

[0048] S1. Obtain a variety of typical natural disaster events, including rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accident events. Decompose the above typical natural disaster events into granularity, and construct event factors and event factor spectra with three-level structures including disaster-causing factors, disaster-bearing carriers, and disaster-pregnant environments. Specifically, perform the following operations:

[0049] Five typical natural disaster events, namely, rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accidents, were obtained. According to the "National Emergency Platform System Emergency Event Classification and Coding Specifications", the above five typical natural disaster events were decomposed to determine the hazard factors and disaster carriers of each disaster event, and a disaster factor {S1…S i}、Disaster-bearing carrier {S1…S j} and disaster-prone environment {S1…S k The event factors and event factor spectrum of the three-level disaster structure of {S i ,S j ,S k}, where S i represents the ith disaster factor, S j represents the jth disaster-bearing carrier, S k represents the kth disaster event.

[0050] S2. According to the event factors obtained in step S1, a multi-hazard coupling model library including a vibration model, a rainstorm-waterlogging dynamics model, a soil consolidation settlement dynamics model, and a rigid body fatigue fracture and corrosion brittle fracture dynamics model is constructed. Specifically, the following operations are performed:

[0051] According to the event factors obtained in step S1, a multi-hazard coupling model library including a vibration model, a rainstorm-waterlogging dynamics model, a soil consolidation settlement dynamics model, a rigid body fatigue fracture and corrosion brittle fracture dynamics model is constructed according to the principles of fluid mechanics, electricity, soil mechanics, and structural mechanics;

[0052] Dynamic relationship between heavy rain and urban groundwater level:

[0053]

[0054] Among them, △h represents the change of groundwater level; Q r represents rainfall; S represents the infiltration area; n represents the number of infiltration paths; q i represents rainfall intensity; ψ represents permeability coefficient; t represents rainfall time;

[0055] Dynamic relationship between soil displacement and soil stress:

[0056]

[0057]

[0058]

[0059] Where u represents the surface velocity of the soil unit; G represents the shear modulus of the soil; w x ,w y ,w z Respectively represent the soil displacement in the x, y, and z directions; γ z Indicates the specific gravity in the z direction.

[0060] The dynamic relationship between soil effective stress and soil strain in the three-dimensional space {x, y, z}:

[0061]

[0062]

[0063] Among them, ε v represents the soil volume strain; ε x ,ε y ,ε z represents the positive strain in the x, y, and z directions of the soil volume; σ′ x ,σ′ y ,σ′ zrepresents the effective normal stress in the soil in the x, y, and z directions; τ xy ,τ yz ,τ xz represents the unit penetration force in the x, y, and z directions, γ xy ,γ yz ,γ xz represents the shear strain in the x, y, and z directions.

[0064] Dynamic relationship between soil stress and stress wave:

[0065] σ′ x =σ″ x / D ε

[0066] σ′ y =σ″ y / D ε

[0067] σ′ z =σ″ z / D ε

[0068] Among them, σ″ x ,σ″ y ,σ″ z It represents the soil stress in the x, y, and z directions of the soil after propagation attenuation in the soil; D ε It represents the soil stress wave attenuation coefficient, where ε represents the Dake number, ε=(2+σ) / (1-σ), and σ represents the soil stress diffusion coefficient.

[0069] The dynamic relationship between soil effective stress and stress wave and rigid body fatigue brittle fracture life is established according to the Smith-Watson-Topper criterion.

[0070] S3. According to the multi-hazard coupling model library constructed in step S2, determine the dangerous omen factors in the multi-hazard coupling event chain consisting of rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accident events, and specifically perform the following operations:

[0071] Using semantic search to find the event factor spectrum of the three-level disaster structure i ,S j ,S k}, where S i represents the ith disaster factor, S j represents the jth disaster-bearing carrier, S k Represents the kth disaster event. When the event factor exists in both the disaster-causing factor and the disaster-bearing carrier, it is determined to be a dangerous omen factor R ij , and then establish a set of near miss factors

[0072] S4. According to the multi-hazard coupling model library constructed in step S3, combined with environmental parameters, determine the utility relationship between various dangerous omen factors in the multi-hazard coupling event chain, and specifically perform the following operations:

[0073] Based on the dynamic model in step S3, the coupling force between the rainstorm event and the ground subsidence event is calculated. Coupling force between ground subsidence and gas pipeline leakage And the coupling force between gas pipeline leakage and gas explosion Then, combined with environmental variables, including temperature, humidity, rainfall, wind speed, thunderstorms, and earthquake intensity, the utility relationship u between each dangerous omen factor in the multi-hazard coupling event chain is first determined. ij :

[0074]

[0075] Among them, u ij is the efficacy between the near-miss factors; is the ith disaster factor S calculated by the dynamic model i The jth disaster-bearing carrier S j The near miss factor R ij The coupling force of ij , α ij The upper and lower critical point limits of the preset dangerous factor;

[0076] Then we get the utility relation set u,

[0077]

[0078] S5. According to the utility relationship between the near-miss factors determined in step S4, the coupling degree between the near-miss factors is calculated, and the following operations are specifically performed:

[0079] According to the utility relationship between each dangerous sign factor, the coupling degree C between dangerous sign factors is calculated by referring to the coupling concept and model in physics. ij ,

[0080]

[0081] Among them, C ij u is the contribution of the first-coming scene unit to the later-coming scene unit, representing the coupling degree between dangerous omen factors; ij is the efficacy between the near-miss factors; i is the sequence number of the i-th near-miss factor in the first scenario unit, and j is the sequence number of the j-th near-miss factor in the second scenario unit.

[0082] Then we get the coupling degree set C of the dangerous factors,

[0083]

[0084] S6. According to the coupling degree between the dangerous factors determined in step S5, combined with the event factor spectrum obtained in step S1, the correlation between the dangerous factors is determined, a multi-hazard coupling event chain is drawn, and the multi-hazard coupling event chain and the situation scenario units therein are determined. Specifically, the following operations are performed:

[0085] According to the coupling degree between the dangerous factors determined in step S5, combined with the event factor spectrum obtained in step S1, the correlation between the dangerous factors is determined. When the coupling degree C between the relevant natural disaster events is ij If the value is greater than the standard value α, it is determined that there is a chain relationship between the related natural disaster events, thus drawing a multi-hazard coupling event chain {A1, A2, …, A n}, the multi-hazard coupling event chain of this embodiment is specifically {A 暴雨事件 ,A 地面沉降事件 ,A 燃气管网泄露事件 ,A 燃气爆炸事件}.

[0086] S7. According to the utility relationship of dangerous factors and based on the state transition theory, the state transition probability of the situation scenario unit is obtained, and then the joint conditional probability distribution of the multi-hazard coupling event chain is obtained, the multi-hazard coupling event chain reasoning principle is established, and the multi-hazard coupling model deduction is completed. Specifically, the following operations are performed:

[0087] S701. Obtain the initial probability of the current environmental situation scenario unit according to the initial value of the disaster factor parameter Where R ij,0 Represents the initial hazard factor parameter of the nth situation scenario unit;

[0088] S702, according to the initial probability of the situation scenario unit and the utility relationship between the dangerous omen factors, the state transition probability P(A n |A n-1 ,…,A1),

[0089]

[0090] in, R represents the disaster factor ij After being affected by the utility relationship, the nth situation scenario unit A n The probability of occurrence, P(A n |A n-1 ,…,A1) represents the state transition probability of the nth situation scenario unit;

[0091] S703, according to the state transition probability of the situation scenario unit, calculate the joint conditional probability distribution P(A1,…,A n ), that is, the comprehensive risk of multi-hazard coupled event chains,

[0092] P(A1,…,A n )=∏ n P(A2|A1)P(A3|A2,A1)…P(A n |A1,…,A n-1 )

[0093] According to the joint conditional probability distribution of multi-hazard coupling event chains, the reasoning principle of multi-hazard coupling event chains is established to complete the deduction of the multi-hazard coupling model.

[0094] The present invention adopts an event chain approach to target multi-disaster coupled events, realizes the deduction of the evolution process of the coupling of multiple primary disasters, predicts the development outcomes of multi-disaster coupled events, and completes real-time, online multi-disaster coupled event chain deduction, making it convenient to prepare for and respond to disasters that may be induced by various natural disasters in a timely manner.

[0095] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, all changes made according to the shape and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. The multi-hazard coupling model deduction method driven by event chain is characterized by: The following steps are involved: S1. Obtain five typical natural disaster events, namely, rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accident events. Decompose the above five typical natural disaster events into granularity, and construct event factors and event factor spectra with three-level structures including disaster-causing factors, disaster-bearing carriers, and disaster-pregnant environments; S2. According to the event factors obtained in step S1, a multi-hazard coupling model library is constructed, including a vibration model, a rainstorm-waterlogging dynamics model, a soil consolidation settlement dynamics model, and a rigid body fatigue fracture and corrosion brittle fracture dynamics model; S3, according to the multi-hazard coupling model library constructed in step S2, determining the dangerous omen factors in the multi-hazard coupling event chain consisting of rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accident events; S4. According to the multi-hazard coupling model library constructed in step S2, combined with environmental parameters, determine the utility relationship between various dangerous omen factors in the multi-hazard coupling event chain; specifically, perform the following operations: Based on the multi-hazard coupling model library in step S2, including the vibration model, the rainstorm-waterlogging dynamics model, the soil consolidation settlement dynamics model, the rigid body fatigue fracture and corrosion brittle fracture dynamics model, and the environmental variables, including temperature, humidity, rainfall, wind force, thunderstorm and earthquake intensity, the utility relationship between each dangerous omen factor in the multi-hazard coupling event chain is determined: Among them, u ij is the efficacy between the risk factors; is the ith disaster factor S calculated by the dynamic model i The jth disaster-bearing carrier S j The near miss factor R ij The coupling force of ij , α ij The upper and lower critical point limits of the preset dangerous factor; S5, calculating the coupling degree between the near-miss factors according to the utility relationship between the near-miss factors determined in step S4; S6, according to the coupling degree between the dangerous factors determined in step S5, combined with the event factor spectrum obtained in step S1, determine the correlation between the dangerous factors, draw a multi-hazard coupling event chain, and determine the multi-hazard coupling event chain and the situation scenario units therein; S7. According to the utility relationship of dangerous factors and based on the state transition theory, the state transition probability of the situation scenario unit is obtained, and then the joint conditional probability distribution of the multi-hazard coupling event chain is obtained, the reasoning principle of the multi-hazard coupling event chain is established, and the multi-hazard coupling model deduction is completed.

2. The method for deducing a multi-hazard coupling model driven by an event chain according to claim 1, characterized in that: In step S1, the following operations are specifically performed: Five typical natural disaster events, namely, rainstorm events, geological disaster events, lightning events, waterlogging disaster events, and urban lifeline infrastructure accident events, are obtained. The above five typical natural disaster events are decomposed into granularity to determine the hazard factors and disaster carriers of each disaster event. The disaster factor {S1…S i }、Disaster-bearing carrier {S1…S j } and disaster-prone environment {S1…S k The event factors and event factor spectrum of the three-level disaster structure of {S i ,S j ,S k }, where S i represents the ith disaster factor, S j represents the jth disaster-bearing carrier, S k represents the kth disaster event.

3. The method for deducing a multi-hazard coupling model driven by an event chain according to claim 1, characterized in that: In step S2, the following operations are specifically performed: According to the event factors obtained in step S1, based on the principles of fluid mechanics, electricity, soil mechanics, and structural mechanics, a multi-hazard coupling model library is constructed, including a vibration model, a rainstorm-waterlogging dynamics model, a soil consolidation settlement dynamics model, a rigid body fatigue fracture and corrosion brittle fracture dynamics model.

4. The method for deducing a multi-hazard coupling model driven by an event chain according to claim 1, characterized in that: In step S3, the following operations are specifically performed: Using semantic search to find the event factor spectrum of the three-level disaster structure i ,S j ,S k }, where S i represents the ith disaster factor, S j represents the jth disaster-bearing carrier, S k Represents the kth disaster event. When the event factor exists in both the disaster-causing factor and the disaster-bearing carrier, it is determined to be a dangerous omen factor R ij , R ij ∈{S i ,S j ,S k }, where ij represents the number of the near-miss factor, and a near-miss factor set {R ij }.

5. The method for deducing a multi-hazard coupling model driven by an event chain according to claim 4, characterized in that: In step S5, the following operations are specifically performed: According to the utility relationship between each dangerous sign factor, the coupling degree C between dangerous sign factors is calculated by referring to the coupling concept and model in physics. ij , Among them, C ij u is the contribution of the first-coming scene unit to the later-coming scene unit, representing the coupling degree between dangerous omen factors; ij is the efficacy between the near-miss factors; i is the sequence number of the i-th near-miss factor in the first scenario unit, and j is the sequence number of the j-th near-miss factor in the second scenario unit.

6. The method for deducing a multi-hazard coupling model driven by an event chain according to claim 5, characterized in that: In step S6, the following operations are specifically performed: According to the coupling degree between the dangerous factors determined in step S5, combined with the event factor spectrum obtained in step S1, the correlation between the dangerous factors is determined. When the coupling degree C between the relevant natural disaster events is ij If the value is greater than the standard value α, it is determined that there is a chain relationship between related natural disaster events, thus drawing a multi-hazard coupling event chain {A1, A2, …, A n }, determine the multi-hazard coupled event chain and the situation scenario unit A n , where A n Represents the nth situation scenario unit.

7. The method for deducing a multi-hazard coupling model driven by an event chain according to claim 6, characterized in that: In step S7, the following operations are specifically performed: S701. Obtain the initial probability of the current environmental situation scenario unit according to the initial value of the disaster factor parameter Where R ij,0 Represents the initial hazard factor parameter of the nth situation scenario unit; S702, according to the initial probability of the situation scenario unit and the utility relationship between the dangerous omen factors, the state transition probability P(A n |A n-1 ,…,A1), in, R represents the disaster factor ij After being affected by the utility relationship, the nth situation scenario unit A n The probability of occurrence, P(A n |A n-1 ,…,A1) represents the state transition probability of the nth situation scenario unit; S703, according to the state transition probability of the situation scenario unit, calculate the joint conditional probability distribution P(A1,…,A n ), that is, the comprehensive risk of multi-hazard coupled event chains, P(A1,…,A n )=∏ n P(A2|A1)P(A3|A2,A1)…P(A n |A1,…,A n-1 ) According to the joint conditional probability distribution of multi-hazard coupling event chains, the reasoning principle of multi-hazard coupling event chains is established to complete the deduction of the multi-hazard coupling model.

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