A method for classifying port disaster risk levels

Abstract

The present invention discloses a method for classifying the risk levels of port disasters, which relates to the technical field of risk level classification. On the existing basis, the present invention further considers the comprehensive correlation coefficients among all consequences in each disaster type in a data-driven manner to ensure that the correlation factors among different consequences can be comprehensively considered. At the same time, by analyzing and calculating the first and second composite indices of each disaster type and obtaining the third composite index on the basis of combining the first and second composite indices, the complexity factors of the consequences of each disaster type are effectively considered. Finally, the obtained results are incorporated into the existing calculation formula of the expected loss value to ensure that a more accurate, comprehensive and scientific expected loss value is obtained. This enables the subsequent occurrence probability of misjudging the risk level to be effectively reduced to the greatest extent even when determining the risk levels of disaster types with the same coordinates.

Description

Technical Field

[0001] The present invention relates to the technical field of risk level classification, and in particular to a method for classifying port disaster risk levels. Background Art

[0002] The method for classifying port disaster risk levels is usually formulated based on the identification, analysis, and evaluation of potential disasters, which usually include natural factors such as earthquakes, typhoons, floods, and technical or human factors such as ship collisions and hazardous material leaks. Currently, the classification of port disaster risk levels mainly relies on statistical analysis methods to evaluate the likelihood of risk occurrence and the severity of potential consequences. The following are the specific operation steps:

[0003] First, determine all types of disasters affecting port operations through historical disaster event records, and directly obtain the occurrence frequency of each type of disaster, the consequences caused by each type of disaster, and the severity value of each consequence based on the reports of historical disaster events. Among them, the consequences caused by each type of disaster that can be obtained through the reports of historical disaster events include, but are not limited to, consequences at the economic, environmental, and personnel levels, and the severity value of each consequence is often obtained by statistically calculating the corresponding economic loss value, environmental loss value, and number of casualties; subsequently, perform an averaging process on the severity values of all consequences caused by each type of disaster obtained through statistics to obtain the average severity value of all consequences caused by each type of disaster, and then calculate the expected loss value of each type of disaster by combining the occurrence frequency of each type of disaster; finally, based on the obtained expected loss value, the average severity value of all consequences caused by each type of disaster, and the occurrence frequency of each type of disaster, create a two-dimensional risk matrix. In the matrix, the x-axis represents the probability of occurrence and increases gradually from left to right, and the y-axis represents the average consequence severity value and increases gradually from bottom to top. Then, set thresholds for the occurrence frequency and average severity value respectively to effectively divide the low-risk area, medium-risk area, and high-risk area. Subsequently, map the average severity value of all consequences caused by each type of disaster and the occurrence frequency of each type of disaster to the created two-dimensional risk matrix. At this time, the occurrence frequency and average severity value respectively represent the x-axis coordinate and y-axis coordinate in the two-dimensional risk matrix, and the combination represents the specific coordinate of this type of disaster. Then, according to the divided low-risk area, medium-risk area, and high-risk area, it is possible to intuitively determine which risk area this type of disaster specifically belongs to, so as to determine the risk level of this type of disaster. Further, the role of the expected loss value is mainly that if the specific coordinates of other multiple types of disasters are the same as those of the current type of disaster, then the expected loss value can be used to determine the risk level priority of these types of disasters. Specifically, at this time, the higher the expected loss value of the type of disaster, the higher the risk level.

[0004] In the existing calculation process of the expected loss value, since only the average severity value of all consequences caused by each disaster type and the occurrence frequency of each disaster type are considered, the correlation factors between different consequences and the complexity factors of the consequences of each disaster type are often ignored. As a result, the calculated expected loss value often lacks high scientificity. Although it can meet the basic risk level classification, when determining the risk level of disaster types with the same coordinates, there is a high probability of misjudging the risk level of disaster types due to the relatively inaccurate expected loss value.

[0005] Therefore, there is an urgent need for a technical solution for a method of classifying port disaster risk levels in the existing technology. Summary of the Invention

[0006] To solve the above technical problems, the present invention provides a method for classifying port disaster risk levels, which specifically includes the following steps:

[0007] Step S1: Collect the historical disaster event records of the port, and based on the historical disaster event records, statistically obtain each disaster type of the port, the occurrence frequency of each disaster type, the consequences caused by each disaster type, and the severity value of each consequence caused by each disaster type;

[0008] Step S2: Calculate the mean value of the severity values of all consequences caused by each disaster type, and based on the mean value of the severity values of all consequences caused by each disaster type and the occurrence frequency of each disaster type, calculate the first expected loss value of each disaster type;

[0009] Step S3: Optimize the calculated first expected loss value of each disaster type to obtain the second expected loss value of each disaster type;

[0010] Step S3a: Obtain the comprehensive correlation coefficient between all consequences in each disaster type;

[0011] Step S3a1: Obtain the correlation coefficient between different consequences in each disaster type;

[0012] Step S3a2: Synthesize the correlation coefficients between different consequences in each disaster type and take the mean value to obtain the comprehensive correlation coefficient between all consequences in each disaster type;

[0013] Step S3b: Obtain the comprehensive recovery time of all consequences in each disaster type;

[0014] Step S3b1: Based on the historical disaster event records of the port, statistically obtain the recovery time of each consequence in each disaster type;

[0015] Step S3b2: Assign weights to each consequence caused by each type of disaster according to the severity value of each consequence caused by each type of disaster;

[0016] Step S3b3: Combine the recovery times of each consequence in each type of disaster and, in combination with the weights of each consequence, calculate the comprehensive recovery time of all consequences in each type of disaster;

[0017] Among them, the calculation formula for obtaining the comprehensive recovery time of all consequences in each type of disaster is:

[0018] ;

[0019] In the formula, represents the comprehensive recovery time of all consequences in the i-th type of disaster; represents the weight of the j-th consequence in the i-th type of disaster; represents the recovery time of the j-th consequence in the i-th type of disaster; represents the number of consequences in the i-th type of disaster;

[0020] Step S3c: Calculate the first composite index of each type of disaster according to the ratio of the mean value of the severity values of all consequences caused by each type of disaster to the occurrence frequency of each type of disaster;

[0021] Among them, the calculation formula for obtaining the first composite index of each type of disaster is:

[0022] ;

[0023] In the formula, represents the first composite index of the i-th type of disaster; represents the mean value of the severity values of all consequences caused by the i-th type of disaster; represents the occurrence frequency of the i-th type of disaster;

[0024] Step S3d: Calculate the second composite index of each type of disaster according to the ratio of the comprehensive correlation coefficient between all consequences in each type of disaster to the comprehensive recovery time of all consequences in each type of disaster;

[0025] Among them, the calculation formula for obtaining the second composite index of each type of disaster is:

[0026] ;

[0027] In the formula, represents the first composite index of the i-th type of disaster; represents the comprehensive correlation coefficient between all consequences in the i-th type of disaster; Represents the comprehensive recovery time of all consequences in the i-th type of disaster;

[0028] Step S3e: Calculate the third composite index of each type of disaster based on the first composite index and the second composite index;

[0029] Among them, the calculation formula for obtaining the third composite index of each type of disaster is:

[0030] ;

[0031] In the formula, Represents the third composite index of the i-th type of disaster; Represents the first composite index of the i-th type of disaster; Represents the second composite index of the i-th type of disaster;

[0032] Step S3f: Calculate the second expected loss value of each type of disaster according to the mean value of the severity values of all consequences caused by each type of disaster, the occurrence frequency of each type of disaster, the comprehensive correlation coefficient between all consequences in each type of disaster, the comprehensive recovery time of all consequences in each type of disaster, and the third composite index of each type of disaster;

[0033] Among them, the calculation formula for obtaining the second expected loss value of each type of disaster is:

[0034] ;

[0035] In the formula, Represents the second expected loss value of the i-th type of disaster; Represents the occurrence frequency of the i-th type of disaster; Represents the mean value of the severity values of all consequences caused by the i-th type of disaster; Represents the comprehensive correlation coefficient between all consequences in the i-th type of disaster; Represents the comprehensive recovery time of all consequences in the i-th type of disaster; Represents the third composite index of the i-th type of disaster;

[0036] Step S4: Construct a two-dimensional risk matrix based on the second expected loss value of each type of disaster, the mean value of the severity values of all consequences caused by each type of disaster, and the occurrence frequency of each type of disaster, and determine the risk level of each type of disaster through the two-dimensional risk matrix.

[0037] The embodiments of the present invention have the following technical effects:

[0038] On the existing basis, the present invention further considers the comprehensive correlation coefficient between all consequences in each disaster type in a data-driven manner to ensure that the correlation factors between different consequences can be comprehensively considered. At the same time, by analyzing and calculating the first and second composite indices of each disaster type, and obtaining the third composite index on the basis of combining the first and second composite indices, it is ensured that the complexity factors of the consequences of each disaster type are effectively considered. Finally, the obtained results are incorporated into the existing calculation formula of the expected loss value to ensure a more accurate, comprehensive and scientific expected loss value. This enables the subsequent determination of the risk level based on the two-dimensional risk matrix to effectively improve the accuracy and scientificity of the risk level determination. Especially when determining the risk level of disaster types with the same coordinates, it can also effectively reduce the probability of misjudgment of the risk level to the greatest extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0040] Figure 1 is a flowchart of a method for dividing the risk level of port disasters provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0042] Embodiment 1: As Figure 1 shown, the present invention provides a method for dividing the risk level of port disasters, including the following steps:

[0043] Step S1, collect the records of historical port disaster events, and statistically obtain each disaster type of the port, the occurrence frequency of each disaster type, the consequences caused by each disaster type, and the severity value of each consequence caused by each disaster type based on the records of historical disaster events;

[0044] Step S2: Calculate the mean of the severity values of all consequences caused by each disaster type, and calculate the first expected loss value of each disaster type based on the mean of the severity values of all consequences caused by each disaster type and the occurrence frequency of each disaster type;

[0045] Step S3: Optimize the calculated first expected loss value of each disaster type to obtain the second expected loss value of each disaster type;

[0046] Step S3a: Obtain the comprehensive correlation coefficient between all consequences in each disaster type;

[0047] Step S3a1: Obtain the correlation coefficient between different consequences in each disaster type;

[0048] It should be noted that the process of obtaining the correlation coefficient between different consequences in each disaster type is specifically as follows:

[0049] First, obtain the disaster event records in the past period of time, such as in the past 20 years, from channels such as port management departments, insurance companies, and government agencies. For each disaster type, count the severity value of each consequence caused in each event that occurred in the past 20 years. For example, there are the following consequence types: infrastructure damage, business interruption, environmental damage, etc. For each consequence type, record its specific severity value in each disaster event. Then, for each disaster type, establish a data set for each consequence type, which contains the severity values of this consequence in all historical events. Assume that the i-th disaster type has n different consequence types, then each consequence type has a corresponding data set. For example, the data set of the j-th consequence is expressed as , similarly, the data set of the k-th consequence is expressed as ;

[0050] Immediately afterwards, use the Pearson correlation coefficient to calculate the correlation coefficient between different consequences. The specific formula is as follows:

[0051] ;

[0052] In the formula, represents the Pearson correlation coefficient between the j-th consequence and the k-th consequence; M represents the number of historical events; represents the severity value of the j-th consequence in the m-th historical event; represents the severity value of the k-th consequence in the m-th historical event; represents the average severity value of the j-th consequence in all historical events; represents the average severity value of the k-th consequence in all historical events;

[0053] Step S3a2: Synthesize the correlation coefficients between different consequences in each disaster type and take the mean value to obtain the comprehensive correlation coefficient between all consequences in each disaster type;

[0054] Among them, the calculation formula for obtaining the comprehensive correlation coefficient between all consequences in each disaster type is:

[0055] ;

[0056] In the formula, represents the comprehensive correlation coefficient between all consequences in the i-th disaster type; represents the number of consequences in the i-th disaster type; represents the Pearson correlation coefficient between the j-th consequence and the k-th consequence;

[0057] Step S3b: Obtain the comprehensive recovery time of all consequences in each disaster type;

[0058] Step S3b1: Based on the historical disaster event records of the port, count the recovery time of each consequence in each disaster type;

[0059] Step S3b2: According to the severity value of each consequence caused by each disaster type, assign weights to each consequence caused by each disaster type;

[0060] Step S3b3: Synthesize the recovery time of each consequence in each disaster type and combine with the weight of each consequence to calculate the comprehensive recovery time of all consequences in each disaster type;

[0061] Among them, the calculation formula for obtaining the comprehensive recovery time of all consequences in each disaster type is:

[0062] ;

[0063] In the formula, represents the comprehensive recovery time of all consequences in the i-th disaster type; represents the weight of the j-th consequence in the i-th disaster type; represents the recovery time of the j-th consequence in the i-th disaster type; represents the number of consequences in the i-th disaster type;

[0064] Step S3c: Calculate the first composite index of each disaster type according to the ratio of the mean value of the severity values of all consequences caused by each disaster type to the occurrence frequency of each disaster type;

[0065] Among them, the calculation formula for obtaining the first composite index of each disaster type is:

[0066] ;

[0067] In the formula, represents the first composite index of the i-th type of disaster; represents the mean value of the severity values of all consequences caused by the i-th type of disaster; represents the occurrence frequency of the i-th type of disaster;

[0068] It should be noted that the first composite index combines the mean severity of the consequences of each type of disaster with its occurrence frequency, thus providing a more comprehensive risk assessment indicator. This not only considers the likelihood of the disaster occurring but also measures the average loss that may be caused each time it occurs. Relying solely on the occurrence frequency or the severity of the consequences is likely to lead to biases in risk assessment. For example, a disaster with a low occurrence frequency but extremely severe consequences such as an earthquake and a disaster with a high occurrence frequency but less severe consequences such as a small-scale flood. Therefore, through the first composite index, the complexity factors of their relative risks can be more accurately evaluated.

[0069] Step S3d: Calculate the second composite index of each type of disaster according to the ratio of the comprehensive correlation coefficient between all consequences in each type of disaster to the comprehensive recovery time of all consequences in each type of disaster;

[0070] Among them, the calculation formula for obtaining the second composite index of each type of disaster is:

[0071] ;

[0072] In the formula, represents the first composite index of the i-th type of disaster; represents the comprehensive correlation coefficient between all consequences in the i-th type of disaster; represents the comprehensive recovery time of all consequences in the i-th type of disaster;

[0073] It should be noted that the second composite index measures the intensity of the interaction between different consequences through the relationship between the comprehensive correlation coefficient and the recovery time, which helps to reveal the correlation between different consequences and its importance to the overall impact, especially in the long-term recovery. Further, when a type of disaster has multiple consequences and there is a strong correlation between these consequences, for example, infrastructure damage will extend the time of business interruption, and the second composite index can effectively capture the complexity factors of this interaction, ensuring that the evaluation results are more scientific and reasonable.

[0074] Step S3e: Calculate the third composite index of each type of disaster based on the first composite index and the second composite index;

[0075] Among them, the calculation formula for obtaining the third composite index of each type of disaster is:

[0076] ;

[0077] In the formula, represents the third composite index of the i-th type of disaster; represents the first composite index of the i-th type of disaster; represents the second composite index of the i-th type of disaster;

[0078] It should be noted that the third composite index comprehensively considers the first composite index and the second composite index, that is, it covers multiple key factors such as occurrence frequency, consequence severity, correlation between consequences, and recovery time. This makes the risk assessment more comprehensive, ensures that the complexity factors of consequences in the disaster type are effectively considered, reduces the assessment error caused by ignoring some important factors. By introducing the third composite index, the overall risk level of the disaster can be better reflected. Especially for those disaster types with the same occurrence frequency and consequence severity, the third composite index can further accurately distinguish their priorities and ensure more effective resource allocation.

[0079] Step S3f: Calculate the second expected loss value of each type of disaster based on the mean value of the severity values of all consequences caused by each type of disaster, the occurrence frequency of each type of disaster, the comprehensive correlation coefficient between all consequences in each type of disaster, the comprehensive recovery time of all consequences in each type of disaster, and the third composite index of each type of disaster;

[0080] Among them, the calculation formula for obtaining the second expected loss value of each type of disaster is:

[0081] ;

[0082] In the formula, represents the second expected loss value of the i-th type of disaster; represents the occurrence frequency of the i-th type of disaster; represents the mean value of the severity values of all consequences caused by the i-th type of disaster; represents the comprehensive correlation coefficient between all consequences in the i-th type of disaster; represents the comprehensive recovery time of all consequences in the i-th type of disaster; represents the third composite index of the i-th type of disaster;

[0083] It should be noted that the second expected loss value comprehensively considers the occurrence frequency, the mean value of the consequence severity, the correlation coefficient between consequences, the comprehensive recovery time, and the third composite index. This ensures that the evaluation result not only reflects the possibility of the disaster occurrence and the direct loss, but also takes into account the interaction between consequences and their long-term impact. Moreover, by introducing multiple composite indices, especially the third composite index, the potential loss of the disaster can be more accurately evaluated, avoiding evaluation errors caused by neglecting some important factors. This enables, when facing disaster types with the same occurrence frequency and consequence severity, to effectively reduce the probability of misjudging the risk level of the disaster type by comprehensively considering other factors such as the correlation between consequences and the recovery time.

[0084] Step S4: Construct a two-dimensional risk matrix based on the second expected loss value of each disaster type, the mean value of the severity values of all consequences caused by each disaster type, and the occurrence frequency of each disaster type, and determine the risk level of each disaster type through the two-dimensional risk matrix.

[0085] It should be noted that the terms used in the present invention are only for describing specific embodiments and do not limit the scope of the present application. As shown in the specification of the present invention, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include plural. The term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method or device including the said element.

[0086] It should also be noted that the orientation or positional relationship indicated by terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation of the present invention. Unless otherwise clearly specified and limited, terms such as "installed", "connected", "connected to" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood in specific situations.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for classifying port disaster risk levels, characterized in that: The following steps are involved: Step S1, collecting historical disaster event records of the port, and obtaining statistics of each disaster type of the port, the frequency of occurrence of each disaster type, the consequences caused by each disaster type, and the severity value of each consequence caused by each disaster type based on the historical disaster event records; Step S2: Calculate the mean value of the severity of all consequences caused by each disaster type, and calculate the first expected loss value of each disaster type based on the mean value of the severity of all consequences caused by each disaster type and the occurrence frequency of each disaster type; Step S3, optimizing the calculated first expected loss value of each disaster type to obtain a second expected loss value of each disaster type; Specifically include: Step S3a, obtaining the comprehensive correlation coefficient between all consequences in each disaster type; Step S3b, obtaining the comprehensive recovery time of all consequences of each disaster type; Step S3c, calculating a first composite index for each disaster type according to the ratio of the mean value of the severity of all consequences caused by each disaster type to the occurrence frequency of each disaster type; Step S3d, calculating a second composite index for each disaster type according to the ratio of the comprehensive correlation coefficient between all consequences in each disaster type and the comprehensive recovery time of all consequences in each disaster type; Step S3e, calculating a third composite index for each disaster type based on the first composite index and the second composite index; Step S3f, calculating the second expected loss value of each disaster type according to the mean value of the severity of all consequences caused by each disaster type, the frequency of occurrence of each disaster type, the comprehensive correlation coefficient between all consequences in each disaster type, the comprehensive recovery time of all consequences in each disaster type, and the third composite index of each disaster type; Step S4: construct a two-dimensional risk matrix based on the second expected loss value of each disaster type, the mean of the severity values ​​of all consequences caused by each disaster type, and the occurrence frequency of each disaster type, and determine the risk level of each disaster type through the two-dimensional risk matrix.

2. A method for classifying port disaster risk levels according to claim 1, characterized in that: The comprehensive correlation coefficients between all consequences of each disaster type are obtained, including: Step S3a1, obtaining the correlation coefficients between different consequences in each disaster type; Step S3a2: Integrate the correlation coefficients between different consequences in each disaster type and take the average to obtain the comprehensive correlation coefficient between all consequences in each disaster type.

3. A method for classifying port disaster risk levels according to claim 1, characterized in that: The method of obtaining the comprehensive recovery time for all consequences of each disaster type includes: Step S3b1: based on the historical disaster event records of the port, the recovery time of each consequence of each disaster type is counted; Step S3b2, assigning a weight to each consequence caused by each disaster type according to the severity value of each consequence caused by each disaster type; Step S3b3, comprehensively analyzing the recovery time of each consequence in each disaster type and combining the weight of each consequence to calculate the comprehensive recovery time of all consequences in each disaster type; Among them, the calculation formula for the comprehensive recovery time of all consequences in each disaster type is: ； In the formula, represents the comprehensive recovery time of all consequences in the i-th disaster type; represents the weight of the jth consequence in the i-th disaster type; represents the recovery time of the jth consequence in the i-th disaster type; Represents the number of consequences in the i-th disaster type.

4. A method for classifying port disaster risk levels according to claim 1, characterized in that: The calculation formula for obtaining the first composite index of each disaster type is: ； In the formula, The first composite index representing the i-th disaster type; represents the mean value of all consequence severity values ​​caused by the i-th disaster type; Represents the occurrence frequency of the i-th disaster type.

5. A method for classifying port disaster risk levels according to claim 1, characterized in that: The calculation formula for obtaining the second composite index of each disaster type is: ； In the formula, The second composite index representing the i-th disaster type; represents the comprehensive correlation coefficient between all consequences in the i-th disaster type; Represents the comprehensive recovery time of all consequences in the i-th disaster type.

6. A method for classifying port disaster risk levels according to claim 1, characterized in that: The calculation formula for obtaining the third composite index of each disaster type is: ； In the formula, The third composite index representing the i-th disaster type; The first composite index representing the i-th disaster type; The second composite index representing the i-th disaster type.

7. A method for classifying port disaster risk levels according to claim 1, characterized in that: The calculation formula for obtaining the second expected loss value for each disaster type is: ； In the formula, represents the second expected loss value of the i-th disaster type; represents the occurrence frequency of the i-th disaster type; represents the mean value of all consequence severity values ​​caused by the i-th disaster type; represents the comprehensive correlation coefficient between all consequences in the i-th disaster type; represents the comprehensive recovery time of all consequences in the i-th disaster type; The third composite index representing the i-th disaster type.

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