Port disaster risk level classification method

Abstract

The present invention relates to the technical field of risk level classification. Disclosed is a port disaster risk level classification method. On the basis of the prior art, the present invention further takes into consideration a comprehensive correlation coefficient among all consequences of each disaster type in a data-driven manner, so as to ensure that correlation factors between different consequences can be comprehensively taken into account; in addition, a first composite index and a second composite index of each disaster type are analyzed and calculated, and a third composite index is obtained on the basis of the first composite index and the second composite index, so as to ensure that complexity factors of the consequences of each disaster type are effectively taken into consideration; finally, obtained results are incorporated into an existing calculation formula for an expected loss value, so as to ensure that a more accurate, more comprehensive, and more scientific expected loss value is obtained; thus, even when subsequently determining risk levels of disaster types at the same coordinates, it is possible to effectively reduce the probability of occurrence of risk level misclassification to the greatest extent.

Description

A method for classifying port disaster risk levels Technical Field

[0001] This invention relates to the field of risk level classification technology, and in particular to a method for classifying port disaster risk levels. Background Technology

[0002] Port disaster risk level classification methods are typically based on the identification, analysis, and assessment of potential disasters. These disasters generally include natural factors such as earthquakes, typhoons, and floods, and technical or human factors such as ship collisions and hazardous material spills. Currently, the classification of port disaster risk levels mainly relies on statistical analysis methods to assess the likelihood of risk occurrence and the severity of potential consequences. The specific operational steps are as follows:

[0003] First, all disaster types affecting port operations are identified through historical disaster event records. Based on these reports, the frequency of occurrence, consequences, and severity of each disaster type are directly obtained. The consequences of each disaster type, as obtained from historical event reports, include, but are not limited to, economic, environmental, and personnel consequences. The severity of each consequence is typically calculated by statistically analyzing corresponding economic losses, environmental losses, and casualties. Next, the severity values ​​of all consequences for each disaster type are averaged to obtain the average severity value. Then, the expected loss value for each disaster type is calculated by combining this with its frequency. Finally, a two-dimensional risk matrix is ​​created based on the expected loss value, the average severity value of all consequences for each disaster type, and the frequency of occurrence of each disaster type. In this matrix, the x-axis represents the probability of occurrence, increasing gradually from left to right, and the y-axis... The average severity value represents the severity of consequences, increasing gradually from bottom to top. Thresholds are then set for both the frequency of occurrence and the average severity value to effectively divide the disaster into low-risk, medium-risk, and high-risk areas. Subsequently, the average severity value of all consequences caused by each disaster type and the frequency of occurrence of each disaster type are mapped to the created two-dimensional risk matrix. At this point, the frequency of occurrence and the average severity value represent the x-axis and y-axis coordinates respectively in the two-dimensional risk matrix. Combined, these represent the specific coordinates of this disaster type. Based on the divided low-risk, medium-risk, and high-risk areas, it is possible to intuitively determine which risk area this disaster type should be addressed within, thus determining its risk level. Furthermore, the expected loss value plays a crucial role. If the specific coordinates of other disaster types are consistent with the coordinates of the current disaster type, then the expected loss value can be used to prioritize the risk levels of these disaster types. Specifically, the higher the expected loss value of a disaster type, the higher its risk level.

[0004] Current methods for calculating expected loss values ​​often neglect the correlation between different consequences and the complexity of the consequences of each disaster type because they only consider the average severity of all consequences caused by each disaster type and the frequency of occurrence of each disaster type. As a result, the calculated expected loss values ​​often lack high scientific rigor. Although they can meet the basic risk level classification, when faced with the risk level determination of disaster types with the same coordinates, it is very easy to misjudge the risk level of disaster types due to the poor accuracy of the expected loss values.

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

[0006] To address the aforementioned technical problems, this invention provides a method for classifying port disaster risk levels, specifically comprising the following steps:

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

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

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

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

[0011] Step S3a1: Obtain the correlation coefficients between different consequences for each type of disaster;

[0012] Step S3a2: Combine the correlation coefficients between different consequences in each type of disaster and take the average value to obtain the comprehensive correlation coefficient between all consequences in each type of disaster.

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

[0014] Step S3b1: Based on the port's historical disaster event records, calculate the recovery time for each consequence of each disaster type;

[0015] Step S3b2: Assign a weight to each consequence of each disaster type based on the severity value of each consequence caused by each disaster type;

[0016] Step S3b3: Combine the recovery time of each consequence in each disaster type and the weight of each consequence to calculate the overall recovery time of all consequences in each disaster type;

[0017] The formula for calculating the overall recovery time for all consequences in each type of disaster is as follows:

[0018]

[0019] In the formula, Represents the total recovery time for all consequences in the i-th disaster type; D represents the weight of the j-th consequence in the i-th disaster type; ij Represents the recovery time for the j-th consequence in the i-th disaster type; This represents the number of consequences in the i-th type of disaster;

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

[0021] The formula for calculating the first composite index for each disaster type is as follows:

[0022]

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

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

[0025] The formula for calculating the second composite index for each disaster type is as follows:

[0026]

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

[0028] Step S3e: Based on the first composite index and the second composite index, calculate the third composite index for each disaster type;

[0029] The formula for calculating the third composite index for each disaster type is as follows:

[0030]

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

[0032] Step S3f: Calculate the second expected loss value for each disaster type based on the mean severity value 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.

[0033] The formula for calculating the second expected loss value for each type of disaster is as follows:

[0034]

[0035] In the formula, ELV i The second expected loss value represents the i-th type of disaster; This represents the frequency of occurrence of the i-th type of disaster; This represents the mean of the severity values ​​of all consequences caused by the i-th type of disaster. This represents the comprehensive correlation coefficient among all consequences in the i-th disaster type; Represents the total recovery time for all consequences in the i-th disaster type; The third composite index represents the i-th type of disaster;

[0036] Step S4: Construct a two-dimensional risk matrix based on the second expected loss value for 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.

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

[0038] Building upon existing methods, this invention further considers the comprehensive correlation coefficients among all consequences of each disaster type using a data-driven approach. This ensures that the correlation factors between different consequences are fully considered. Simultaneously, by analyzing and calculating the first and second composite indices for each disaster type, and combining these indices to obtain a third composite index, the complexity of the consequences of each disaster type is effectively considered. Finally, the results are incorporated into the existing formula for calculating expected loss values, ensuring a more accurate, comprehensive, and scientifically sound expected loss value. This significantly improves the accuracy and scientific rigor of risk level determination when using a two-dimensional risk matrix, especially when determining the risk level of disaster types with the same coordinates, thus minimizing the probability of misjudgments. Attached Figure Description

[0039] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0040] Figure 1 is a flowchart of a method for classifying port disaster risk levels according to an embodiment of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0042] Example 1: As shown in Figure 1, the present invention provides a method for classifying port disaster risk levels, including the following steps:

[0043] Step S1: Collect historical disaster event records of the port, and based on the historical disaster event records, statistically obtain the port's disaster type, the frequency of occurrence of each disaster type, the consequences of each disaster type, and the severity value of each consequence of each disaster type;

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

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

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

[0047] Step S3a1: Obtain the correlation coefficients between different consequences for each type of disaster;

[0048] It is worth noting that the process for obtaining the correlation coefficients between different consequences within each type of disaster is as follows:

[0049] First, records of disaster events over a past period, such as the past 20 years, are obtained from port management departments, insurance companies, and government agencies. For each type of disaster, the severity value of each consequence caused by each event in the past 20 years is calculated. For example, there are several consequence types, such as infrastructure damage, business interruption, and environmental damage. For each consequence type, its specific severity value is recorded in each disaster event. Next, for each disaster type, a dataset is created for each consequence type, containing the severity values ​​of that consequence in all historical events. Assuming that the i-th disaster type has n different consequence types, each consequence type has a corresponding dataset. For example, the dataset for the j-th consequence type is represented as follows: Similarly, the dataset for the kth consequence is represented as follows;

[0050] Next, the correlation coefficient between different consequences is calculated using the Pearson correlation coefficient, as shown in the following formula:

[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; This represents the severity value of the j-th consequence in the m-th historical event; This represents the severity value of the k-th consequence in the m-th historical event; This represents the average severity of the j-th consequence across all historical events. This represents the average severity of the k-th consequence across all historical events.

[0053] Step S3a2: Combine the correlation coefficients between different consequences in each type of disaster and take the average value to obtain the comprehensive correlation coefficient between all consequences in each type of disaster.

[0054] The formula for calculating the comprehensive correlation coefficient among all consequences for each disaster type is as follows:

[0055]

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

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

[0058] Step S3b1: Based on the port's historical disaster event records, calculate the recovery time for each consequence of each disaster type;

[0059] Step S3b2: Assign a weight to each consequence of each disaster type based on the severity value of each consequence caused by each disaster type;

[0060] Step S3b3: Combine the recovery time of each consequence in each disaster type and the weight of each consequence to calculate the overall recovery time of all consequences in each disaster type;

[0061] The formula for calculating the overall recovery time for all consequences in each type of disaster is as follows:

[0062]

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

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

[0065] The formula for calculating the first composite index for each disaster type is as follows:

[0066]

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

[0068] It is worth noting that the first composite index combines the average severity of the consequences of each disaster type with its frequency of occurrence, thus providing a more comprehensive risk assessment indicator. This not only considers the probability of a disaster occurring, but also measures the average loss that may be caused each time it occurs. Relying solely on the frequency of occurrence or the severity of consequences can easily lead to biases in risk assessment. For example, a disaster with a low frequency of occurrence but extremely severe consequences, such as an earthquake, and a disaster with a high frequency of occurrence but minor consequences, such as a small-scale flood, are different. Therefore, the first composite index can more accurately assess the complexity of the relative risks between them.

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

[0070] The formula for calculating the second composite index for each disaster type is as follows:

[0071]

[0072] In the formula, The first composite index represents the i-th type of disaster; This represents the comprehensive correlation coefficient among all consequences in the i-th disaster type; Represents the total recovery time for all consequences in the i-th disaster type;

[0073] It is worth noting that the second composite index measures the strength of the interaction between different consequences by integrating the relationship between correlation coefficients and recovery time. This helps to reveal the correlation between different consequences and their importance to the overall impact, especially in terms of long-term recovery. Furthermore, when a disaster type has multiple consequences and there is a strong correlation between these consequences, such as infrastructure damage prolonging business interruption, the second composite index can effectively capture the complexity of such interactions, ensuring that the assessment results are more scientific and reasonable.

[0074] Step S3e: Based on the first composite index and the second composite index, calculate the third composite index for each disaster type;

[0075] The formula for calculating the third composite index for each disaster type is as follows:

[0076]

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

[0078] It is worth noting that the third composite index comprehensively considers the first and second composite indices, that is, it simultaneously covers multiple key factors such as frequency of occurrence, severity of consequences, correlation between consequences, and recovery time. This makes the risk assessment more comprehensive, ensures that the complex factors of consequences in disaster types are effectively considered, and reduces assessment errors caused by ignoring certain important factors. By introducing the third composite index, the overall risk level of disasters can be better reflected. In particular, for disaster types with the same frequency of occurrence and severity of consequences, 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 for each disaster type based on the mean severity value 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.

[0080] The formula for calculating the second expected loss value for each type of disaster is as follows:

[0081]

[0082] In the formula, ELV i The second expected loss value represents the i-th type of disaster; This represents the frequency of occurrence of the i-th type of disaster; This represents the mean of the severity values ​​of all consequences caused by the i-th type of disaster. This represents the comprehensive correlation coefficient among all consequences in the i-th disaster type; Represents the total recovery time for all consequences in the i-th disaster type; The third composite index represents the i-th type of disaster;

[0083] It is worth noting that the second expected loss value comprehensively considers the frequency of occurrence, the average severity of consequences, the correlation coefficient between consequences, the comprehensive recovery time, and the third composite index. This ensures that the assessment results not only reflect the probability of disaster occurrence and direct losses, but also consider the interaction between consequences and their long-term impact. Furthermore, by introducing multiple composite indices, especially the third composite index, the potential losses of disasters can be assessed more accurately, avoiding assessment errors caused by ignoring certain important factors. This allows for a more effective reduction in the probability of misjudging the risk level of disaster types when facing disaster types with the same frequency of occurrence and severity of consequences by comprehensively considering other factors such as the correlation between consequences and recovery time.

[0084] Step S4: Construct a two-dimensional risk matrix based on the second expected loss value for 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.

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

[0086] It should also be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Unless otherwise expressly specified and limited, the terms "installed," "connected," "linked," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components. For those skilled in the art, the specific meaning of the above terms in the present invention can be understood according to the specific circumstances.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions 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, Includes the following steps: Step S1: Collect historical disaster event records of the port, and based on the historical disaster event records, statistically obtain the port's disaster type, the frequency of occurrence of each disaster type, the consequences of each disaster type, and the severity value of each consequence of each disaster type; Step S2: Calculate the mean severity value of all consequences caused by each disaster type, and calculate the first expected loss value for each disaster type based on the mean severity value of all consequences caused by each disaster type and the occurrence frequency of each disaster type. Step S3: Optimize the first expected loss value for each disaster type to obtain the second expected loss value for each disaster type; Specifically, it includes: Step S3a: Obtain the comprehensive correlation coefficient between all consequences in each disaster type; Step S3b: Obtain the total recovery time for all consequences in each disaster type; Step S3c: Calculate the first composite index for each disaster type based on the ratio of the mean severity of all consequences caused by each disaster type to the frequency of occurrence of each disaster type; Step S3d: Calculate the second composite index for each disaster type based on the ratio of the comprehensive correlation coefficient between all consequences in each disaster type to the comprehensive recovery time of all consequences in each disaster type. Step S3e: Based on the first composite index and the second composite index, calculate the third composite index for each disaster type; Step S3f: Calculate the second expected loss value for each disaster type based on the mean severity value 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 for 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. The method for classifying port disaster risk levels according to claim 1, characterized in that, The process of obtaining the comprehensive correlation coefficient between all consequences in each disaster type includes: Step S3a1: Obtain the correlation coefficients between different consequences for each type of disaster; Step S3a2: Combine the correlation coefficients between different consequences in each type of disaster and take the average value to obtain the comprehensive correlation coefficient between all consequences in each type of disaster.

3. The method for classifying port disaster risk levels according to claim 1, characterized in that, The acquisition of the comprehensive recovery time for all consequences in each disaster type includes: Step S3b1: Based on the port's historical disaster event records, calculate the recovery time for each consequence of each disaster type; Step S3b2: Assign a weight to each consequence of each disaster type based on the severity value of each consequence caused by each disaster type; Step S3b3: Combine the recovery time of each consequence in each disaster type and the weight of each consequence to calculate the overall recovery time of all consequences in each disaster type; The formula for calculating the overall recovery time for all consequences in each type of disaster is as follows: In the formula, Represents the total recovery time for all consequences in the i-th disaster type; D represents the weight of the j-th consequence in the i-th disaster type; ij Represents the recovery time for the j-th consequence in the i-th disaster type; This represents the number of consequences in the i-th type of disaster.

4. The method for classifying port disaster risk levels according to claim 1, characterized in that, The formula for calculating the first composite index for each disaster type is as follows: In the formula, The first composite index represents the i-th type of disaster; This represents the mean of the severity values ​​of all consequences caused by the i-th type of disaster. This represents the frequency of occurrence of the i-th type of disaster.

5. The method for classifying port disaster risk levels according to claim 1, characterized in that, The formula for calculating the second composite index for each disaster type is as follows: In the formula, The second composite index represents the i-th type of disaster; This represents the comprehensive correlation coefficient among all consequences in the i-th disaster type; This represents the combined recovery time for all consequences of the i-th disaster type.

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

7. The method for classifying port disaster risk levels according to claim 1, characterized in that, The formula for calculating the second expected loss value for each type of disaster is as follows: In the formula, ELV i The second expected loss value represents the i-th type of disaster; This represents the frequency of occurrence of the i-th type of disaster; This represents the mean of the severity values ​​of all consequences caused by the i-th type of disaster. This represents the comprehensive correlation coefficient among all consequences in the i-th disaster type; Represents the total recovery time for all consequences in the i-th disaster type; The third composite index represents the i-th type of disaster.

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