Port disaster risk grading method

Abstract

The invention discloses a port disaster risk grading method, which relates to the technical field of risk grading, and further considers comprehensive correlation coefficients among all consequences in each disaster type in a data-driven manner on the basis of the prior art, so as to ensure that correlation factors among different consequences can be comprehensively considered, and improve the risk grading efficiency. Meanwhile, 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 combining the first composite index and the second composite index so as to ensure that complexity factors of consequences of each disaster type are effectively considered, and finally the obtained result is incorporated into an existing calculation formula of an expected loss value, so that the calculation accuracy of the expected loss value is improved. According to the method and the device, the probability of occurrence of risk level misjudgment can be effectively reduced to the greatest extent even if the risk level of disaster types with the same coordinates is judged subsequently, so that the expected loss value which is more accurate, more comprehensive and more scientific is ensured to be obtained, and the probability of occurrence of risk level misjudgment can be effectively reduced to the greatest extent.

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 port disaster risk classification method is usually 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 dangerous goods leakage. At present, the classification of port disaster risk levels mainly relies on statistical analysis methods to assess the possibility of risk occurrence and the severity of potential consequences. The following are the specific steps: First, all disaster types that affect port operations are determined through historical disaster event records, and based on historical disaster event reports, the frequency of occurrence of each disaster type, the consequences caused by each disaster type, and the severity value of each consequence are directly obtained. The consequences of each disaster type that can be obtained through historical disaster event reports include but are not limited to economic, environmental, and personnel consequences, and the severity value of each consequence is often obtained by counting the corresponding economic loss values, environmental loss values, and casualties; then, the severity values ​​of all consequences caused by each disaster type obtained by statistics are averaged to obtain the average severity value of all consequences caused by each disaster type, and then the expected loss value of each disaster type is calculated by combining the frequency of occurrence of each disaster type; finally, based on the expected loss value obtained, the average severity value of all consequences caused by each disaster type, and the frequency of occurrence of each disaster type, a two-dimensional risk matrix is ​​created, in which the x-axis represents the probability of occurrence and gradually increases from left to right, and the y-axis represents the probability of occurrence. It represents the average severity value of the consequences, and gradually increases from bottom to top. Then, thresholds are set for the occurrence frequency and the average severity value respectively to effectively divide the low-risk area, medium-risk area and high-risk area. Then, the average severity value of all consequences caused by each disaster type and the occurrence frequency of each disaster type are mapped to the created two-dimensional risk matrix. At this time, the occurrence frequency and the average severity value represent the x-axis coordinate and the y-axis coordinate in the two-dimensional risk matrix respectively, and the combination represents the specific coordinates of this disaster type. Then, according to the divided low-risk area, medium-risk area and high-risk area, it can be intuitively determined in which risk area this disaster type is specifically handled to determine the risk level of this disaster type. Furthermore, the role of the expected loss value is mainly that if the specific coordinates of multiple other disaster types are consistent with the coordinates of the current disaster type, then the expected loss value can be used to determine the risk level priority of these disaster types. Specifically, the higher the expected loss value of the disaster type, the higher the risk level.

[0003] In the existing calculation process of expected loss values, only the average severity value of all consequences caused by each disaster type and the frequency of occurrence of each disaster type are considered, and 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 values ​​are often not highly scientific. 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 the disaster type due to the poor accuracy of the expected loss value.

[0004] Therefore, the prior art urgently needs a technical solution for a method for classifying port disaster risk levels. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method for classifying port disaster risk levels, which specifically includes the following steps: 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; Step S3a, obtaining the comprehensive correlation coefficient between all consequences in each disaster type; Step S3a1, obtaining the correlation coefficients between different consequences in each disaster type; Step S3a2, integrating the correlation coefficients between different consequences in each disaster type and taking the average to obtain 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 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; 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; Among them, the calculation formula for 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; 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; Among them, the calculation formula for the second composite index of each disaster type is: ; In the formula, The first 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; Step S3e, calculating a third composite index for each disaster type based on the first composite index and the second composite index; Among them, the calculation formula for 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; 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; The calculation formula for obtaining the second expected loss value of 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; 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.

[0006] The embodiments of the present invention have the following technical effects: On the basis of the existing, 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 fully considered. At the same time, by analyzing and calculating the first and second composite indexes of each disaster type, and obtaining the third composite index based on the combination of the first and second composite indexes, 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 that a more accurate, comprehensive and scientific expected loss value is obtained. This enables the subsequent risk level determination based on the two-dimensional risk matrix to effectively improve the accuracy and scientificity of the risk level determination, especially when facing the risk level determination 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

[0007] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0008] Figure 1 It is a flow chart of a method for classifying port disaster risk levels provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0009] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0010] Embodiment 1: Figure 1 As shown, the present invention provides a method for classifying port disaster risk levels, comprising the following steps: 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; Step S3a, obtaining the comprehensive correlation coefficient between all consequences in each disaster type; Step S3a1, obtaining the correlation coefficients between different consequences in each disaster type; It is worth noting that the process of obtaining the correlation coefficients between different consequences in each disaster type is as follows: First, obtain disaster event records from the port management department, insurance company, government agencies and other channels in the past period of time, such as the past 20 years. For each disaster type, count the severity values ​​of each consequence caused by each event in the past 20 years. For example, there are the following types of consequences: 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, including the severity values ​​of the consequence in all historical events. Assuming that the i-th disaster type has n different consequence types, each consequence type has a corresponding data set. For example, the data set of the j-th consequence is expressed as ,Similarly, the dataset of the kth consequence is expressed as; Next, the Pearson correlation coefficient was used to calculate the correlation coefficients between different consequences. The specific formula is as follows: ; In the formula, represents the Pearson correlation coefficient between the jth consequence and the kth consequence; M represents the number of historical events; represents the severity value of the jth consequence in the mth historical event; represents the severity value of the kth consequence in the mth historical event; represents the average severity value of the jth consequence in all historical events; represents the average severity value of the k-th consequence in all historical events; Step S3a2, integrating the correlation coefficients between different consequences in each disaster type and taking the average to obtain the comprehensive correlation coefficient between all consequences in each disaster type; Among them, the calculation formula for the comprehensive correlation coefficient between all consequences in each disaster type is: ; 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 jth consequence and the kth consequence; Step S3b, obtaining the comprehensive recovery time of all consequences of each disaster type; 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; 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; Among them, the calculation formula for 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; It is worth noting that the first composite index combines the mean severity of the consequences of each disaster type with its frequency of occurrence, thus providing a more comprehensive risk assessment indicator, which not only takes into account the possibility of a disaster, but also measures the average loss that may be caused each time it occurs. If we rely solely on the frequency of occurrence or the severity of the consequences, it is easy to lead to deviations in risk assessment. For example, a disaster with a low frequency but extremely serious consequences, such as an earthquake, and a disaster with a high frequency but lighter consequences, such as a small-scale flood, for this reason, the first composite index can more accurately assess the complexity factor of the relative risk between them.

[0011] 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; Among them, the calculation formula for the second composite index of each disaster type is: ; In the formula, The first 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; It is worth noting that the second composite index measures the intensity of 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 their importance to the overall impact, especially in long-term recovery. Furthermore, when a disaster type has multiple consequences and there is a strong correlation between these consequences, for example, infrastructure damage will prolong the duration of business interruption, and the second composite index can effectively capture the complexity of this interaction and ensure that the evaluation results are more scientific and reasonable.

[0012] Step S3e, calculating a third composite index for each disaster type based on the first composite index and the second composite index; Among them, the calculation formula for 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; It is worth noting 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 frequency of occurrence, severity of consequences, correlation between consequences and recovery time. This makes the risk assessment more comprehensive, ensures that the complexity factors of the consequences in the disaster type are effectively considered, and reduces the assessment errors caused by ignoring certain 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 frequency of occurrence and severity of consequences. The third composite index can further accurately distinguish their priorities and ensure more effective resource allocation.

[0013] 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; The calculation formula for obtaining the second expected loss value of 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; It is worth noting that the second expected loss value comprehensively considers the frequency of occurrence, the mean 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 possibility of disaster occurrence and direct losses, but also take into account the interaction between consequences and their long-term impact. By introducing multiple composite indexes, especially the third composite index, the potential losses of disasters can be more accurately assessed to avoid assessment errors caused by ignoring certain important factors. This means that 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, the probability of misjudgment of the risk level of the disaster type can be effectively reduced.

[0014] 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.

[0015] It should be noted that the terms used in the present invention are only for describing specific embodiments, rather than limiting the scope of the present application. As shown in the present specification, unless the context clearly indicates an exception, the words "one", "a", "a kind of" and / or "the" do not specifically refer to the singular, but may also include the plural. The terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method or device. In the absence of more restrictions, the elements defined by the sentence "include one..." do not exclude the presence of other identical elements in the process, method or device including the elements.

[0016] It should also be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are 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 therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", etc. 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 a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0017] 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 it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions 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; 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 step of optimizing the calculated first expected loss value for each disaster type to obtain a second expected loss value for each disaster type includes: 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, calculate the second expected loss value of each disaster type based on the mean severity value of all consequences caused by each disaster type, the occurrence frequency 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.

3. A method for classifying port disaster risk levels according to claim 2, 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.

4. A method for classifying port disaster risk levels according to claim 2, 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.

5. A method for classifying port disaster risk levels according to claim 2, 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.

6. A method for classifying port disaster risk levels according to claim 2, characterized in that: The calculation formula for obtaining the second composite index of each disaster type is: ； In the formula, The first 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.

7. A method for classifying port disaster risk levels according to claim 2, 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.

8. A method for classifying port disaster risk levels according to claim 2, 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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