A query method and system for an emergency plan based on natural disasters

Abstract

The application is suitable for the technical field of data query, and provides a query method and system of an emergency plan based on natural disasters, which comprises the following steps: receiving a query instruction sent by a cloud server, wherein the query instruction comprises identification information of a current natural disaster; judging whether the identification information is pre-stored in a database, wherein the database is provided with a plan name, a plan level, a disaster type, a plan quantity and a region position corresponding to a plan; if not, taking the identification information as a query keyword sequence, calculating the correlation between the query keyword sequence and a plan sequence set in the database; determining a target emergency plan corresponding to the query instruction according to the correlation; if yes, generating the target emergency plan corresponding to the query instruction according to the query result of the database, and using the intelligent query of the database to replace manual query, thereby effectively improving the query efficiency of the power plan.

Description

Technical Field

[0001] This invention relates to the field of data query technology, and in particular to a method and system for querying emergency plans based on natural disasters. Background Technology

[0002] In practical applications, a series of natural disasters, such as high temperatures and droughts, torrential rains, strong winds, and earthquake-related disasters, occur frequently, leading to numerous power grid accidents and damage to power system equipment. Because natural disasters are sudden events that cannot be accurately predicted in advance, and because their destructive power is significant, they have a considerable impact on the normal operation of the power system. Therefore, emergency mechanisms are pre-established to address these emergencies, allowing power companies to quickly implement contingency plans for real-time maintenance of power equipment and restore power supply as much as possible.

[0003] In existing technologies, handling power grid emergencies requires collaboration among multiple departments. Therefore, during emergency response, problems such as unclear division of responsibilities and low coordination efficiency inevitably arise. Power grid emergency plans include the emergency work content for each responsible department under emergency circumstances; however, manual review is time-consuming and cannot meet the timeliness requirements of emergency response. Summary of the Invention

[0004] This application provides a method and system for querying emergency plans based on natural disasters, which addresses the problem of low efficiency in querying emergency plans.

[0005] The first aspect of this application provides a method for querying emergency plans based on natural disasters, including:

[0006] Receive a query command sent by a cloud server, the query command including identification information of a currently occurring natural disaster;

[0007] Determine whether the identification information is pre-existing in the database, where the database contains the plan name, plan level, disaster type, number of plans, and the corresponding regional location of the plan;

[0008] If not, the identification information is used as a query keyword sequence, and the correlation between the query keyword sequence and the preset sequence in the database is calculated;

[0009] The target emergency response plan corresponding to the query instruction is determined based on the correlation.

[0010] If so, the target emergency plan corresponding to the query instruction will be generated based on the query results from the database.

[0011] Furthermore, determining whether the identification information is pre-existing in the database includes:

[0012] Extract the disaster type, the time of the disaster, and the location of the disaster from the identification information;

[0013] Based on the disaster type, time information, and address information, it is determined whether there is matching information in the database.

[0014] Furthermore, calculating the relevance between the query keyword sequence and the set plan sequence in the database includes calculating the positional relevance, string similarity, semantic relevance, and text similarity of the sequences.

[0015] Furthermore, the formula for calculating the location relevance is as follows:

[0016]

[0017] Where: m is the query vector, a is the sequence object, dist(m.λ, a.λ) is the Euclidean distance between a and m, and D Max This represents the maximum distance across all sets of objects.

[0018] Furthermore, the formula for calculating the string similarity is as follows:

[0019]

[0020] Where: ld(ms,as) is the edit distance between the corresponding keywords of m and a, len() is the function to calculate the pay length, and max(len(ms),len(as)) is the maximum value of the length of the corresponding keywords of m and a.

[0021] Furthermore, the formula for calculating the semantic relevance is as follows:

[0022]

[0023] Where: w0 and w1 are the training words, and is the input and output vectors identified by the vector representation of w, where W is the number of words in the vocabulary.

[0024] Furthermore, the formula for calculating the text similarity is as follows:

[0025]

[0026] Where: V a V is a vectorized representation of sequence objects. m This is a vectorized representation of the keywords.

[0027] A second aspect of this application provides a query system for emergency response plans based on natural disasters, including:

[0028] A query instruction receiving unit is used to receive query instructions sent by a cloud server, wherein the query instructions include identification information of a currently occurring natural disaster;

[0029] The identification information judgment unit is used to determine whether the identification information is pre-existing in the database, wherein the database is set with the plan name, plan level, disaster type, number of plans and the area location corresponding to the plan;

[0030] The relevance calculation unit is used to calculate the relevance between the identification information as a query keyword sequence and the preset sequence in the database when the identification information is not pre-existing in the database.

[0031] A target emergency response plan determination unit is used to determine the target emergency response plan corresponding to the query instruction based on the correlation.

[0032] The target emergency response plan generation unit is used to generate the target emergency response plan corresponding to the query instruction based on the query results of the database when the identification information is pre-existing in the database.

[0033] A third aspect of this application provides a computer device including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, wherein the processor, when executing the computer-readable instructions, implements the steps of the query method for emergency plans based on natural disasters as described in any of the preceding embodiments.

[0034] A fourth aspect of this application provides a readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps of the query method for emergency plans based on natural disasters as described in any of the preceding embodiments.

[0035] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0036] First, the system receives a query command from the cloud server containing identification information about a currently occurring natural disaster. Then, it determines whether this identification information is pre-existing in the database, which includes the plan name, plan level, disaster type, number of plans, and the corresponding regional location. If the information is not in the database, the identification information is used as a query keyword sequence. The correlation between the query keyword sequence and the pre-existing plan sequence in the database is calculated, and the corresponding emergency plan is determined based on the correlation. If the information exists in the database, the corresponding emergency plan is directly generated. By connecting to the cloud server to obtain query commands and sequentially determining whether the data to be queried exists in the database, the plan can be retrieved directly. If not, the corresponding plan can be determined by calculating the correlation between the queried data and the data in the database. This reduces the time spent on manual queries and effectively improves the efficiency of plan retrieval. Attached Figure Description

[0037] Figure 1 This is a schematic flowchart of an embodiment of a method for querying emergency plans based on natural disasters in this invention;

[0038] Figure 2 This is a structural block diagram of an embodiment of an emergency response plan query system based on natural disasters in this invention;

[0039] Figure 3 This is a structural block diagram of a computer device according to the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0041] The method for querying emergency response plans based on natural disasters in this embodiment is used to improve the efficiency of plan retrieval. The implementation method in this embodiment can be implemented in the system, on the server, or on the terminal; no specific limitation is made.

[0042] Example 1

[0043] Please see Figure 1 An embodiment of the method for querying emergency plans based on natural disasters in this invention includes the following steps:

[0044] S11. Receive a query command sent by the cloud server. The query command includes the identification information of the natural disaster that has occurred.

[0045] In power system accidents, besides equipment failures and human error, natural disasters are the primary cause, and their impact on the power grid is severe. When an equipment failure in a certain area is detected as being caused by a sudden natural disaster, the cloud server triggers a query command, referencing the database in the contingency plan system. This database contains emergency plans for various regions under different natural disaster conditions. The cloud server sends the query command to the system, which, upon receiving the command, matches the optimal power emergency plan for that region's natural disaster. Relevant departments can then execute their duties based on the retrieved plan.

[0046] Specifically, the query command includes the location identifier information of the natural disaster that is currently occurring. For example, when a natural disaster occurs in a certain place, the cloud server can identify the specific type of disaster, the time period of the disaster, and the location information of the equipment failure based on the local weather information of that day. Then, the cloud server sends the location as the identifier information to the query system.

[0047] S12. Determine whether the identification information is pre-existing in the database. The database contains the plan name, plan level, disaster type, number of plans, and the corresponding regional location of the plan.

[0048] In this embodiment, determining whether the identification information is pre-existing in the database includes the following steps:

[0049] 1. Extract the disaster type, time of occurrence, and location of the disaster from the identification information;

[0050] 2. Based on the disaster type, time information, and address information, determine whether there is matching information in the database.

[0051] When cloud servers identify data information generated by natural disasters, they can directly generate data packets containing disaster type, time of occurrence, and location of occurrence. For example, if a heavy rainstorm occurs in a certain area of ​​Guangzhou during a certain period, the cloud server can directly generate a data packet (identification information) from the acquired data, and then directly trigger an instruction based on the entire data packet to send it to the query system.

[0052] After receiving a data packet, the query system extracts relevant information from the data packet and then matches the extracted information against the database to check if the information exists in the database.

[0053] S13. When the identification information does not exist in the database, the identification information is used as the query keyword sequence, and the correlation between the query keyword sequence and the preset sequence in the database is calculated;

[0054] If the identification information is not found in the database, it means that the semantic text format of the identification information sent by the cloud server is inconsistent with the data text format stored in the database, and the system cannot read it. In this case, the semantics in the identification information can be used as keywords to calculate the relevance between the keywords and the text in the database. The corresponding solution can then be retrieved based on this relevance. The relevance calculation includes positional relevance, string similarity, semantic relevance, and text similarity.

[0055] The formula for calculating location relevance is as follows:

[0056]

[0057] Where: n is the query vector, a is the sequence object, dist(m.λ, a.λ) is the Euclidean distance between a and m, and D Max This represents the maximum distance across all sets of objects.

[0058] Locational relevance is determined by calculating the location distance between the identifier information and the sequence objects in the database.

[0059] The formula for calculating string similarity is as follows:

[0060]

[0061] Where: ld(ms,as) is the edit distance between the corresponding keywords of m and a, len() is the function to calculate the pay length, and max(len(ms),len(as)) is the maximum value of the length of the corresponding keywords of m and a.

[0062] String similarity is determined by calculating the length relationship between the strings.

[0063] The formula for calculating semantic relevance is as follows:

[0064]

[0065] Where: w0 and w1 are the training words, and is the input and output vectors identified by the vector representation of w, where W is the number of words in the vocabulary.

[0066] Semantic similarity is assessed by calculating the log probability in the semantics.

[0067] The formula for calculating text similarity is as follows:

[0068]

[0069] Where: V a V is a vectorized representation of sequence objects. m This is a vectorized representation of the keywords.

[0070] Text similarity is assessed by calculating the similarity between query keywords and text in the database.

[0071] S14. Determine the target emergency response plan corresponding to the query command based on the relevance;

[0072] Based on the above relevance calculation results, the similarity of the query keyword results is determined by integrating location relevance, string similarity, semantic similarity, and text similarity. When the set similarity conditions are met, the approximate text corresponding to the query keyword in the database can be determined. For example, when the names of addresses in the identification information are inconsistent, the similarity between the two can be calculated to meet the conditions, and the corresponding emergency plan can be queried based on the named text in the database.

[0073] S15. When the identification information exists in the database, the target emergency plan corresponding to the query instruction is generated based on the query results of the database.

[0074] In this embodiment, if the identification information exists in the database, it means that the text format of the identification information obtained by the cloud server is consistent with the one pre-stored in the database. Therefore, the emergency plan in the database can be directly retrieved based on the identification information. There may be multiple emergency plans in the exported emergency plan, and the user can select the appropriate emergency plan according to the specific needs.

[0075] The above embodiments retrieve corresponding emergency plans by calculating the correlation between query keywords and data in the database. The calculation process is simple and effectively improves the efficiency of plan retrieval.

[0076] Example 2

[0077] Please see Figure 2 An embodiment of the present invention, a query system for emergency plans based on natural disasters, includes the following steps:

[0078] The query instruction receiving unit 101 is used to receive query instructions sent by the cloud server. The query instructions include identification information of the currently occurring natural disaster.

[0079] The identification information judgment unit 102 is used to determine whether the identification information is pre-existing in the database. The database is set with the plan name, plan level, disaster type, number of plans and the area location corresponding to the plan.

[0080] The correlation calculation unit 103 is used to calculate the correlation between the identification information as a query keyword sequence and the preset sequence in the database when the identification information is not pre-existing in the database.

[0081] The target emergency response plan determination unit 104 is used to determine the target emergency response plan corresponding to the query command based on the relevance.

[0082] The target emergency response plan generation unit 105 is used to generate the target emergency response plan corresponding to the query command based on the query results of the database when the identification information is pre-existing in the database.

[0083] For specific limitations regarding the query system, please refer to the limitations on the query method above, which will not be repeated here. Each module in the above query system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0084] Example 3

[0085] Please see Figure 3 The present invention provides a computer device including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, wherein the processor executes the computer-readable instructions to implement the steps of the method described above.

[0086] Those skilled in the art will recognize that the units of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of the invention.

[0087] In the embodiments provided by this invention, it should be understood that the division of units is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units may be combined into one unit, one unit may be split into multiple units, or some features may be ignored. Furthermore, the functional units in the various embodiments of this invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The integrated unit described above can be implemented in hardware or as a software functional unit.

[0088] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0089] It is understood 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 therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for querying emergency response plans based on natural disasters, characterized in that, include: Receive a query command sent by a cloud server, the query command including identification information of a currently occurring natural disaster; Determine whether the identification information is pre-existing in the database, where the database contains the plan name, plan level, disaster type, number of plans, and the corresponding regional location of the plan; If not, the identification information is used as a query keyword sequence, and the relevance of the query keyword sequence to the set plan sequence in the database is calculated; the calculation of the relevance of the query keyword sequence to the set plan sequence in the database includes calculating the positional relevance, string similarity, semantic relevance and text similarity of the sequence; The formula for calculating the location relevance is as follows: in: For query vector, For sequence objects, for and Euclidean distance, The maximum distance across all objects in the set; The formula for calculating string similarity is as follows: in: for and Edit distance between corresponding keywords A function to calculate the length of a string. for and The maximum value corresponding to the keyword length; The formula for calculating the semantic relevance is as follows: in: and These are the training words, and yes The vector identifiers the input and output vectors. This represents the number of words in the vocabulary list; The formula for calculating text similarity is as follows: in: A vectorized representation of sequence objects. This is a vectorized representation of the keywords; The target emergency response plan corresponding to the query instruction is determined based on the correlation. If so, the target emergency plan corresponding to the query instruction will be generated based on the query results from the database.

2. The method for querying emergency plans based on natural disasters according to claim 1, characterized in that, The step of determining whether the identification information is pre-existing in the database includes: Extract the disaster type, the time of the disaster, and the location of the disaster from the identification information; Based on the disaster type, time information, and address information, it is determined whether there is matching information in the database.

3. A query system for emergency response plans based on natural disasters, characterized in that, The method for querying emergency response plans based on natural disasters according to any one of claims 1 to 2 includes: A query instruction receiving unit is used to receive query instructions sent by a cloud server, wherein the query instructions include identification information of a currently occurring natural disaster; The identification information judgment unit is used to determine whether the identification information is pre-existing in the database, wherein the database is set with the plan name, plan level, disaster type, number of plans and the area location corresponding to the plan; The relevance calculation unit is used to calculate the relevance between the identification information as a query keyword sequence and the preset sequence in the database when the identification information is not pre-existing in the database. A target emergency response plan determination unit is used to determine the target emergency response plan corresponding to the query instruction based on the correlation. The target emergency response plan generation unit is used to generate the target emergency response plan corresponding to the query instruction based on the query results of the database when the identification information is pre-existing in the database.

4. A computer device comprising a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, characterized in that, When the processor executes the computer-readable instructions, it implements the steps of the query method for emergency plans based on natural disasters as described in any one of claims 1 to 2.

5. A readable storage medium storing computer-readable instructions, characterized in that, When the computer-readable instructions are executed by the processor, they implement the steps of the query method for emergency response plans based on natural disasters as described in any one of claims 1 to 2.

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