Abnormal event emergency dispatch method, device, equipment and storage medium

Abstract

The present invention relates to the field of big data technology, and in particular to a method, device, equipment and storage medium for emergency dispatch of abnormal events. The present invention obtains key elements of the abnormal events by counting feedback information related to the abnormal events and performing feature extraction on the on-site feedback information. Based on the extracted key elements and the historical abnormal event data set, a target collaborative linkage plan for the abnormal events is generated to improve the efficiency of collaborative linkage when facing abnormal events. Finally, based on the target collaborative linkage plan, multi-department emergency collaborative linkage dispatch is performed on the abnormal events, thereby improving the operating efficiency between various departments and avoiding the technical problems of slow response speed and low operating efficiency when facing sudden abnormal events in the existing technology.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to an abnormal event emergency dispatch method, device, equipment and storage medium. Background Art

[0002] When an unexpected abnormal event occurs in a city, it is often necessary for multiple emergency rescue departments to work together to handle it. When facing an abnormal event, the abnormal event is generally handled according to the experience of on-site staff, decision-making by department leaders, expert consultation or pre-made emergency plans. In particular, when each department handles the event based on past experience, due to the lack of timely communication between departments, the command of each department is chaotic and difficult to effectively implement, which further leads to a vicious development of the situation and is not conducive to the economic development of the city. It can be seen that the above-mentioned emergency handling methods all have the problems of slow response speed and low operating efficiency.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide an abnormal event emergency dispatch method, device, equipment and storage medium, aiming to solve the technical problems of slow response speed and low operating efficiency in the prior art when facing sudden abnormal events.

[0005] To achieve the above object, the present invention provides an abnormal event emergency dispatch method, the method comprising the following steps:

[0006] Collect on-site feedback information of statistical abnormal events;

[0007] Extracting features from the on-site feedback information to obtain key elements of the abnormal event;

[0008] Generate a target collaborative linkage plan based on the key factors and historical abnormal event data set;

[0009] Based on the target collaborative linkage plan, multi-department emergency collaborative linkage dispatch is carried out for the abnormal event.

[0010] Optionally, extracting features from the on-site feedback information to obtain key elements of the abnormal event includes:

[0011] Integrate the on-site feedback information to obtain a description text of the abnormal event;

[0012] Extract features from the abnormal event description text using a preset feature extraction model to obtain a full-factor feature representation matrix of the abnormal event;

[0013] Performing element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event, wherein the current status description set includes at least a number of abnormal events and key elements corresponding to each abnormal event;

[0014] Accordingly, the target collaborative linkage scheme is generated based on the key elements and the historical abnormal event data set, including:

[0015] Based on the current situation description set and the historical abnormal event data set, a target collaborative linkage plan is generated.

[0016] Optionally, the performing element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event further includes:

[0017] Performing factor mining on the full-factor feature representation matrix to obtain a candidate factor set;

[0018] Classify the abnormal event description text by a preset classification model to obtain an abnormal event type set, wherein the abnormal event type set includes several types of abnormal events;

[0019] Key elements of various abnormal events are extracted from the candidate element set, and a current status description set of the abnormal events is constructed based on the various abnormal events and the key elements corresponding to the abnormal events.

[0020] Optionally, generating a target collaborative linkage solution based on the current situation description set and the historical abnormal event data set includes:

[0021] Matching corresponding candidate solution sets from the historical abnormal event dataset based on various abnormal events in the current state description set;

[0022] Calculating the similarity between the candidate element set of the abnormal event and each processing solution in the candidate solution set;

[0023] Determine a candidate processing solution based on the similarity calculation result, wherein the candidate processing solution is the processing solution with the greatest similarity to the candidate element set of the abnormal event in the candidate solution set;

[0024] The candidate processing solutions are updated according to the on-site feedback information to obtain a target collaborative linkage solution.

[0025] Optionally, updating the candidate processing solutions according to the on-site feedback information to obtain a target collaborative linkage solution includes:

[0026] Extracting on-site element information from the on-site feedback information;

[0027] The corresponding element information in the target collaborative linkage plan is updated according to the on-site element information to obtain the target collaborative linkage plan.

[0028] Optionally, before generating a target collaborative linkage solution based on the key elements and the historical abnormal event dataset, the method further includes:

[0029] Obtain historical handling plans, joint drill records, and preset emergency plans corresponding to historical abnormal events;

[0030] Constructing a basic data set of a collaborative linkage plan for abnormal events based on the historical processing plan, the joint exercise record, and the preset emergency plan;

[0031] Based on the basic data set, a semi-supervised learning model is used to generate a historical abnormal event data set.

[0032] Optionally, generating a historical abnormal event dataset through a semi-supervised learning model based on the basic dataset includes:

[0033] extracting a target data stream from the basic data set;

[0034] marking the target data stream;

[0035] The labeled target data stream is supplemented with data through a semi-supervised learning model to generate a historical abnormal event dataset.

[0036] In addition, to achieve the above-mentioned purpose, the present invention further proposes an emergency dispatch device for abnormal events, the emergency dispatch device for abnormal events comprising:

[0037] Statistics module, used for on-site feedback information of abnormal events;

[0038] An extraction module, configured to extract features from the on-site feedback information to obtain key elements of the abnormal event;

[0039] A generation module, configured to generate a target collaborative linkage plan based on the key elements and the historical abnormal event data set;

[0040] The scheduling module is used to perform multi-department emergency collaborative linkage scheduling for the abnormal event based on the target collaborative linkage plan.

[0041] In addition, to achieve the above-mentioned purpose, the present invention also proposes an abnormal event emergency dispatch device, which includes: a memory, a processor, and an abnormal event emergency dispatch program stored on the memory and runnable on the processor, and the abnormal event emergency dispatch program is configured to implement the steps of the abnormal event emergency dispatch method described above.

[0042] In addition, to achieve the above objectives, the present invention also proposes a storage medium, on which an abnormal event emergency scheduling program is stored. When the abnormal event emergency scheduling program is executed by a processor, the steps of the abnormal event emergency scheduling method described above are implemented.

[0043] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the abnormal event emergency dispatch method as described above.

[0044] One or more technical solutions proposed in this application have at least the following technical effects: This application discloses a method for emergency dispatch of abnormal events, which includes: counting on-site feedback information of abnormal events; performing feature extraction on the on-site feedback information to obtain key elements of the abnormal events; generating a target collaborative linkage plan based on the key elements and historical abnormal event data sets; and performing multi-department emergency collaborative linkage dispatch on the abnormal events based on the target collaborative linkage plan. Compared with the existing technology, this application counts feedback information related to abnormal events and performs feature extraction on the on-site feedback information to obtain key elements of abnormal events, and then generates a target collaborative linkage plan for abnormal events based on the extracted key elements and historical abnormal event data sets, thereby improving the efficiency of collaborative linkage when facing abnormal events. Finally, based on the target collaborative linkage plan, multi-department emergency collaborative linkage dispatch is performed on abnormal events, thereby improving the operating efficiency between departments and avoiding the technical problems of slow response speed and low operating efficiency when facing sudden abnormal events in the existing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0047] Figure 1 This is a flow chart of a first embodiment of the abnormal event emergency dispatch method of the present invention;

[0048] Figure 2 A schematic diagram of constructing a historical abnormal event data set according to an embodiment of the abnormal event emergency dispatch method of the present invention;

[0049] Figure 3A schematic diagram of a multi-department collaborative business process in accordance with an embodiment of an abnormal event emergency dispatch method of the present invention;

[0050] Figure 4 This is a flow chart of a second embodiment of the abnormal event emergency dispatch method of the present invention;

[0051] Figure 5 This is a structural block diagram of the first embodiment of the abnormal event emergency dispatch device of the present invention.

[0052] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0054] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0055] Based on this, the embodiment of the present invention provides an abnormal event emergency dispatch method, referring to Figure 1 , Figure 1 This is a flow chart of a first embodiment of an abnormal event emergency dispatch method according to the present invention.

[0056] In this embodiment, the abnormal event emergency dispatch method includes:

[0057] Step S10: Collecting statistics on on-site feedback information of abnormal events.

[0058] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device, terminal device, server, etc. that can implement the above functions. The following terminal device is used as an example to illustrate this embodiment and the following embodiments.

[0059] It should be noted that for sudden abnormal events such as natural disasters, accidents, public health incidents, social security incidents, etc., in order to ensure the rapid, orderly and effective implementation of emergency rescue operations, reduce accident losses, and achieve emergency coordination and linkage dispatch and command, there are usually the following methods to formulate emergency coordination and linkage plans: 1. Experience guidance method; 2. Leadership decision-making method; 3. Expert consultation method and 4. Pre-formulation method.

[0060] Among them, the experience-based guidance method, leadership decision-making method, or expert consultation method all rely on the experience of the handling personnel to decide which specific measures should be taken to deal with sudden abnormal events, and request relevant resources and personnel assistance from surrounding areas and higher-level departments. However, since the experience-based guidance basically relies on the experience of emergency response personnel to formulate abnormal event coordination and linkage plans, the efficiency of generating plans is extremely low and time-consuming. Sometimes, in order to design a reasonable plan, emergency response personnel need to revise it repeatedly, which takes a long time. In addition, once a small number of special, highly professional, difficult, major, and sensitive events occur, they cannot rely on past experience. The coordination and linkage plans formulated based on experience are neither accurate nor rigorous. In addition, in highly urgent situations, emergency response personnel need to master a large amount of event-related professional knowledge and background knowledge, such as professional, geographical, legal and regulatory knowledge, and emergency resource deployment, in order to make correct decisions quickly on sudden abnormal events. This large amount of knowledge is impossible for emergency response personnel to achieve by memory alone. In addition, any decision has an optimal timing problem. Since emergency decision-making has more stringent time requirements, even if experts are dispatched to the scene for consultation as soon as possible, it will take a lot of time, resulting in the loss of the best opportunity to resolve sudden abnormal events. Due to the uncertainty of emergencies and the ever-changing on-site conditions, experts are generally experts in a certain area and cannot be experts in all aspects. Therefore, there are risks in relying too much on experts to develop emergency action plans.

[0061] The pre-formulation method refers to formulating a corresponding set of abnormal event collaborative linkage plans in advance. When a sudden abnormal event occurs, a set of abnormal event collaborative linkage plans that match the current event is retrieved from the collaborative linkage plan data set based on the current event information.

[0062] This approach has the following problems: Pre-defined coordination plans for abnormal events cannot cover all types of abnormal emergencies. Emergency situations are complex and dynamic, and the dynamics of environmental factors associated with an event vary. Pre-defined coordination plans for a particular type of event cannot account for all dynamic factors.

[0063] Based on this, this embodiment extracts the key elements of abnormal events through training models, and matches the key elements with the processing solutions in the historical abnormal event data set in the database, so as to obtain solutions that can solve abnormal events to the greatest extent and reduce the impact of abnormal events.

[0064] It can be understood that on-site feedback information includes but is not limited to the collection of urban Internet of Things, feedback information from people at risk and disposal personnel on site, basic geographic information on site and data reported by business systems of various departments, such as: real-time collection and storage of on-site urban spatial element information, urban infrastructure information, urban social demographic information, urban climate environment and other information, feedback information from people at risk and disposal personnel on site, as well as data reported from various subordinate departments, real-time messages from the network, etc. This embodiment does not impose specific restrictions on this.

[0065] Step S20: extracting features from the on-site feedback information to obtain key elements of the abnormal event.

[0066] It should be understood that feature extraction of on-site feedback information can eliminate some of the confusing and invalid information caused by abnormal events, and can also determine the key elements of abnormal events so as to provide collaborative processing solutions more quickly. For example, if a fire occurs in a certain place, the on-site feedback information may contain fire alarm records of the masses, inspection records of relevant departments, and urban monitoring records. At this time, the key elements of this information can be extracted, such as location, time, size of the fire, and whether there are dangerous goods, so as to quickly provide a collaborative processing solution later.

[0067] Step S30: Generate a target collaborative linkage plan based on the key elements and historical abnormal event data set.

[0068] It should be noted that the historical abnormal event data set refers to a data set stored in a database that records various abnormal events and corresponding processing solutions. The historical abnormal event data set includes various types of abnormal events that have occurred in the local history and the corresponding processing records, as well as the currently disclosed various types of abnormal times and corresponding processing records, and the drill records organized by various departments for various emergencies.

[0069] Furthermore, before generating a target collaborative linkage solution based on the key elements and the historical abnormal event data set, the method further includes:

[0070] Obtain historical handling plans, joint drill records, and preset emergency plans corresponding to historical abnormal events;

[0071] Constructing a basic data set of a collaborative linkage plan for abnormal events based on the historical processing plan, the joint exercise record, and the preset emergency plan;

[0072] Based on the basic data set, a semi-supervised learning model is used to generate a historical abnormal event data set.

[0073] In the specific implementation, urban disaster potential threat assessment, urban facility disaster resistance capacity assessment, major hazardous source risk assessment, etc. are carried out for major urban safety assurance systems (such as lifeline systems, refuge passages, refuge spaces, etc.), as well as dangerous sources that pose a major threat to urban safety (such as nuclear power plants, dangerous factories, etc.). At the same time, various types of abnormal events that have occurred in the city (county) emergency departments over the years and the corresponding detailed historical records of disposal plans are collected and sorted out. Detailed records of joint drills organized by various departments for various emergencies are compiled. Combined with the pre-released emergency plans for dealing with various emergencies, a basic data set for the collaborative linkage plan of abnormal events is constructed.

[0074] After generating the basic data set, a historical abnormal event data set is established through a semi-supervised learning method. Further, generating the historical abnormal event data set through a semi-supervised learning model based on the basic data set includes:

[0075] extracting a target data stream from the basic data set;

[0076] marking the target data stream;

[0077] The labeled target data stream is supplemented with data through a semi-supervised learning model to generate a historical abnormal event dataset.

[0078] In the specific implementation, refer to Figure 2 , a small amount of data is selected from the basic data set of the abnormal event collaborative linkage plan, and manually labeled. The labeled data set is supplemented and improved with the description of the abnormal event type and related components. For example: there are only abnormal events such as fire, earthquake, and waterlogging in the historical data, but since the above abnormal events will cause traffic jams, when extracting the elements of the existing abnormal events, the traffic jam can be extracted and labeled as a new abnormal event separately, and the processing plan for the abnormal event corresponding to the traffic jam can be supplemented according to the existing processing plan, forming a new data stream, increasing the data volume, adapting to more scenarios, and enriching the historical abnormal event data set.

[0079] Step S40: Perform multi-department emergency collaborative linkage dispatch for the abnormal event based on the target collaborative linkage plan.

[0080] Understandably, the reference Figure 3 When conducting multi-department emergency coordination and dispatch, the time, location, rescue object, rescue route and other elements of the abnormal event can be pushed to the command center's IOC early warning screen to provide decision-making support for the command center, and help to comprehensively coordinate the emergency coordination and dispatch command of various departments, thereby realizing efficient and rapid department coordination and dispatch, and reducing the impact of abnormal events.

[0081] This embodiment obtains the key elements of abnormal events by counting feedback information related to abnormal events and extracting features from the on-site feedback information. Based on the extracted key elements and the historical abnormal event data set, a target collaborative linkage plan for abnormal events is generated to improve the efficiency of collaborative linkage when facing abnormal events. Finally, based on the target collaborative linkage plan, multi-department emergency collaborative linkage scheduling is carried out for abnormal events, thereby improving the operating efficiency between various departments and avoiding the technical problems of slow response speed and low operating efficiency when facing sudden abnormal events in the existing technology.

[0082] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 4 Step S20 includes:

[0083] Step S201: Integrate the on-site feedback information to obtain a description text of the abnormal event.

[0084] Step S202: extracting features from the abnormal event description text using a preset feature extraction model to obtain a full-factor feature representation matrix of the abnormal event.

[0085] Step S203: performing element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event, wherein the current status description set includes at least a number of abnormal events and key elements corresponding to each abnormal event.

[0086] It should be noted that integrating on-site feedback information means classifying it according to the source of information and integrating it into a file to form a description text of the abnormal event. The description text of the abnormal event can be updated in real time according to the on-site data, reducing resource waste while solving abnormal events. For example: a traffic jam occurs in a certain place due to a vehicle collision. Because the colliding vehicles were not removed in time, the traffic jam is large. As long as the colliding vehicles are removed, the traffic will be quickly unblocked. If the traffic police department is dispatched to clear the traffic, a lot of human resources will be wasted.

[0087] The preset feature extraction model can be a feature extraction model based on a deep learning algorithm, such as a Transformer model, or other models that can achieve the same or similar functions. This embodiment does not impose any specific restrictions on this.

[0088] Furthermore, the performing of element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event further includes:

[0089] Performing element mining on the full-element feature representation matrix to obtain a candidate element set;

[0090] Classifying the abnormal event description text by a preset classification model to obtain an abnormal event type set, wherein the abnormal event type set includes several types of abnormal events;

[0091] Key elements of various abnormal events are extracted from the candidate element set, and a current status description set of the abnormal events is constructed based on the various abnormal events and the key elements corresponding to the various abnormal events.

[0092] The preset classification model may be a classification model based on a conditional random field, or may be other models that can achieve the same or similar functions, and this embodiment does not impose any specific restrictions on this.

[0093] Specifically, the Transformer model is used to extract features from the description text of abnormal events to form a feature representation matrix of all abnormal events. Then, the Conditional Random Fields (CRF) method is used to mine the feature representation matrix to obtain the candidate feature set E = {e1, e2, e3, ..., e m}, and then use the classic normalized exponential function (SoftMax) classifier to classify the abnormal event description text, and obtain the current abnormal event type set I = {i1,i2,...i n}, where i1 is the main abnormal event and the rest are secondary abnormal events.

[0094] For each abnormal event i∈I, the attention mechanism is used to extract the key elements of the abnormal event from the candidate element set E to form a current status description set of the abnormal event

[0095]

[0096] Accordingly, in this embodiment, step S30 includes:

[0097] Step S301: matching corresponding candidate solution sets from the historical abnormal event data set based on various abnormal events in the current state description set.

[0098] Step S302: Calculate the similarity between the candidate element set of the abnormal event and each processing solution in the candidate solution set.

[0099] Step S303: determining a candidate processing solution according to the similarity calculation result, wherein the candidate processing solution is the processing solution with the greatest similarity to the candidate element set of the abnormal event in the candidate solution set.

[0100] Step S304: updating the candidate processing solutions according to the on-site feedback information to obtain a target collaborative linkage solution.

[0101] In the specific implementation, first, for each type of abnormal event s in the current situation description set S i , obtain the corresponding candidate solution set {A1,A2...A k}, then, through the BM25 algorithm, calculate the candidate solution set and the current event element set E i The most similar solution, the calculation formula for abnormal event similarity is:

[0102]

[0103] Among them, W e Represents the weight of factor e, R(e,A k ) represents E i Element e and candidate A k 's relevance score.

[0104] Furthermore, the updating of the candidate processing solutions according to the on-site feedback information to obtain a target collaborative linkage solution includes:

[0105] Extracting on-site element information from the on-site feedback information;

[0106] The corresponding element information in the target collaborative linkage plan is updated according to the on-site element information to obtain the target collaborative linkage plan.

[0107] Finally, the time, location, rescue object, rescue route and other elements of the current abnormal event are used to replace the most similar plan to form a collaborative linkage plan, and the main abnormal events and secondary abnormal events are merged to form a collaborative linkage plan for the final abnormal event. Combined with the business work processes of various departments, integrated communication means are used to carry out urban emergency collaborative linkage dispatch and command.

[0108] This embodiment obtains a description text of the abnormal event by integrating the on-site feedback information; performs feature extraction on the description text of the abnormal event through a preset feature extraction model to obtain a full-factor feature representation matrix of the abnormal event; performs element mining on the full-factor feature representation matrix to obtain a current status description set of the abnormal event, wherein the current status description set includes at least several abnormal events and key elements corresponding to each abnormal event; based on the current status description set and the historical abnormal event data set, a target collaborative linkage plan is generated; by extracting the full-factor identification matrix and the current status description set of the abnormal event, a target collaborative linkage plan is generated, thereby improving the collaborative efficiency between departments.

[0109] This application also provides an abnormal event emergency dispatch device, please refer to Figure 5 , the abnormal event emergency dispatch device includes:

[0110] The statistics module 10 is used for on-site feedback information of abnormal events.

[0111] The extraction module 20 is used to extract features from the on-site feedback information to obtain key elements of the abnormal event.

[0112] The generation module 30 is used to generate a target collaborative linkage plan based on the key elements and the historical abnormal event data set.

[0113] The scheduling module 40 is used to perform multi-department emergency coordinated linkage scheduling for the abnormal event based on the target coordinated linkage plan.

[0114] This embodiment obtains the key elements of abnormal events by counting feedback information related to abnormal events and extracting features from the on-site feedback information. Based on the extracted key elements and the historical abnormal event data set, a target collaborative linkage plan for abnormal events is generated to improve the efficiency of collaborative linkage when facing abnormal events. Finally, based on the target collaborative linkage plan, multi-department emergency collaborative linkage scheduling is carried out for abnormal events, thereby improving the operating efficiency between various departments and avoiding the technical problems of slow response speed and low operating efficiency when facing sudden abnormal events in the existing technology.

[0115] In one embodiment, the extraction module 20 is further used to integrate the on-site feedback information to obtain an abnormal event description text; perform feature extraction on the abnormal event description text through a preset feature extraction model to obtain a full-factor feature representation matrix of the abnormal event; perform element mining on the full-factor feature representation matrix to obtain a current status description set of the abnormal event, and the current status description set includes at least several abnormal events and key elements corresponding to each abnormal event; accordingly, generating a target collaborative linkage plan based on the key elements and historical abnormal event data sets includes: generating a target collaborative linkage plan based on the current status description set and the historical abnormal event data sets.

[0116] In one embodiment, the generation module 30 is further used to perform element mining on the full-element feature representation matrix to obtain a candidate element set; classify the abnormal event description text through a preset classification model to obtain an abnormal event type set, and the abnormal event type set includes several types of abnormal events; extract key elements of each type of abnormal event from the candidate element set, and construct a current status description set of the abnormal event based on each type of abnormal event and the key elements corresponding to each type of abnormal event.

[0117] In one embodiment, the generation module 30 is also used to match corresponding candidate solution sets from the historical abnormal event data set based on various abnormal events in the current state description set; calculate the similarity between the candidate element set of the abnormal event and each processing solution in the candidate solution set; determine the candidate processing solution based on the similarity calculation result, and the candidate processing solution is the processing solution in the candidate solution set with the greatest similarity to the candidate element set of the abnormal event; update the candidate processing solution according to the on-site feedback information to obtain the target collaborative linkage solution.

[0118] In one embodiment, the generating module 30 is further configured to extract on-site element information from the on-site feedback information; and update corresponding element information in the target collaborative linkage scheme according to the on-site element information to obtain the target collaborative linkage scheme.

[0119] In one embodiment, the generation module 30 is also used to obtain historical processing plans, joint drill records and preset emergency plans corresponding to historical abnormal events; construct a basic data set of abnormal event collaborative linkage plans based on the historical processing plans, the joint drill records and the preset emergency plans; and generate a historical abnormal event data set based on the basic data set through a semi-supervised learning model.

[0120] In one embodiment, the generation module 30 is further used to extract a target data stream from the basic data set; label the target data stream; and perform data completion on the labeled target data stream through a semi-supervised learning model to generate a historical abnormal event data set.

[0121] The present application provides an abnormal event emergency dispatch device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the abnormal event emergency dispatch method in the above-mentioned embodiment one.

[0122] The abnormal event emergency dispatch device provided in this application, employing the abnormal event emergency dispatch method of the aforementioned embodiment, can resolve the technical issues of abnormal event emergency dispatch. Compared to the prior art, the beneficial effects of the abnormal event emergency dispatch device provided in this application are the same as those of the abnormal event emergency dispatch method provided in the aforementioned embodiment. The other technical features of this abnormal event emergency dispatch device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0123] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0124] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0125] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer program) stored thereon, and the computer-readable program instructions are used to execute the abnormal event emergency dispatch method in the above-mentioned embodiment.

[0126] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0127] The computer-readable storage medium may be included in the abnormal event emergency dispatch device; or may exist independently without being assembled into the abnormal event emergency dispatch device.

[0128] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the abnormal event emergency dispatch device, the abnormal event emergency dispatch device can perform abnormal event emergency dispatch.

[0129] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0130] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0131] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0132] The computer-readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned method for emergency dispatching for abnormal events, thereby resolving the technical issues of emergency dispatching for abnormal events. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the method for emergency dispatching for abnormal events provided in the aforementioned embodiments, and are not further elaborated here.

[0133] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned abnormal event emergency dispatch method when executed by a processor.

[0134] The computer program product provided in this application can solve the technical problem of emergency dispatch of abnormal events. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the emergency dispatch method of abnormal events provided in the above embodiment, and will not be repeated here.

[0135] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for emergency dispatching of abnormal events, characterized in that: The abnormal event emergency dispatch method includes: Collect on-site feedback information of statistical abnormal events; Extracting features from the on-site feedback information to obtain key elements of the abnormal event; Generate a target collaborative linkage plan based on the key factors and historical abnormal event data set; Conduct multi-department emergency coordination and linkage dispatch for the abnormal event based on the target coordination and linkage plan; The feature extraction of the on-site feedback information to obtain key elements of the abnormal event includes: Integrate the on-site feedback information to obtain a description text of the abnormal event; Perform feature extraction on the abnormal event description text using a preset feature extraction model to obtain a full-factor feature representation matrix of the abnormal event; Performing element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event, wherein the current status description set includes at least a number of abnormal events and key elements corresponding to each abnormal event; The performing element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event further includes: Performing element mining on the full-element feature representation matrix to obtain a candidate element set; Classifying the abnormal event description text by a preset classification model to obtain an abnormal event type set, wherein the abnormal event type set includes several types of abnormal events; Key elements of various abnormal events are extracted from the candidate element set, and a current status description set of the abnormal events is constructed based on the various abnormal events and the key elements corresponding to the various abnormal events.

2. The method according to claim 1, wherein The generating of a target collaborative linkage plan based on the key elements and the historical abnormal event data set includes: Based on the current situation description set and the historical abnormal event data set, a target collaborative linkage plan is generated.

3. The method according to claim 2, wherein Generating a target collaborative linkage solution based on the current situation description set and the historical abnormal event data set includes: Matching corresponding candidate solution sets from the historical abnormal event dataset based on various abnormal events in the current state description set; Calculating the similarity between the candidate element set of the abnormal event and each processing solution in the candidate solution set; Determine a candidate processing solution based on the similarity calculation result, wherein the candidate processing solution is the processing solution with the greatest similarity to the candidate element set of the abnormal event in the candidate solution set; The candidate processing solutions are updated according to the on-site feedback information to obtain a target collaborative linkage solution.

4. The method according to claim 3, wherein The updating of the candidate processing solutions according to the on-site feedback information to obtain a target collaborative linkage solution includes: Extracting on-site element information from the on-site feedback information; The corresponding element information in the target collaborative linkage plan is updated according to the on-site element information to obtain the target collaborative linkage plan.

5. The method according to claim 1, wherein Before generating a target collaborative linkage solution based on the key elements and the historical abnormal event data set, the method further includes: Obtain historical handling plans, joint drill records, and preset emergency plans corresponding to historical abnormal events; Constructing a basic data set of a collaborative linkage plan for abnormal events based on the historical processing plan, the joint exercise record, and the preset emergency plan; Based on the basic data set, a semi-supervised learning model is used to generate a historical abnormal event data set.

6. The method according to claim 5, wherein The method of generating a historical abnormal event dataset based on the basic dataset through a semi-supervised learning model includes: extracting a target data stream from the basic data set; marking the target data stream; The labeled target data stream is supplemented with data through a semi-supervised learning model to generate a historical abnormal event dataset.

7. An emergency dispatch device for abnormal events, characterized in that: The abnormal event emergency dispatch device includes: Statistics module, used for on-site feedback information of abnormal events; An extraction module, configured to extract features from the on-site feedback information to obtain key elements of the abnormal event; A generation module, configured to generate a target collaborative linkage plan based on the key elements and the historical abnormal event data set; A scheduling module, configured to perform multi-department emergency collaborative scheduling for the abnormal event based on the target collaborative linkage plan; The extraction module is further used to integrate the on-site feedback information to obtain a description text of the abnormal event; Perform feature extraction on the abnormal event description text using a preset feature extraction model to obtain a full-factor feature representation matrix of the abnormal event; Performing element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event, wherein the current status description set includes at least a number of abnormal events and key elements corresponding to each abnormal event; The performing element mining on the full-element feature representation matrix to obtain a current status description set of the abnormal event further includes: Performing element mining on the full-element feature representation matrix to obtain a candidate element set; Classifying the abnormal event description text by a preset classification model to obtain an abnormal event type set, wherein the abnormal event type set includes several types of abnormal events; Key elements of various abnormal events are extracted from the candidate element set, and a current status description set of the abnormal events is constructed based on the various abnormal events and the key elements corresponding to the various abnormal events.

8. An abnormal event emergency dispatch device, characterized in that: The abnormal event emergency dispatch device includes: a memory, a processor, and an abnormal event emergency dispatch program stored in the memory and executable on the processor, wherein the abnormal event emergency dispatch program is configured to implement the steps of the abnormal event emergency dispatch method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores an emergency dispatch program for abnormal events, and when the emergency dispatch program for abnormal events is executed by the processor, the steps of the emergency dispatch method for abnormal events according to any one of claims 1 to 6 are implemented.

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