129 results about "Response process" patented technology

The invention relates to the technical field of network operation and maintenance, in particular to an automatic operation and maintenance method and system based on artificial intelligence, and the method comprises the steps: collecting detailed log information containing a security event in real time through a security information and event management system configured at a target endpoint; performing cleaning, labeling and structured processing on the log data by utilizing a proxy artificial intelligence system to generate standardized metadata, and performing MITRE ATTamp with the standardized metadata; mapping the CK knowledge base, identifying technical features and behavior patterns of attacks, comparing enriched log data with an external threat intelligence source, analyzing TTP of a known attack group, generating a threat intelligence association report, generating a targeted response plan by using a large language model, generating an executable command sequence according to the response plan, and generating a threat intelligence association report; the proxy executor is connected with the server through a WebSocket protocol, executes a command in a POSIX shell environment, captures and returns an execution result, verifies the execution result, carries out necessary command optimization, records an optimized response to a vector database, and automatically matches a historical event and triggers a predefined response process through a vector retrieval mechanism. And continuous threat monitoring and adaptive response are realized. According to the method, the problem that a closed loop aiming at a terminal executor, data enrichment and historical event recall cannot be formed by security operation and maintenance in the prior art can be solved.

The embodiment of the invention provides a voice conversation method and system, electronic equipment, a storage medium and a program product. One method is implemented as follows: a voice dialogue stream (which can be an inquiry voice stream input by a user for a target commodity) of a user is subjected to streaming response, a plurality of dialogue text segments are generated in a segmented manner in the streaming response process, and the dialogue text segments are output in real time after being generated and stored in a first cache queue; and when it is detected that the reply text fragment is stored in the first cache queue, the stored reply text fragment is converted into a reply voice fragment in real time and played. The streaming response may be performed by an agent. Visibly, according to the response of the voice dialogue stream of the user, the dialogue is played while being generated, the waiting time from text to voice synthesis can be greatly shortened, and therefore the response time can be shortened.

The invention relates to an emergency command decision assessment method based on a four-dimensional visual cloud platform, and the method comprises the steps: collecting historical cases and heterogeneous sensing data in a structured manner, extracting multi-dimensional features, such as event types, influence factors, response processes, space-time and causal chains, carrying out the normalization processing, mapping the features into a dynamic ontology library, and carrying out the decision assessment of the emergency command. And realizing structured expression and semantic association of cross-case knowledge. On the basis, AI-driven semantic structure migration and graph neural network characteristic migration are utilized, most relevant knowledge fragments are quickly matched for new events, a prediction model is generated in a self-adaptive mode, and model dynamic optimization is achieved in combination with real-time perception data. According to the technology, the accuracy and generalization ability of knowledge migration in the emergency response process are effectively improved, continuous self-adaptive situation prediction and high-reliability decision support are realized, and the real-time performance and intelligence of an emergency command system are enhanced.

The invention provides a customer service robot response method and system based on a knowledge graph, and relates to the field of natural language processing. The method comprises the following steps: obtaining a user input query; identifying a query intention input and queried by a user and slot position information through an intention identification model; generating a knowledge graph query statement based on the query intention and the slot position information, and retrieving related entities in a knowledge graph and associated entity relationships; executing path-based multi-hop semantic reasoning and rule-based logical reasoning on the basis of entities and associated entity relationships thereof, and determining an optimal response result; and generating a natural language response based on the optimal response result. The method is used in the response process of the customer service robot based on the knowledge graph, and the technical problem that an existing customer service robot is inaccurate in response to complex problems is solved.

The invention relates to the technical field of network security, in particular to a network security operation and maintenance automatic analysis and response system based on artificial intelligence, which comprises an operation sensing module for acquiring a server state, extracting a security log, monitoring a network protocol and a transmission direction, identifying a performance bottleneck, sorting event data and generating a sensing summary sheet, the path offset identification module tracks a cross-domain path, identifies an abnormal path and generates an offset list; the behavior chain construction module sorts an event sequence and generates a behavior chain graph; the response processing module arranges processing steps, records a response process, generates an operation and maintenance execution sequence, synthesizes an output module to complete a process and generates an analysis result. According to the invention, by comparing the server resources with the historical reference, the abnormity is identified, and the event behavior basis is provided. And tracking cross-domain path lag and abnormity, and positioning threats. Arranging event data, and constructing an attack chain. The automatic response improves the speed and accuracy, shortens the response time, and enhances the attack handling capability.

The invention relates to the field of power system automation, and discloses an intelligent power distribution network feed automation control system based on multi-source information fusion, which comprises a multi-source sensor module used for collecting current data in a power distribution network in real time, and an information fusion module used for receiving the preprocessed current data and sending the preprocessed current data to the power distribution network. The multi-source fusion module is used for carrying out multi-source fusion processing on the current data by adopting a Bayesian reasoning algorithm, the fault positioning module is used for receiving a fusion result, and the optimal control module is used for receiving a grounding fault occurrence position and adopting an optimal control theory and a dynamic planning algorithm; the invention further discloses an intelligent power distribution network feed automatic control method based on multi-source information fusion. The method comprises the following steps of an acquisition stage, a fusion stage, a positioning and decision-making stage and an execution and self-healing stage. According to the invention, by constructing the Bayesian fusion and dynamic programming control mechanism, the purposes of more accurate ground fault positioning, more efficient strategy removal and more adaptive response process are achieved.

The invention relates to the technical field of data processing, and discloses a customer management method, device and equipment and a storage medium, and the method is used for establishing a dynamic customer portrait and managing a customer according to the dynamic customer portrait. The method comprises the following steps: acquiring multi-source heterogeneous logistics data, and preprocessing the multi-source heterogeneous logistics data to obtain preprocessed data; fusing the preprocessed data by using a trained multi-modal data fusion model to obtain fused data; based on a preset customer label system, performing feature extraction on the fused data through a machine learning algorithm, and generating a dynamic customer portrait according to the extracted features; generating a personalized service strategy through a multi-objective optimization algorithm according to the dynamic customer portrait and the real-time logistics state, and storing the personalized service strategy in a preset personalized service strategy library; and monitoring customer logistics data in real time, and when a preset abnormal condition occurs, triggering an early warning mechanism and matching a corresponding personalized service strategy from the personalized service strategy library to start a corresponding customer service response process.

The invention discloses a distributed sensor abnormal event identification method for intelligent traffic, and particularly relates to the technical field of traffic information perception and identification, and the method comprises the following steps: generating an abnormal information initial confidence value through deploying a sensor node with a confidence value dynamic adjustment function; during fusion processing, independent identification priorities of single node anomalies are reserved; after sequence reconstruction of a unified time reference, judging whether a response condition is met or not in combination with trajectory evolution; if yes, an abnormal response process is triggered, a space-time compensation set is constructed based on historical data of the sensing blind area for verification, and finally an abnormal intervention instruction is output and a traffic scheduling system is linked; according to the method, the sensing sensitivity, the fusion accuracy and the response timeliness of the abnormal information in a complex traffic environment are improved, the problem of an identification blind area that single-point abnormity is covered is avoided, state reconstruction and supplementary verification of the sensing blind area are realized, and the rapid intervention capability of an intelligent traffic system on emergencies is enhanced.

The invention relates to the technical field of state monitoring, in particular to an underground space infrastructure state monitoring management system based on the Internet of Things, which comprises a data acquisition marking module, a dynamic threshold adjustment module, a pattern analysis learning module, an anomaly identification prediction module, a task sorting scheduling module and a maintenance task management module. According to the method, through dynamic adjustment of the moving average and the exponentially weighted moving average and refining processing of data points, it is ensured that tiny variation is recognized in a changeable underground environment, so that the accuracy of fault prediction is greatly improved, and the fault prediction accuracy is improved by utilizing the long and short-term memory network and the sequence-to-sequence model. The system can automatically learn and identify the abnormal mode from complex multi-dimensional data, the response capability of early warning and the early warning accuracy are enhanced, the maintenance response process is optimized through intelligent task sorting and resource allocation, the time delay for coping with an emergency condition is effectively reduced, and the operation and maintenance efficiency is improved.

The invention discloses a wake-up response method based on linkage of a Beidou short message and emergency broadcast, and relates to the technical field of emergency communication and disaster early warning, and the method comprises the following steps: generating early warning information, and transmitting the early warning information to an early warning terminal; displaying early warning content and triggering a buzzer to give an alarm; if the terminal does not confirm the response within the preset time, the response is spread in a broadcast mode; if the terminal does not confirm the response again, an SOS alarm key is automatically activated, Beidou positioning is started, and the real-time position is reported to a back-end management platform; and the back-end management platform performs resource scheduling, coordinates rescue strength, tracks each response process and generates a response chain. By integrating Beidou short message communication, emergency broadcast, SOS alarm and positioning tracking technologies, a multi-level and all-around disaster early warning and response system is formed, early warning information can be quickly transmitted, and people in a disaster area can be forcibly awakened; and personnel can be ensured to obtain timely and effective rescue information and response guidance when a disaster occurs.

The invention discloses a satellite-ground fusion hybrid ad hoc network routing protocol and fault self-healing method, device and equipment and a storage medium, and the method comprises the steps: building a satellite-ground fusion network model based on the global routing information of a target region, and when a task request is received, sending the task request to a satellite-ground fusion network; generating a target routing strategy based on the task priority of the task request and the satellite-ground fusion network model, calling each node of the communication link based on the target routing strategy to carry out communication response on the task request, monitoring the communication response process of the communication link, and when the communication link has a fault, sending the fault to the satellite-ground fusion network model; according to the method, fault self-healing analysis is carried out through the target fault self-healing analysis model, a fault self-healing link is generated, and each node in the fault self-healing link is called to carry out communication response on the task request, so that communication fault self-healing in the communication response process is realized, the link stability and the fault-tolerant capability of the self-networking network in the unmanned area are effectively improved, and the self-healing efficiency of the self-networking network in the unmanned area is improved. The multi-target balance in the communication response process is realized, and the fault self-healing speed during the communication response fault is improved.

The invention provides an automatic research, judgment and coping method and device for a network public opinion event based on a large model agent. The method comprises the steps of obtaining public opinion data of the public opinion event at a current time node; performing situation awareness analysis on the public opinion data of the current time node to obtain situation data of the current time node; based on the situation data of the current time node, the basic information of the public opinion event and the element information of a plurality of historical key time nodes, adopting a pre-trained public opinion coping large model to generate a coping measure of the current time node; and automatically coping with the public opinion event based on the coping measure of the current time node. According to the public opinion research and judgment coping method and device, the coping measures of the public opinion event can be automatically generated and coping of the public opinion event can be automatically carried out through the public opinion large model, manual participation is not needed in the whole public opinion research and judgment coping process, automation is comprehensively achieved through the large model agent, and therefore the public opinion research and judgment coping accuracy and response speed are greatly improved.

An operation method of an email security system comprises the steps of: configuring security threat information synchronization data by synchronizing targeted email security threat information configured by performing a targeted email security threat inspection on an inbound mail with targeted email security threat information configured by performing a targeted email security threat inspection on an outbound mail; performing a targeted email security threat inspection corresponding to a new inbound mail or a new outbound mail using the security threat information synchronization data; and performing a targeted email security threat response process according to the targeted email security threat inspection of the new inbound mail or the new outbound mail.

The invention provides a self-adaptive collaborative security protection method based on attack path deduction, a medium and a system, and belongs to the technical field of network security. The method comprises the following steps: sampling possible paths from a current attack node to high-value assets based on an adaptive path sampling algorithm of Monte Carlo tree search to generate an attack path graph, calculating a protection effectiveness score and a service influence score according to key nodes and predicted attack actions, and generating an optimal protection instruction set based on a multi-target tradeoff function; an instruction is converted into a heterogeneous security device configuration command through a strategy execution cooperative controller, multi-device synchronous activation is realized by adopting a distributed transaction protocol based on a logic clock, and a protection effect is monitored and fed back to an artificial intelligence model for parameter optimization; the problem of protection strategy failure caused by asynchronous network security protection response and attack evolution is solved.

The invention relates to the technical field of data measurement, in particular to an online measurement system and method for measurement data of an oiling machine, and the method comprises the steps: introducing a trace disturbance signal in an oiling process, and collecting a flow fluctuation sequence before and after disturbance and a feedback value of a measurement module; according to the response relation between the flow fluctuation sequence and the metering feedback, extracting stability characteristics representing metering link integrity and response consistency; judging whether the stability characteristic is abnormal or not, and outputting an online measurement credibility score and an abnormal early warning signal of the current refueling measurement according to the stability characteristic; and when the credibility score is continuously lower than the dynamic credibility threshold value by a set number of times, triggering a metering self-diagnosis mode, carrying out backtracking analysis on related data segments in a disturbance response process, and outputting a suggestive equipment maintenance instruction or fault positioning information. The method has the advantages of being quantifiable in score and explainable in judgment, and is suitable for high-adaptability online verification and evaluation in various refueling scenes and different equipment states.

The invention provides a chemical accident emergency response method and system under real-time monitoring, and relates to the technical field of emergency response, and the method comprises the steps: carrying out the time alignment through collecting multi-source heterogeneous data in real time, and generating multi-source synchronous data; extracting multi-modal features of the multi-source synchronous data to carry out chemical accident identification; accident scene parameters are called, accident response analysis is carried out based on an accident identification result, an emergency response scheme is formulated, resource scheduling analysis is carried out, and a resource scheduling network diagram is constructed; and performing accident monitoring and early warning according to the resource scheduling network diagram in combination with the multi-source synchronous data, generating a real-time decision instruction, and pushing the real-time decision instruction and an emergency response scheme to an emergency command center. According to the method and the device, the technical problems of low chemical accident identification accuracy and response flow lag caused by lack of a multi-source heterogeneous data fusion and real-time linkage mechanism in the prior art are solved, and the technical effects of improving the chemical accident identification precision and the emergency response speed are achieved.

The invention provides an agent personal private assistant method and device and integrated electronic equipment, and the method comprises the steps: a localized deployment process of a large model: deploying the large model on an all-in-one machine, and carrying out the physical isolation; in the process of creating the personal private assistant of the intelligent agent, user exclusive data is collected to serve as a data source of an RAG of a large model, and collection means that in the process of interaction between the all-in-one machine and the user, at least one of life information, historical memory information and special sensitive information of the user is recorded in real time and is permanently memorized; the calling response process of the personal private assistant of the intelligent agent comprises a daily calling process and a special calling process; the daily calling process is that the user calls life information, historical memory information or special sensitive information through interaction with the all-in-one machine. According to the invention, a mode of'all-in-one machine localization deployment of a large model + physical isolation 'is adopted, and a permanent memory function of a computer system is utilized to solve the pain point problem of memory decline of old people.

The invention relates to the technical field of voice switches, in particular to a voice switch response optimization method and system based on off-line and on-line dual-mode switchover, and the method comprises the steps: obtaining off-line and on-line dual-mode switching parameters and performance parameters of a voice switch, building a nonlinear mapping relation between the off-line and on-line dual-mode switching parameters, solving an optimal switching parameter combination through an optimization algorithm, and obtaining a voice switch response optimization result. And a target parameter under the target performance index is obtained and issued to a voice switch control engine, the performance parameter is monitored in real time, and re-optimization is triggered when the parameter deviates. In the response process, performance parameters are monitored, and system characteristic management and control are carried out on irregular fluctuation or uncontrollable scenes; acquiring characteristic data of the target voice data, performing big data analysis in combination with the performance parameters and the switching parameters, and continuously correcting the nonlinear mapping relationship; based on historical switching data, a knowledge base and a case base are established, a standardized optimization scheme is formed, and adaptive matching adjustment is performed on switching parameters of the voice switch so as to realize efficient and stable voice switch response.

The invention relates to the technical field of power system network security, and discloses a power system network security question-answering method and system based on a network security knowledge base, and the network security question-answering method comprises the steps: receiving a power system security knowledge base and a target environment feature set, and carrying out the calculation to obtain a knowledge vulnerability matrix; based on the knowledge vulnerability matrix, generating a weakness map of the safety question-answering system of the power system; constructing an electric power system safety knowledge immune memory bank; generating immune response according to the activated immune memory unit, neutralizing potential safety weaknesses, and recording response process data to form an immune response execution report; and updating the defense capability of the system through the immunological enhancement kinetic equation to form an evolved defense capability vector. According to the method, a vulnerability function and an immunological enhancement kinetic model are established, so that the system can quantitatively evaluate the security vulnerability of different knowledge in different environments, and a defense strategy is dynamically adjusted according to the security vulnerability.

This application provides a method and system for rapid response to traffic incidents based on multi-source data fusion, relating to the field of traffic incident response technology. The method includes: extracting traffic feature vectors from multi-source traffic data for multi-source fusion calculation; determining whether abnormal traffic incidents exist in the fused situational data; when abnormal traffic incidents exist, determining the type and locating the information; generating an initial response plan based on the determined type and location information; pushing the initial response plan to the handling department's terminal and receiving execution status information from the handling department; recording the timestamps and operation logs of the entire process, and evaluating the effectiveness of this response process. This application addresses the technical problem of lacking multi-source traffic data fusion analysis in existing technologies, enabling rapid response to traffic incidents based on multi-source traffic data fusion, and achieving the technical effect of improving the accuracy of traffic incident identification.

The invention provides an intelligent contract automatic execution method and system for a culture big data transaction platform, and a medium. The method comprises the following steps: acquiring feature information of cultural asset data to generate biological information and a data hash value of a data right person, generating a right confirmation certificate structure, generating a parameterized contract according to cultural asset transaction request information, translating the code to obtain a contract code, and signing to obtain a digital contract, generating a data key of the digital contract and a transaction fund trusteeship protocol, performing execution detection on the digital contract, if the execution detection is passed, triggering a contract execution mechanism to generate an interactive response, if an abnormality occurs in a supervision response process, sending out an early warning and terminating, and arbitrating the contract; therefore, the method of right confirmation, negotiation, execution and detection of cultural data transaction is realized by constructing an intelligent contract and a supervision system, and the effectiveness and credibility of cultural data asset transaction are guaranteed.

The application discloses a consumer complaint response method and system based on AI assistance and language understanding, which splits the complaint response process into two core sub-problems of multi-modal consumer complaint data processing and feature fusion and demand attribution and response generation. In multi-modal consumer complaint data processing and feature fusion, first, regular expressions are used to denoise text, spectral subtraction is used to denoise voice, and Gaussian filtering and adaptive histogram equalization are used to denoise images; then, modal features are extracted, text is used as the core of cross-modal fusion, and entity and relationship are extracted to construct a multi-modal semantic knowledge graph. In demand attribution and response generation, Graph Transformer is used in combination with the graph and domain prior knowledge to output primary and secondary demands; a static complaint graph is constructed, an attribution path is mined through BFS and is verified through multi-modal verification; and an "emotion-demand-attribution-prevention" structure is used to optimize text and adjust the format by using LLM, and an individualized complaint response is output.

The embodiment of the invention provides a risk domain name identification method and device, electronic equipment, a storage medium and a product, and relates to the technical field of network security. The method comprises the following steps: in response to a response message of an original domain name, judging whether a redirection behavior exists in a response process of the original domain name, if the redirection behavior exists in the response process of the original domain name, acquiring a target jump address of the original domain name based on the response message, and judging whether the target jump address is a trusted address based on a preset rule, and if the target jump address is the trusted address, performing risk assessment on the original domain name, and judging whether the original domain name is a risk domain name. According to the embodiment of the invention, under the condition that the redirection behavior exists in the response process and the target jump address is the credible address, risk assessment is performed on the original domain name initiating jump, so that the risk domain name is accurately identified, and the identification accuracy of the risk domain name is remarkably improved.

The invention belongs to the technical field of network security, and discloses a network security automatic decision-making method and system based on multi-agent collaboration, and the method comprises the steps: constructing a multi-agent system; establishing a script-based standardized safety response flow library, and completing flow representation and execution arrangement of the script in the SOAR system; constructing a structured cue word for each agent, and constraining a role boundary and an output specification through the cue word; security event input is received, and event analysis, task decomposition, script selection and response execution are completed through cooperation of multiple agents; and verifying the validity of the system in the security event response based on a preset index, and iteratively optimizing the cue word and the script-based standardized security response process library according to feedback data. According to the invention, accurate, efficient and automatic response to the security event is realized by constructing a role-based, cooperative and evolvable intelligent decision-making system.

This invention discloses a precise legal consultation method and system based on multi-agent orchestration. The method includes: employing a hybrid intent classification mechanism with three levels of linkage—LLM remote reasoning, local heuristic correction, and keyword fallback—to route user requests to different paths, driving differentiated processing flows; performing dual-path retrieval of vector retrieval and knowledge graph relationship expansion in deep analysis to generate a structured analysis report; introducing a multi-dimensional context compression algorithm to reduce token overhead and illusion risk; embedding a three-stage emotional reassurance mechanism throughout the entire response process; and using a rendering type protocol to achieve front-end / back-end decoupling and unified rendering across multiple platforms, decomposing the processing into continuous dynamic feedback through a staged streaming response mechanism. This invention achieves intelligent, precise, and emotionally engaging legal consultation processes through multi-agent orchestration, significantly reducing model reasoning costs and improving the handling capacity for complex cases and user interaction experience.

A control system, method, electronic device, and storage medium for logistics equipment are disclosed. The control system includes: a gateway layer configured to receive business requests of various importance levels using multiple gateways and route the received business requests to an access layer; an access layer configured to receive business requests routed from at least one gateway through a main station, and for each business request received through the main station, redirect to a corresponding sub-site for response; and a service layer configured to, during the response process for each business request, call corresponding service applications from multiple service applications for each redirected sub-site, process the business requests corresponding to the sub-site according to the called service applications, generate control information for the logistics equipment, and control the corresponding logistics equipment to perform corresponding actions. By quickly and accurately generating control information corresponding to business requests, the efficiency and accuracy of controlling the logistics equipment are improved.

This application provides a system-level verification convergence system, method, and product, belonging to the technical field of chip verification. The system is a Python-based COcotb system verification platform, comprising: an application component (app agent) for calling a Python library-based application to perform network packet testing on the Device Under Test (DUT); a COcotbext-PCIe TLP transport layer adapter for sending and receiving PCIe packets at the TLP transport layer interface; a network packet transceiver component (pkt_gen scapy agent) for a Python library-based scapy application to execute different types of network packet sending, receiving, parsing, and automatic response processes; a COcotbext-eth TLP transport layer adapter for sending and receiving network packets at the TLP transport layer interface; and a checker component (checker agent) for generating comparison results between expected test results and the actual output results of the DUT. This application aims to improve the convergence speed of system-level verification for smart network interface cards (NICs).

The embodiment of the invention provides an interface response time delay test method and system, a medium and equipment, and the method comprises the steps: collecting continuous image frames of a response process after a target interface is triggered, and recognizing a target feature point in each continuous image frame, and constructing a comprehensive evaluation feature fusing the quantity feature, the spatial distribution feature and the hue feature of the target feature point, judging a response image frame when the target interface enters a steady state for the first time based on the change trend of the comprehensive evaluation feature in the time dimension, and determining a response time delay between the response time corresponding to the response image frame and the trigger time. According to the method, the state of the target interface in the response process is represented through the multi-dimensional features, so that the response image frame is accurately judged, and the time delay test precision is improved.

The invention, which relates to the technical field of the computer, discloses a multi-source-data-based outdoor falling risk early warning processing method and system for the elderly, comprising the following steps: collecting and fusing multi-source data; performing multi-dimensional feature extraction and correlation analysis; carrying out risk identification based on business rules; small sample machine learning identification; performing relation network auxiliary analysis; according to the method, Internet of Things devices such as video monitoring and smart bracelets are integrated, three types of recognition algorithms of a rule model, a classification model and a relation network model are creatively fused, model cooperation is realized through a weighted voting mechanism, and high recognition accuracy is still kept under the condition of small samples. A differential response process is automatically triggered based on a risk level, flexible expansion of system function modules is supported by adopting a micro-service architecture design, a whole-process closed loop of old people outdoor fall risk early warning disposal is finally realized, and the intelligent level of grassroots social governance is remarkably improved.

The invention, which relates to the technical field of flood prevention and emergency rescue, discloses a converged communication-based emergency command and dispatch system for flood prevention and emergency rescue, comprising a converged communication unit, a data fusion unit, a decision analysis unit and an intelligent dispatch unit. The communication platform serves as a core communication hub, an information interaction feedback mechanism is arranged, when the information receiving end obtains flood prevention and emergency rescue measures, automatic confirmation is carried out, feedback information is sent to the information sending end, then the subsequent response process of the information receiving end is obtained, and the flood prevention feedback efficiency coefficient of the information receiving end is calculated; meanwhile, a risk analysis model is constructed based on an LSTM neural network, then an emergency scheme recommendation list is generated, flood prevention and emergency measures are sent to a corresponding executor, namely an information receiving end, through a communication platform, a flood prevention feedback efficiency coefficient of the executor is obtained, and the execution efficiency of the executor is judged according to a preset efficiency judgment threshold. And scheme optimization is carried out according to an execution efficiency judgment result to ensure that the emergency rescue scheme is effectively executed.