112 results about "Vulnerability index" patented technology

The invention belongs to the technical field of base station equipment management, and discloses a base station equipment management method and system based on big data. The method comprises the following steps: firstly, collecting security situation data of a physical layer, a network layer and an application layer, extracting time sequence behavior characteristics, performing cross-layer correlation analysis, and constructing an equipment security credibility dynamic evaluation model; then, identifying vulnerability indexes of control nodes according to the trust attenuation curve, and constructing a cascade risk conduction model in combination with a topological connection relationship; dynamically dividing a security isolation domain based on the model and generating protection parameters and control rules; further, a differentiated security policy is configured, and a cross-domain collaborative response channel is established; and finally, dynamically adjusting the isolation domain boundary and the security policy by monitoring the security event frequency and the interception success rate in real time. According to the invention, the conversion from passive defense to active prediction is realized, and the safety protection capability and operation stability of the base station equipment are improved.

The invention discloses a multi-model game method for multi-scene intelligent safety management. The method comprises the following steps: acquiring multi-domain original data and generating information structure features; the heterogeneous indexes are uniformly mapped into information loss components based on the features, and stable routing of the game template is carried out in combination with sequential statistics and hysteretic decision; performing game payment-oriented decision sensitive subspace compression on the unified semantic state output after routing; a dynamic risk-to-go (dynamic risk surplus) time difference method is adopted to generate step risk signals meeting total amount conservation, and the step risk signals are injected into a compression space; and through online estimation of the spectral radius of the Jacobian matrix of the optimal response operator, an equilibrium vulnerability index is generated, and stability management and closed-loop adjustment of an equilibrium point are realized. According to the invention, the decision adaptability, stability and robustness of the intelligent system in a dynamic confrontation environment can be improved.

The invention discloses an island ecological restoration effect comprehensive evaluation method, and particularly relates to the technical field of ecological environment evaluation. Obtaining a restoration area ecological basic parameter set, and constructing an original ecological characteristic matrix; calculating a restoration response curve based on the time sequence change characteristics, and determining the restoration response weight of each ecological factor; calculating a restoration net effect through a normalized difference model of parameters of a contrast area, and eliminating the influence of natural fluctuation; inputting the net effect vector into an ecological system structure coupling model, and quantifying the coupling strength between ecological factors to obtain a restoration comprehensive contribution degree; further performing space-time interpolation analysis to form a restoration effect distribution matrix and calculating a restoration vulnerability index; generating a repair optimization suggestion set according to a threshold value distribution result, and outputting a comprehensive evaluation report; according to the method, dynamic quantification and systematized diagnosis of the ecological restoration process are realized, the spatio-temporal evolution characteristics and restoration effect differences of the island ecosystem can be accurately reflected, and a scientific basis is provided for ecological restoration optimization and intelligent decision making.

The invention relates to the technical field of supply chain risk management, and particularly discloses a comprehensive risk early warning method and system fusing a supply chain graph and machine learning, and the method comprises the steps: collecting supply chain multi-modal heterogeneous data and prior risk knowledge, dynamically constructing and updating a sequential supply chain knowledge graph, and carrying out the early warning of the risk of a supply chain. Performing node-level, edge-level and system-level multi-level anomaly detection, generating an anomaly score and a network vulnerability index, when the anomaly score exceeds a dynamic threshold value, deducing risk propagation and node sweep probability by improving an SEIR model, calculating a dynamic fusion weight in combination with data source authority and the like, and performing weighted fusion on multi-dimensional indexes to generate a comprehensive risk score, and dynamically adjusting a threshold value to generate graded early warning, an optimization model, a map and a priori knowledge base. According to the method, the defects of lag, isolation and stiffness of a traditional method can be overcome, risk perception in advance, comprehensive coverage and accurate early warning are achieved, the method has the self-evolution capacity, the method adapts to dynamic changes of a supply chain, and powerful support is provided for safety and stability of an industrial chain.

The invention discloses a power transmission line disaster monitoring data fusion analysis method and system. The method comprises the following steps: acquiring historical meteorological data in a target area; acquiring satellite remote sensing data of a target area, and extracting a plurality of microtopographic factors; obtaining standing book and space topology information of the power transmission line in the target area, and obtaining an anti-galloping vulnerability index of each line section; constructing and training a statistical interpolation model and a machine learning fusion model based on the historical meteorological data and the plurality of microtopographic factors, and generating a meteorological element sequence along the power transmission line in the target area; and based on the meteorological element sequence, the anti-galloping vulnerability index and a multi-meteorological element collaborative threshold condition, calculating the historical galloping occurrence frequency and intensity of the target area, and combining with meteorological prediction data to obtain a galloping disaster dynamic risk early warning result of the power transmission line. According to the invention, the anti-galloping vulnerability index, the multi-meteorological-element collaborative threshold and the meteorological prediction data are combined, and the accuracy of a disaster risk early warning result is improved.

The invention provides a physical attribute-external environment fused single building flood vulnerability assessment method and device. According to the method, the physical attribute vulnerability characteristics of the single building are automatically and efficiently extracted based on the deep learning model; adopting an entropy weight method to quantify external environment vulnerability indexes of the single building; a four-quadrant coupling analysis model fusing physical attributes of a single building and an external environment is constructed, a multi-dimensional building flood grading system is established, and visualization and accurate positioning of vulnerability grades are realized in combination with a GIS spatial analysis technology. According to the method, the technical level of urban flood vulnerability assessment is improved, the assessment result is more accurate and efficient, and a scientific basis and technical support are provided for urban flood control and disaster reduction decisions.

The invention relates to the technical field of quality supervision and early warning management, in particular to an AI-based subway engineering construction quality supervision and early warning management system and method, and the system comprises a process data fusion module which obtains the sensor monitoring data deviation degree, the material detection qualified rate and the personnel operation specification conformity of a shield tunneling process. According to the method, a quality vulnerability index for expressing process state fluctuation is established by fusing a sensor monitoring data deviation degree, a material detection qualification rate and a personnel operation specification conformity, and an accumulated risk assessment mode based on a process chain conduction relation is formed by combining dynamic quantification of an upstream process defect on a downstream influence probability. And the capability of identifying the coupling influence between the working procedures is enhanced. And synchronously analyzing information request metadata, scheduling personnel hour data, access control behavior records and rectification cycle time, and constructing a multi-dimensional collaborative efficiency index sequence covering information circulation efficiency, personnel operation load and problem solving efficiency.

The invention relates to the technical field of sewage treatment and gas monitoring control, in particular to a distributed monitoring system for gas emission tracking. The system comprises a working condition data acquisition unit, an emission reference modeling unit, a model deviation analysis unit, a vulnerability deduction unit and an anti-vulnerability control unit. The system obtains a predicted emission value by constructing a physical information neural network model, compares the predicted emission value with a measured value to calculate a deviation, and generates an attack state flag; the method is characterized in that a microbial flora vulnerability index is calculated in combination with an attack state flag and a carbon source fluctuation rate; when the vulnerability index exceeds a preset biological safety threshold value, the system adaptively switches to a biological priority mode; according to the method, real-time quantification of the credibility of the model is realized, and invisible biochemical attacks with unknown toxicity sources can be effectively identified.

The invention discloses a weak link identification method and device for a power distribution system, electronic equipment and a program product, and relates to the field of power distribution systems.The method comprises the steps that classified typical disaster scenes and line fault probabilities in the typical disaster scenes are analyzed; evaluating a power supply operation state of the power distribution system after each typical disaster scene occurs by using a maximum power supply capability model, calculating element risk parameters of the power distribution system based on the power supply operation state and the line fault probability, and weighting and calculating a state weakness index by combining the element risk parameters of the power distribution system and scene weight parameters; and calculating a structure vulnerability index based on the centrality index of the node and the scene weight parameter weighting, fusing the state vulnerability index and the structure vulnerability index, and identifying a node weak link in the power distribution system. According to the invention, a technical problem of low accuracy of an evaluation result because only evaluation of a physical structure of the power distribution system is carried out in weak link evaluation of the power distribution system in related technologies is solved.

The invention relates to a multi-disaster coupling tough power grid dynamic defense method and a storage medium, and the method comprises the steps: a multi-disaster coupling analysis module receives disaster data and power grid data in real time, carries out the grid processing, obtains a disaster coupling value H of each grid, and carries out the risk grade division of each grid; the dynamic toughness evaluation module calculates the node vulnerability index of each grid according to the disaster coupling value H of each grid and the real-time data of the power grid; the collaborative recovery decision module formulates an optimal recovery strategy for the execution terminal by adopting a mixed integer linear programming model MILP according to the vulnerability index of each grid node, the equipment importance grading information and the fault influence range information; and the execution terminal executes the instruction according to the optimal recovery strategy and feeds back the executed state data in real time. Compared with the prior art, the method provided by the invention solves the three major problems of vulnerability identification lagging, low recovery resource scheduling efficiency and difficulty in cross-department collaboration of the oversize urban power grid under composite extreme disasters.

The invention discloses a dynamic voltage recovery and flicker suppression method based on light-storage cooperation, and relates to the technical field of power quality control of a power distribution network, and the method comprises the steps: obtaining a dynamic topological structure and a node impedance spectrum of the power distribution network in real time; calculating the vulnerability index of each node based on the data; generating a risk thermodynamic diagram according to the vulnerability index; proactive power scheduling is performed on the energy storage system based on a thermodynamic diagram, node impedance characteristics can be actively shaped and optimized in combination with impedance, the system comprises an intelligent monitoring unit, a central control platform, the energy storage system and a communication network, weak links of the system can be accurately recognized, the problems that a voltage disturbance propagation path is uncertain and the early warning adaptability is poor are solved, and the system reliability is improved. The perspectiveness and the accuracy of voltage disturbance suppression are improved, and the voltage stability and the power supply reliability of the power distribution network are enhanced.

The invention relates to the technical field of information asset management and control, and discloses an information asset management system and a protection intensity evaluation method thereof. An asset identification module of the method obtains original attribute data of information assets, and generates asset identification codes according to asset types and storage positions; the classification mapping module extracts asset key attributes and establishes an association relationship between the asset identification codes and the key attributes; the risk assessment module calculates an asset vulnerability index based on the key attribute, and generates a risk level in combination with external threat data; the dynamic adjustment module updates the key attribute according to the risk level change, and recalculates the vulnerability index; and the access control module generates an access authority strategy according to the updated vulnerability index, and restricts asset access behaviors. The system realizes refined and dynamic management of information assets, balances asset security and management efficiency, and meets the requirements of organizations for information asset management.

The invention relates to the technical field of data analysis, in particular to a natural disaster engineering rescue data platform construction and intelligent analysis system, which comprises an edge intelligent sensing module for generating a field three-dimensional live-action grid through laser radar point cloud and visible light video fusion and extracting disaster feature vectors; the cloud deep analysis module adopts a graph neural network to aggregate multi-source data, and generates a global disaster evolution graph composed of disaster grade distribution and infrastructure vulnerability indexes; the dynamic decision generation module is used for generating a space-time cooperative rescue instruction set composed of an equipment scheduling path and an engineering disposal sequence in combination with a rescue resource library and engineering constraints including an equipment mechanical arm operation radius and an aftershock influence coefficient; and the closed-loop optimization module is used for collecting operation feedback logs, correcting extraction weights of disaster feature vectors through a difference comparison engine, and dynamically updating an engineering constraint library. According to the invention, unified cooperation of disaster sensing intelligence, task allocation optimization and response process closed loop is realized.

This invention relates to the field of ischemic injury model construction technology, and particularly to a method for constructing a mouse ischemic injury model for evaluating the protective effect of GDF-15. The method includes acquiring a dataset of mouse physiological parameters to determine physiological feature vectors, thereby determining an individual vulnerability index and performing similarity matching with the vulnerability index of a specific individual. Based on the matching results, a matching sample set is constructed, and then an ischemic injury model is constructed using a deep learning network model. The model is then dynamically simulated using the specific individual vulnerability index, specific intermediate monitoring data, and specific infarct area percentage data to output a simulated protective effect index to determine if the model is qualified. If unqualified, the similarity matching threshold is adjusted based on the degree of deviation, and the matching and model construction are repeated. This invention significantly improves the uniformity and construction success rate of the ischemic injury model through individualized matching and dynamic feedback optimization, providing a reliable model for evaluating the protective effect of GDF-15.

The application discloses a kind of intelligent scheduling and distribution method of protein complex detection task in cloud platform, it is related to big data management technical field;By constructing task feature model;Real-time sequencing is carried out to task using dynamic priority evaluation function containing vulnerability index, and dynamic scheduling sequence is generated;Using improved space-time graph convolutional neural network to construct resource matching prediction model, and generating resource-task matching matrix;Using improved adaptive genetic algorithm, with minimizing completion time and maximizing equipment utilization as target, under the constraint of resource-task matching matrix, the optimal allocation strategy and execution instruction set are generated;Through abnormal hierarchical judgment and dynamic adjustment resource allocation, and generate exception traceability feedback report;Realize biological characteristic perception and physical resource state prediction deep coupling, improve the survival rate of easy-degradable sample and the utilization efficiency of experimental equipment, guarantee the intelligentization and high robustness of cloud platform detection whole process.

The application discloses a kind of legal document quality confrontation test method based on logic game, it is related to legal artificial intelligence technical field, including, collection legal document full-text data, and extract fact triple, evidence citation fragment, law article number and conclusion claim, generate structured argumentation set;Based on the confidence attenuation sequence of multiple rounds of game, in combination with the vulnerability propagation coefficient corresponding to different types of edges in directed heterogenous graph, carry out path vulnerability contribution value calculation, and generate legal document global vulnerability index by stratified accumulation;Based on logic breakpoint list, contradiction conflict list and legal document global vulnerability index, comprehensive evaluation legal document's logic integrity, argumentation consistency and conclusion robustness, generate structured check report.The application provides a complete and feasible implementation path for the automatic check of legal documents combined with natural language processing.

The application relates to the technical field of information asset management and control, and discloses an information asset management system and an evaluation method for the protection strength of the information asset management system. An asset identification module of the method acquires original attribute data of information assets, generates an asset identification code according to asset types and storage locations; a classification mapping module extracts key attributes of the assets, and establishes an association between the asset identification code and the key attributes; a risk evaluation module calculates an asset vulnerability index based on the key attributes, and generates a risk level in combination with external threat data; a dynamic adjustment module updates the key attributes according to the change of the risk level, and recalculates the vulnerability index; and an access control module generates an access permission strategy according to the updated vulnerability index, and limits asset access behavior. The system realizes fine and dynamic management of information assets, balances asset security and management efficiency, and meets the needs of an organization for information asset management.

The invention discloses a high-risk attack identification and dynamic defense method for an electric power information physical system, and relates to the field of safety of the electric power information physical system. The method comprises the following steps: firstly, constructing a weight coloring Petri network seven-tuple model, and describing the cross-domain propagation time sequence characteristics of the continuous load redistribution attack in an information-physical network by introducing a time delay parameter; then optimizing the attack triggering and migration probability based on mixed strategy Nash equilibrium; a top-k sequence mining algorithm is adopted to identify a high-risk attack mode from the attack event sequence, and a vulnerability index is defined to quantify the threat degree of the attack; and finally, modeling defense resource allocation as a combined dobby machine problem, and realizing self-adaptive adjustment of a defense strategy through a weight updating mechanism and sliding window optimization. According to the method, an active defense system of'accurate perception-intelligent decision-closed loop optimization 'can be formed, so that the defense capability of an electric power information physical system facing continuous load redistribution attacks is improved.

The application provides a hallucination dataset generation method and device based on semantic confusion induction, which comprises the following steps: obtaining a plurality of hallucination induction instructions to be evaluated based on the keywords in the pre-constructed fact space conflict word set; calculating the semantic vulnerability index corresponding to each instruction based on semantic contradiction and context ambiguity, and performing instruction screening according to the semantic vulnerability index corresponding to each instruction to determine high-confidence hallucination induction instructions; inputting the high-confidence instructions into a large language model to make the model output text, and calculating the hallucination confidence level of the evaluation text by combining the hallucination probability index calculation method; storing the text with a hallucination confidence level exceeding a level threshold and the corresponding high-confidence hallucination induction instructions as a hallucination dataset. The application is a hallucination dataset generation method of systematic induction and quantitative detection, which is used to reveal the potential vulnerability of the model and support the safe application of artificial intelligence systems in complex contexts.

This invention relates to the fields of supply chain collaborative management, risk warning, and AI scheduling technology, specifically a supply chain collaborative management and early warning system for PC board inkjet processing. It includes an external supply chain status perception unit for aggregating external status information and generating an external status vector; an internal logistics bottleneck monitoring unit for monitoring the inbound quality control (IQC) channel and generating IQC congestion alarm signals and internal material delay times; a collaborative vulnerability quantification unit for quantifying the collaborative vulnerability index and generating collaborative vulnerability status signals; a bimodal adaptive decision-making unit for generating scheduling strategy instructions; and a resilience strategy execution unit for executing material redundancy actions and resource redundancy actions to reduce the collaborative vulnerability index. This invention solves physical bottlenecks and proactively restores human-machine trust, ensuring the system automatically stabilizes after a crisis is resolved.

The application discloses a climate risk zoning method based on a complex network, comprising the following steps: acquiring original space-time data of climate disaster-causing factors, exposure and vulnerability indexes of disaster-affected bodies in a region to be researched; performing homogenization preprocessing to generate a standardized grid data set; taking a grid unit as a node to construct a heterogeneous weighted complex network; based on the time sequence change of the edge weight between nodes, performing an adaptive threshold-freezing mechanism to update the heterogeneous weighted complex network; running a cross-scale hierarchical community discovery algorithm to obtain an initial climate risk zoning; inputting the initial climate risk zoning into a space-time convolutional graph neural network to perform transfer learning and fine-tuning by using zoning-loss coupling loss function, and outputting a final climate risk zoning result. The application systematically solves the core problems of high precision, high timeliness and low cost, and solves the problem that traditional climate risk zoning cannot consider both climate risk intensity and climate historical change process.

The application discloses a medical patient transfer emergency integrated intelligent nursing system and relates to the technical field of intelligent medical equipment, which comprises a multi-source data acquisition module, a space topology analysis module, a physiological vulnerability mapping module, a vulnerability index generation module and a space perception execution module; the multi-source data acquisition module is used for acquiring real-time physiological parameters and past medical history information of a patient to form a patient physiological state data set; by constructing an intelligent transfer system integrating the patient physiological state, the medical history information and the hospital space environment, a paradigm shift from passive carrying to active protection is realized, the system can identify the physiological vulnerability of the patient in the key dimensions such as cardiovascular system or spine, dynamically generate a physiological-space vulnerability index in combination with the space geometric characteristics of the transfer path, and drive the intelligent transfer bed to automatically adjust the advancing speed and the posture stability in the high-risk area, so that the most vulnerable physiological system is preferentially protected in the whole transfer process.

The invention provides a regional soil heavy metal water input type pollution risk assessment method and system, and relates to the technical field of soil pollution risk assessment. Aiming at the problem of insufficient accuracy of existing pollution risk assessment, the method comprises the following steps: acquiring a sub-basin boundary, a cadmium-containing wastewater discharge point, cultivated land distribution data, a grain yield, cultivated land irrigation water consumption and a flood-submerged cultivated land area; calculating a cadmium emission hazard index, an irrigation exposure index, a flood exposure index and a vulnerability index according to the acquired data; after standardization processing is conducted on the key indexes, cadmium pollution risk values of the irrigation approaches and the flood approaches of all the sub-basins are calculated; dividing an irrigation exposure type and a flood exposure type according to a set threshold value, and determining a comprehensive risk type by combining the dual-path risk value; a sensitive analysis model is adopted, the key index is used as an input quantity, the double-path risk value is used as an output quantity, and a sampling and statistical method is set to identify a sensitive factor with the maximum influence of the risk value. According to the method, comprehensive and accurate evaluation of the watershed scale pollution risk is realized.

The invention belongs to the technical field of geological disaster risk assessment and urban safety disaster prevention, and particularly discloses an urban karst surface collapse risk assessment method and a storage medium, and the method comprises the steps: screening out dominant factors from a plurality of susceptibility evaluation indexes through a geographic detector, and carrying out the quantification of each dominant factor; quantizing the plurality of induction factors, and inputting the quantized dominant factors and induction factors into a support vector machine model to obtain a risk evaluation result; quantifying the plurality of vulnerability evaluation indexes, performing combined weighting by using an analytic hierarchy process and an entropy evaluation method to determine the weight of each vulnerability evaluation index, and calculating the vulnerability index of the research area based on the weights; and based on the risk evaluation result and the vulnerability evaluation result, superposition is carried out through the same risk level discrimination matrix to form a risk evaluation result, and the research area is divided into a plurality of risk levels. Evaluation indexes can be scientifically screened, human activity induction factors are fused, and high precision and strong interpretation are achieved.

The present application relates to the technical field of mine water treatment, and particularly relates to a mine water treatment agent proportioning intelligent recommendation method based on multi-objective optimization, comprising: collecting mine water treatment multi-dimensional dynamic data and preprocessing to obtain standardized engineering benchmark data sequences; constructing a heavy metal and suspended matter competitive adsorption index and a flocculation body hydraulic shear vulnerability index according to the standardized engineering benchmark data sequences; fusing the standardized engineering benchmark data sequences with the heavy metal and suspended matter competitive adsorption index and the flocculation body hydraulic shear vulnerability index, and predicting future water outflow turbidity by using a classification enhanced gradient boosting tree prediction algorithm; constructing a fitness objective function according to the future water outflow turbidity combined with engineering penalty constraints, and optimizing by using a multi-objective particle swarm optimization algorithm. Through the technical scheme of the present application, the solidity of the flocculation body microstructure can be ensured under harsh working conditions, and invalid consumption of the agent can be avoided.

The invention discloses a rural comprehensive energy system optimal configuration method based on multi-energy complementation. The method comprises the following steps: S1, collecting multi-dimensional rural energy data; s2, mathematical modeling of the energy equipment; s3, performing matching analysis on the rural multi-energy demand and the equipment; s4, constructing a multi-objective optimization constraint system; s5, constructing and solving an optimal configuration model of the integrated energy system; according to the method, layered modeling is carried out on the performance parameters of the energy conversion type equipment and the cold and heat supply type equipment, so that the suitability and accuracy of rural comprehensive energy system equipment modeling are effectively improved; a multi-agent system is adopted to carry out matching analysis of rural multi-energy demands and equipment, and it is ensured that multi-energy complementary potential evaluation can accurately adapt to multi-element demands of different rural scenes; an optimal configuration model is solved by constructing a target function fused with a rural power grid vulnerability index, so that an optimal configuration result can realize collaborative optimization and can adapt to the characteristics of a rural power grid.

The invention provides a power distribution network weak link identification method and system considering photovoltaic output uncertainty, and relates to the technical field of power distribution network safety. Comprising the following steps: establishing a node comprehensive vulnerability index and a line comprehensive vulnerability index; setting node degrees, node betweenness and node voltage out-of-limit risk indexes in the node comprehensive vulnerability indexes; setting line degree, line betweenness and line current-carrying capacity out-of-limit risk indexes in the line comprehensive vulnerability indexes; and setting a target layer and a factor layer based on the node comprehensive vulnerability index and the line comprehensive vulnerability index, calculating each factor weight of each layer by using an analytic hierarchy process, obtaining a comprehensive vulnerability evaluation result of the node and the line through index weighting, and determining the weak node and the line of the power distribution network. According to the method, the weakness evaluation index of the element state of the power distribution network is improved, the characteristic of high-proportion access of the topological characteristics of the power distribution network and renewable energy sources is incorporated, and the weak links of the nodes and lines of the power distribution network are quantified more comprehensively and accurately.

The invention relates to the technical field of water vulnerability coupling analysis, in particular to an industrial, domestic and agricultural water vulnerability coupling analysis method based on drought response. Comprising the following steps: constructing a social economic water shortage ratio index to distinguish general drought and extreme drought scenes; quantifying the industrial, domestic and agricultural water vulnerability by respectively adopting an HARA function, a drinking difficulty population proportion, an area method and a yield method; vulnerability response differences under different drought scenes are analyzed, a comprehensive vulnerability index is calculated by combining a regional long-term water consumption structure, a coupling degree and coordination degree model of water consumption vulnerability of multiple departments is constructed, and comprehensive judgment of the regional water resource system state is achieved. According to the method, the problems of unclear distinguishing of drought scenes, inaccurate description of water vulnerability of multiple departments and insufficient system coupling analysis are solved, and refined evaluation and comprehensive identification of the vulnerability of the regional water resource system under the drought condition are realized.

The application relates to a tropical cyclone disaster loss assessment method and system, and relates to the technical field of natural disaster risk assessment. The method is executed by a computer device and comprises the following steps: acquiring historical cyclone paths, wind field parameters and social and economic statistical data; performing uniform spatial resolution and coordinate reference alignment processing on population and economic spatial distribution data; calculating a hazard intensity index P; determining a cyclone influence range, extracting population exposure PE and economic exposure G; selecting a population and economic vulnerability index set, constructing a population vulnerability index PV and an economic vulnerability index EV; adopting Poisson regression to construct a death assessment model with P, PE and PV as independent variables; and adopting gamma regression to construct an economic loss assessment model with P, G and EV as independent variables. The application realizes double-dimensional and comparable collaborative attribution analysis of historical tropical cyclone event economic loss and population death, and outputs the relative contribution degrees of hazard, exposure and vulnerability to the two types of losses.

The invention discloses a system vulnerability assessment method and device and a readable storage medium, and the method comprises the steps: collecting the resource indexes of nodes in a system, and constructing a node communication topological graph based on the communication behaviors of all nodes in a cluster; the resource indexes comprise the CPU utilization rate, the memory occupancy rate, the network throughput and the disk I / O of the node; calling chain data are collected, a directed dependency graph between services is constructed based on the calling chain data, and the calling chain data comprise calling source service ID, called service ID, calling frequency in cycle time, average calling time delay, calling error rate and timestamp; calculating a vulnerability score of the node based on the resource index of the node, and calculating a vulnerability score of the micro-service based on the call chain data; and calculating an overall vulnerability index of the system based on the vulnerability score of the node, the vulnerability score of the micro-service and a preset weight value. According to the method, comprehensive assessment of the system vulnerability can be effectively carried out.