136 results about "Risk matrix" patented technology

The invention discloses an intelligent induction and early warning system for poisonous gas in a limited space, and relates to the technical field of gas induction and early warning. A three-dimensional structure model of the limited space is constructed, and non-uniform grid division is carried out based on barrier characteristics; multiple types of toxic gas sensing units are arranged in the grids, and gas concentration data are collected in real time; constructing a toxic gas three-dimensional cloud picture, and generating a dynamic weight field based on the concentration gradient; fusing operator positioning and trajectory prediction information, and establishing an individual risk exposure model; calculating a space-time intersection of the toxic gas cloud picture and the high-risk track area to form a fusion risk matrix; realizing linkage early warning control of a region level and an individual level through multi-level dynamic threshold judgment and thermal block clustering identification; the system can realize accurate perception and active response of the toxic gas gathering trend and personnel exposure risk in the complex limited space, has the technical advantages of high sensitivity, high intelligence and low false alarm, and is suitable for various limited space scenes such as chemical engineering, tunnels and mines.

The invention relates to the technical field of chemical enterprise production management, in particular to a chemical enterprise safety production informatization management system which comprises a sensing network layer architecture, a digital twin management platform, a risk management and control and decision center, a process closed-loop management center and an emergency cooperative processing platform. According to the chemical enterprise safety production informatization management system and method, through construction of a chemical knowledge graph, on the basis of a dynamic risk matrix and an AI prediction model library, equipment remaining service life prediction, process tiny anomaly capture and accident consequence simulation processing are realized; meanwhile, a root cause analysis module is used for associating low-level alarm and traversing a knowledge graph to automatically infer a fault root, physical equipment and a virtual model are bound through an entity-model mapping engine, the model state is dynamically updated in combination with a real-time rendering technology, and technological parameter optimization, accident deduction and scheme verification can be completed in an analogue simulation engine; and the management intuition and the decision-making scientificity are effectively improved.

The invention relates to the technical field of data security, in particular to a quantum cryptography migration resisting method and system for a power system, and the method comprises the steps: carrying out the quantum threat risk assessment of a communication link based on the layering and partitioning architecture features of the power system; obtaining attribute data of the encryption component, and performing parallel migration risk analysis on the encryption component in combination with a quantum threat risk assessment result to generate an anti-quantum migration risk matrix; carrying out compatibility evaluation on a traditional public key algorithm and an anti-quantum cryptography algorithm based on algorithm features, and constructing a double-track encryption migration strategy; dynamically adjusting a double-track weight ratio, and constructing a double-track encryption hierarchical migration strategy based on a control hierarchy to which a communication link belongs; and executing the double-track encryption layered migration strategy and monitoring the migration effect, and performing self-adaptive correction on the double-track encryption layered migration strategy based on the migration effect. According to the method, a quantum threat assessment and double-track encryption layered migration mechanism is constructed, so that safe and smooth migration of the power system under the threat of quantum computing is realized.

The invention relates to the technical field of new energy power system instability risk assessment, in particular to a new energy power system frequency instability risk assessment method based on a heterogeneous graph attention network. The method comprises the following steps: constructing a wind power-photovoltaic heterogeneous graph model according to a power grid topology; performing combined sampling on different operation modes and anticipated disturbances, and determining corresponding input feature vectors; calculating a frequency stability index value label of the sample set; expanding the training set through an active learning iteration process, and carrying out model training; and inputting the collected operation data into the trained heterogeneous graph attention model, outputting a frequency stability index value, and evaluating the system frequency instability risk in combination with the risk matrix. By adopting the frequency instability risk assessment method for the new energy power system based on the heterogeneous graph attention network, the problem of low efficiency of risk assessment in a high-dimensional uncertain scene is solved, and the heterogeneous graph attention network can reflect the influence of different types of devices at different positions and disturbance types on the dynamic frequency of the system; and the accuracy of frequency instability risk assessment is improved.

The invention provides a disaster evolution path deduction method and system based on a multi-modal space-time atlas, and the method comprises the steps: obtaining the attribute data of a shopping mall, and constructing a deduction static atlas based on the attribute data of the shopping mall; the deduction static map initializes a state based on a set instruction, updates based on physical simulation, and outputs a deduction dynamic map; generating a comprehensive risk matrix based on the deduction static atlas and the deduction dynamic atlas, and clustering the comprehensive risk matrix to obtain a classification region cluster; performing physical prediction and digital prediction according to the classification region cluster and the deduction dynamic map, respectively obtaining physical determination and judgment data and digital determination and judgment data, and obtaining spreading probability data through the physical determination and judgment data and the digital determination and judgment data; according to the method, re-deduction is carried out through an intervention instruction, a deduction method capable of carrying out step-by-step deduction and backtracking deduction is provided, a deduction dynamic map is fused, and the deduction accuracy is improved in a physical and digital cooperation mode, so that making of a better emergency plan is assisted.

The invention discloses a mountain tourism route planning method based on weather and natural disasters, and the method comprises the steps: 1, building a Markov game model based on POMDP, combining Mama multi-modal feature compression and RAG semantic enhancement, designing a dynamic risk matrix integrating geological disaster probability, weather trend and ecological sensitivity, and providing partial observable environment state perception; 2, establishing a Nash equilibrium constraint optimization model, sharing an extreme weather strategy through federal learning, introducing an NSGA-II-Actor-Critic architecture to optimize unmanned aerial vehicle inspection and path adjustment, and triggering dynamic communication when rainfall exceeds a threshold value; 3, fusing a security and experience income design reward function, processing continuous action planning by using improved DDPG, and accelerating multi-target Pareto frontier convergence in combination with NSGA-II; 4, constructing a user weather sensitivity portrait, and dynamically adjusting weight balance income and AR simulation preview preference; and 5, based on a GIS closed-loop decision engine, performing agent and environment feature complementation, recording an emergency log by a block chain, and constructing a disaster case library by meta-learning.

The invention relates to the technical field of artificial intelligence, and provides an intelligent insurance matching method and system combining a user portrait and a clause knowledge base. The method comprises the following steps: constructing a first portrait of a user based on a user data set and optimizing to generate a second portrait; extracting features from the insurance clause knowledge base in a multi-dimensional manner to construct a product portrait; performing demand coverage risk evaluation on the product portrait based on the second portrait of the user to generate a demand coverage risk matrix; performing guarantee conflict risk evaluation to generate a guarantee conflict risk matrix; introducing an underwriting risk analysis channel, and generating an underwriting risk matrix in combination with the second portrait of the user; and fusing the three types of risk matrixes to perform multi-level optimization matching, and generating an insurance optimization matching graph, so as to solve the technical problem of significant deviation between the recommendation result and the actual risk preference and guarantee demand of the user, realize dynamic and accurate matching of the insurance product and the user demand, reduce the guarantee conflict risk, improve the correlation of the recommendation result, and improve the user experience. And the technical effect of personalized insurance configuration requirements is met.

The invention provides a drought and flood sudden change prediction method fusing a soil moisture content and rainfall coupling model, and relates to the technical field of drought and flood sudden change. Comprising the steps that layered soil moisture content, high-frequency rainfall and auxiliary data are collected and preprocessed, and a soil moisture content-rainfall coupling coordination initial value is constructed and corrected; traversing drought and flood windows by using the standardized soil moisture content-rainfall coupling coordination index sequence, and determining an optimal window; carrying out nonlinear correction, judging a sudden turning event according to a corrected threshold value, and outputting a drought and flood sudden turning prediction result; and calculating a drought and flood sudden change duration prediction value Tint and a soil moisture content rainfall mutation index SPIef according to a drought and flood sudden change prediction result, a soil texture coefficient and the like, constructing a risk matrix, outputting an early warning level and a response suggestion in combination with the vulnerability of the disaster-bearing body, and outputting early warning information. According to the method, the optimal window is determined and optimized, drought and flood sudden turning is predicted, the scientificity and accuracy of prediction are guaranteed, and the practical application value is enhanced.

The invention provides a mixing pile online monitoring method and device and electronic equipment, and relates to the technical field of mixing pile monitoring, and the mixing pile online monitoring method comprises the steps that drill rod inclination angle data, slurry flow data, cement consumption quality data and drill rod displacement data are acquired; coordinate transformation is conducted on the drill rod dip angle data and the drill rod displacement data, and the actual pile depth of the drill rod is calculated; performing double-source verification on the slurry flow data and the cement consumption quality data to generate effective cement consumption; constructing a pile body quality risk matrix model based on a preset pile depth threshold value, a cement consumption safety standard and a drill rod speed specification; inputting the actual pile depth of the drill rod, the effective cement dosage and the real-time drilling speed into the risk matrix model, and outputting a risk grade index; and when the risk grade index exceeds a preset threshold value, a regulation and control signal containing a drilling speed correction instruction, a grouting amount compensation instruction or an equipment locking instruction is generated. Accurate control over the pile depth is achieved, the cement consumption deviation is obviously lower than the industrial standard, and the risk of jerry work and material reduction is reduced.

The invention relates to the field of emergency response, in particular to an emergency lighting evacuation path dynamic planning method and device based on multi-source event triggering, and the method comprises the steps: obtaining multi-source event data in real time; according to the multi-source event data, an information fusion algorithm is adopted for analysis and fusion, and a comprehensive event level comprehensively representing disaster situation development and personnel conditions in the building is generated; dynamically distributing risk weight values for each path node in the building by combining the comprehensive event level and pre-stored building structure topological information, and generating a dynamic risk matrix changing along with time; according to the dynamic risk matrix, performing real-time calculation on personnel at different positions in the building to generate personalized dynamic evacuation paths; and converting the calculated dynamic evacuation path into a control instruction, driving the intelligent emergency lighting lamp to change the indication direction, and guiding the personnel to evacuate along the planned path in a dynamic light and shadow mode. The dynamic risk matrix generates personalized optimal paths for persons at different positions, and accurate evacuation is performed from the perspective of global optimization.

The invention discloses a power network security defense method and device based on digital twinning, and belongs to the technical field of network security, and the method comprises the steps: obtaining the power data of a power network in real time; constructing a digital twinborn simulation environment of the power network according to the power data; extracting electric power characteristic data in a digital twinborn simulation environment; performing layer-by-layer risk analysis on the power feature data according to each layer of hyperplane function of a preset decision tree, and determining a risk type and a risk matrix of the power network; in a digital twin simulation environment, reconstructing a propagation path of the current attack according to the risk matrix; and generating a security defense strategy of the power network according to the risk type and the propagation path. Therefore, by implementing the method and the device, the problem of low accuracy of power network risk detection in the prior art can be solved.

The invention discloses a contract auditing method and device based on an operation and maintenance large model, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the steps: integrating a historical purchase contract, a target law regulation, a preset industry standard and preset related data to generate historical contract auditing data, performing data marking on the historical contract auditing data to generate historical label data; inputting the historical contract auditing data and the historical label data into the initial operation and maintenance large model for training to obtain a to-be-tested operation and maintenance large model, and dividing the historical contract auditing data into a verification set and a test set according to a preset division mode, performing performance test operation on the to-be-tested operation and maintenance large model according to the verification set and the test set to obtain a target operation and maintenance large model; and obtaining a to-be-audited purchase contract, extracting target key information by using the target operation and maintenance large model, identifying a target risk point based on the target key information, and quantitatively evaluating the target risk point according to a preset risk matrix to generate a purchase contract audit report. And the pre-auditing efficiency of the purchase contract is improved.

The invention belongs to the technical field of medical information, and relates to a drug interaction screening method based on drug use records. The core structure comprises: a data integration module, which obtains a multi-source medication record of a patient in real time through an HL7 / FHIR interface and carries out structured processing; the metabolism engine calculation module is used for identifying a metabolism action mode based on the drug-metabolic enzyme influence relation database and quantifying a net effect value by adopting a dynamic time weighting algorithm; the risk decision module is used for integrating liver and kidney functions and gene polymorphism data and generating a three-dimensional risk matrix through a multi-factor prediction model; and the clinical output module is used for executing risk visualization early warning, alternative medicine recommendation and individualized monitoring scheme generation. Dynamic medication time sequence analysis, individualized risk quantification and clinical decision closed-loop management are realized, and medication safety is improved.

This invention discloses a method, equipment, medium, and product for quantitatively assessing the risk of erosion damage to pressure equipment, relating to the safety of pressure equipment in the petrochemical and chemical industries. The method includes: determining the damage form of the equipment; calculating a local / uniform thinning factor based on the damage form; calculating an equipment correction coefficient based on the local / uniform thinning factor, a general condition factor, a mechanical factor, and a process factor; calculating the probability of erosion corrosion failure based on the equipment correction coefficient, a management system evaluation coefficient, the average failure probability of similar equipment, and an impact coefficient for defects exceeding standards; calculating the leakage consequence area; determining the consequences of erosion corrosion failure based on the leakage consequence area; and establishing a two-dimensional risk matrix based on the probability of erosion corrosion failure and the consequences of erosion corrosion failure. The two-dimensional risk matrix is ​​used for real-time quantitative assessment of erosion risk. This invention can effectively guide the prevention and control of erosion corrosion risks in the petrochemical and chemical industries.

The invention relates to a road maintenance scheme generation method fusing a risk priority number and a risk matrix, and the method comprises the steps: S1, generating an initial feature code, initializing an optimal solution to be null, and enabling a target function value of the optimal solution to be infinite; s2, on the basis of the current feature codes, the probability of occurrence of risk events in each year of each road section unit is determined; s3, calculating the risk priority number of each year of each road section unit; s4, based on the obtained risk priority number, a target function value is obtained through calculation in combination with road maintenance basic parameters; s5, judging whether the current target function value is smaller than the target function value of the optimal solution or not, and if yes, updating the current feature code into the optimal solution; s6, judging whether an exit condition is met or not, if yes, mapping the current optimal solution into a road maintenance scheme to be output, and if not, executing the step S7; and S7, modifying the feature codes, and returning to the step S2. Compared with the prior art, the method has the advantages of high accuracy and the like.

The application discloses a railway foreign matter intrusion recognition decision method and device, equipment and medium, relates to the image recognition technical field, and includes: through collecting and preprocessing the inspection image, obtaining the foreign matter category and position information through the lightweight detection model, relying on the two types of information to quantify the risk level, fusing multiple information to construct a query vector, and calling regulations from the railway knowledge graph with the help of a search enhancement generation framework, and generating standard disposal suggestions combined with the search content. Through the coupling of the risk matrix and the knowledge graph, a closed loop from perception to decision is realized, and the accuracy and compliance of foreign matter disposal are improved.

The invention belongs to the technical field of gas pipeline leakage risk evaluation, and discloses a polyethylene gas pipeline leakage risk evaluation method and system.The method comprises the steps that leakage failure factors are graded based on a pipeline failure accident tree, and the failure grade of a sample pipeline is judged based on the maximum membership degree principle; establishing a potential influence radius calculation model suitable for the nonmetal polyethylene pipeline, and determining a heat radiation influence radius model; obtaining a leakage rate curve, and dividing a thermal radiation influence area; determining a consequence severity level according to the loss number; and in combination with the failure level and the consequence severity level, performing leakage risk assessment on the polyethylene gas pipeline based on the risk matrix. According to the method, the pipeline failure grade is calculated based on the cloud model parameters, the membership value and the weight value, the leakage rate attenuation factor suitable for the nonmetal polyethylene pipeline is obtained based on computational fluid mechanics simulation, artificial subjective interference such as expert scoring is not needed, and the risk assessment accuracy and objectivity are greatly improved.

The application discloses an anti-misoperation intelligent control method and system based on integrated control, relates to the technical field of power automation, and comprises the following steps: acquiring first data of a three-party integrated control system, constructing a dynamic instruction pool and an operation time sequence diagram; based on the dynamic instruction pool and the operation time sequence diagram, checking operation consistency through a space-time coupling protocol, combining compliance verification rules and power grid operation data, and constructing a power flow constraint network; according to the power flow constraint network, using a mixed integer programming method and an N-1 risk matrix, generating a risk early warning; according to the risk early warning, generating an anti-misoperation decision, and feeding back to the three-party integrated control system. The application is used to solve the problems that operation instruction management and control of a traditional anti-misoperation system lacks dynamicity and consistency checking is weak.

The invention discloses a pumped storage power station high-fall cable tunnel fire risk assessment method and system, relates to the technical field of fire science and safety, and aims to solve the problem that an existing cable tunnel fire risk assessment method is not suitable for a high-fall scene and lacks consequence quantification capability. Comprising the following steps: identifying a hazard source through multi-mode investigation and in combination with a high-fall cable tunnel structure and the like; a fire accident tree is constructed based on the method, and the occurrence possibility of a top event and the importance of various factors are determined through qualitative and quantitative analysis; a fire consequence severity grade standard is formulated, fire parameters are obtained through CFD simulation, and the fire consequence severity is determined from the two angles of transverse spreading and longitudinal spreading; adopting a risk matrix method to complete risk quantitative evaluation; and according to the accident tree index and the evaluation result, proposing prevention and control suggestions from multiple aspects. According to the invention, accurate quantitative evaluation of the cable tunnel fire risk in the high-fall scene is realized, and a scientific basis is provided for risk prevention and control.

The invention discloses a natural gas pipeline failure risk assessment method and system based on data driving, and relates to the technical field of pipeline safety. The method comprises the following steps: firstly, calculating and correcting the failure probability by establishing a pipeline failure probability evaluation model, extracting key features by constructing a corrosion and design five types of failure factor index systems and principal component analysis, and calculating the failure probability by utilizing an improved correction coefficient formula; secondly, establishing a consequence evaluation model based on a risk matrix, and realizing differentiated evaluation of failure consequences in different geographical environments by combining GIS data; setting an online learning mechanism, and automatically updating a risk matrix when sensor data triggers a threshold value; the problems that a traditional method is high in subjectivity, insufficient in data fusion and low in simulation precision under complex conditions are solved, the accuracy and dynamic adaptability of risk assessment are improved through machine learning and space-time correlation analysis, accurate decision support is provided for pipeline operation and maintenance, and the safety accident rate is effectively reduced.

The invention relates to a method and computer program product for providing a neural network and system for classifying objects for a vehicle. The method according to the invention comprises the steps of providing a hazard and risk matrix for objects to be classified (S10), determining and assigning a safety weight to a misclassification depending on a risk rating (S20), determining and assigning a training weight to a misclassification (S30), and training a neural network by means of a plurality of iterations (S30). In this process, assigned training weights are dynamically adjusted to optimize a safety index, and the safety index is determined depending on misclassifications and assigned safety weights.

The invention discloses a landslide hidden danger risk assessment method and system based on a three-dimensional dynamic matrix, and relates to the technical field of landslide hidden danger risk assessment, and the method comprises the steps: when a preset region is in a non-flood season, obtaining a three-dimensional dynamic matrix of a weight coefficient corresponding to each landslide hidden danger factor and a quantized value of each landslide hidden danger factor; calculating to obtain a hidden danger risk matrix calculation value of the preset area, and taking the calculated hidden danger risk matrix calculation value as a final hidden danger risk matrix calculation value; and according to the final hidden danger risk matrix calculation value, carrying out landslide hidden danger risk assessment on the preset area to obtain a landslide hidden danger risk assessment result of the preset area. According to the method, objective and dynamic risk assessment is realized by means of quantitative analysis of the three-dimensional dynamic matrix in combination with deformation characteristics of the landslide hidden danger in different stages, and scientificity and reliability of an assessment result are remarkably enhanced.

The invention discloses a cold region tunnel disaster multi-field coupling deduction and lining response prediction method and device, and the method comprises the steps: collecting temperature, stress and seepage pressure monitoring data containing time sequence and space dimensions; finishing data intelligent repair and anomaly recognition by adopting an algorithm of combining a deep learning model-Kriging interpolation based on time sequence analysis with an isolated forest-mahalanobis distance to obtain preprocessed data; constructing a multi-field coupling deduction model based on a finite element-lattice Boltzmann method; using a support vector machine and fuzzy logic to diagnose disaster types and severity, and determining disaster risk levels based on Monte Carlo simulation and a risk matrix; and finally, predicting the evolution trend of the lining structure of the medium-high risk part under different time scales by adopting a physical information neural network and taking the risk level as a constraint. According to the method, the accuracy and multi-scale of multi-field coupling deduction and lining response prediction of the tunnel in the cold region are realized, and reliable technical support is provided for tunnel construction monitoring, operation and maintenance scheduling and disaster prevention and control.

A method for monitoring pathogen load in livestock. The method uses a risk matrix to evaluate the risk of a pathogen load in livestock to cause a disease. A computer program product comprising code portions adapted for performing the method and a system for monitoring pathogen load in livestock are also described.

The invention provides an urban rainstorm waterlogging risk assessment method, device and equipment and a storage medium, and belongs to the field of risk assessment, and the method comprises the steps: obtaining multi-source data of different regions of a target city; based on an analytic hierarchy process, screening evaluation indexes from two criterion layers of disaster-inducing factors and disaster-bearing body vulnerability to construct a structured evaluation index system, and allocating weights to the indexes in the evaluation index system; carrying out weighted calculation on the multi-source data of each region by utilizing the structured evaluation index system and the weight thereof, and respectively obtaining comprehensive evaluation values of each region on the occurrence probability dimension and the influence degree dimension of the rainstorm waterlogging risk; and inputting the comprehensive evaluation value of each region into a predefined risk matrix model, and calculating to obtain a quantitative risk level result of each basic evaluation unit through matrix mapping.

The invention provides a fireproof design method and device which are suitable for plant phenotypic facility or indoor facility agriculture, and the method comprises the steps: determining the safety distance of each functional region based on critical radiation heat simulation; according to the safety distance, the fire scale of each functional area under the most unfavorable working condition is obtained by combining the characteristics of combustible materials in each functional area or through analogue simulation; calculating a fire probability prediction value of each functional area under different second-class hazard sources and a fire loss prediction value under different fire scales, and evaluating a fire risk evaluation level of each functional area through the risk matrix; and in combination with the fire scale, the fire risk evaluation grade and the safety distance, matching fire prevention control measures corresponding to each functional area. The method can effectively improve the fireproof control of plant phenotypic facility or indoor facility agriculture, and achieves the real-time monitoring and prediction functions of fire risks.

The present application belongs to the technical field of cooperative control, and particularly relates to a contactless transmission path cooperative control system, which comprises a monitoring module, a risk coupling module, a cooperative control module and a feedback module; the monitoring module collects control parameters, evaluation indexes and process parameters and quality data of a processing process of a contactless transmission process in real time; the risk coupling module constructs a transmission and processing risk matrix by using the data, and generates a risk coupling matrix and a production coupling chain based on an algorithm such as a hidden Markov algorithm; the cooperative control module generates transmission and processing control instructions according to the coupling risk information of each node in the chain; and the feedback module realizes real-time adjustment through reverse abnormality evaluation positioning, so that the production process continuously conforms to the standard process chain; the present application realizes risk cooperative control and closed-loop optimization of the transmission and processing processes, and significantly improves the production yield and the intelligent level of the system.

The invention discloses an artificial intelligence reinforcement learning service platform, particularly relates to the field of computer data processing, and is used for solving the problem that training sample semantics drifts and cannot be rechecked due to data center telemetering backfilling disorder and caliber version change superposition. The method comprises the following steps: generating an original record set by collecting telemetering, establishing double indexes, generating an action bill according to a fixed period, locking a backfill time window, extracting observation to form an aligned observation packet, and labeling missing section entries and late section entries; according to the aperture version identification execution state construction expression and the reward calculation expression, packaging the training sample packet and generating a re-calculation abstract, calculating a backfill link completeness index and an aperture shadow difference risk value, obtaining a release judgment value through a biaxial risk matrix, and writing the training sample packet into a sample library or an isolation area. And generating a strategy release packet, completing admission judgment according to the morphological interval table, triggering the freezing strategy release packet to output a bottom guarantee control instruction, and registering a repair queue.

The invention discloses an AI chip equipment fault prediction system based on a cycle time network, and the system comprises the following modules: an on-chip behavior data acquisition module which is used for collecting on-chip behavior data and constructing an on-chip topology dynamic field; the perturbation response acquisition module is used for applying a perturbation signal to the chip and forming a quantum perturbation response tensor; the cross-scale seepage analysis module is used for executing cross-scale seepage analysis and constructing a cross-scale seepage map; the multi-dimensional feature construction module is used for executing synchronous alignment, feature fusion and dynamic reconstruction and generating a behavior feature sequence; the behavior prediction module is used for obtaining a future behavior prediction sequence based on the improved xLSTM model; and the abnormity judgment and regulation module is used for constructing an abnormity risk matrix based on the prediction sequence and the health baseline, and performing dynamic regulation on the chip. According to the invention, accurate prediction and abnormity identification of the operation state of the AI chip can be realized, and the operation safety and the self-adaptive regulation and control capability of the chip are improved.

The invention discloses a cascade dam group system service risk matrix type evaluation method, which comprises the steps of collecting data information of a drainage basin where a cascade dam group system is located to construct a deep learning model, and performing dam break flood routing calculation; calculating a system failure risk rate of each unit dam, quantifying a risk transfer coefficient between adjacent unit dams, constructing a state transition probability matrix and a state transition loss matrix of the cascade dam group system, calculating a state transition risk matrix of the cascade dam group system, and obtaining a total risk rate of the system and three types of total risks of life, economy and social environment; the corresponding total loss is evaluated; and finally carrying out cascade dam group system risk rating. The method has higher calculation efficiency and precision, and can provide richer and more comprehensive calculation results; according to the system risk quantitative grading standard and method, theoretical preciseness is considered, meanwhile, higher engineering applicability and practical operability are achieved, and higher practical application value is shown.