1806 results about "Index system" patented technology

The invention discloses a computing power scheduling method and system based on dynamic load prediction and resource priority ranking. The computing power scheduling method comprises the following steps: collecting historical load data, task submission data and resource state data of each node in a computing power cluster; on the basis of the preprocessed multi-dimensional load feature data set, constructing an improved hybrid prediction model, optimizing model parameters through training, and predicting the load change trend of each computing power node in a future preset time period by using the trained model to obtain a node load prediction result; extracting a service level protocol parameter, a resource demand type and historical execution efficiency data of a to-be-scheduled task, and establishing a multi-dimensional resource priority evaluation index system; according to the computing power scheduling method, the problems of low resource utilization rate and high task response delay caused by low load prediction precision and mismatching of resource allocation and task priority in a traditional computing power scheduling method are solved, and the overall operation efficiency and service quality of a computing power cluster are improved.

The invention discloses a multi-mode fusion product document and source code association retrieval method based on a knowledge graph, and relates to the technical field of software engineering and artificial intelligence. The method comprises the steps that source codes are preprocessed, and code structure information and business semantics are mapped in combination with a predefined business term dictionary; performing controlled induction on a code file and a product document by utilizing a large model, extracting business terms, logic intentions and a subject relationship, fusing with original codes, and establishing a vector retrieval index system; further analyzing a code structure by using an abstract syntax tree, and extracting an entity and a calling relationship; semantic enhancement and relation normalization are performed in combination with the large model, entities and relations are stored in a graph database, and a knowledge graph is formed; and performing parallel processing on user query based on a full-text retrieval index, a vector retrieval index system and a knowledge graph, and finally generating a product concept. According to the method, the retrieval speed, the semantic depth and the logical reasoning ability can be considered at the same time, and the retrieval accuracy is improved.

The invention discloses a real-time behavior monitoring and dynamic optimization system for an advertisement putting strategy, and relates to the technical field of advertisement putting and user behavior analysis. A real-time multi-source user behavior data acquisition module acquires data; the distributed storage and indexing module supports fragmented storage, capacity expansion and multi-dimensional indexing; the behavior feature extraction and analysis module extracts features and identifies a time sequence rule; the putting effect evaluation module compares data through an index system and positions an effect short board; the user portrait dynamic updating module adjusts the label weight according to the latest data; the strategy optimization decision module optimizes parameters in combination with the portrait and the evaluation result; the execution scheduling module issues an instruction and monitors a state; the historical data mining and model training module is used for mining rules and iteratively training the model; and the visual interaction configuration module provides an interface and supports parameter configuration and data, effect and optimization suggestion display. According to the invention, full-scene real-time monitoring and cross-platform identity association of user behaviors are realized, and support is provided for refined advertisement marketing.

The invention relates to the technical field of environment monitoring, in particular to an intelligent acquisition method based on environment monitoring data fusion, which comprises the following steps: S1, constructing a multi-sensor distributed monitoring network, and acquiring atmosphere, water quality, soil and meteorological environment data; s2, performing data preprocessing, including smoothing, anomaly detection, interpolation and time alignment; s3, carrying out data source, feature and decision three-level fusion, and outputting an environment quality level; s4, constructing a quality index system, monitoring data quality and adaptively optimizing fusion parameters when the data quality is abnormal; s5, performing environment trend prediction and pollution tracing based on a fusion result, and generating early warning information; and S6, constructing a cross-modal causal diagram, reasoning a multi-source causal path, and identifying pollution key factors and source responsibility subjects. According to the invention, through multi-source environment data fusion and cross-modal causal reasoning, high-precision early warning of environment abnormity and intelligent traceability identification of pollution sources are realized.

The invention relates to the technical field of slope settlement monitoring and early warning, in particular to a visual slope settlement monitoring and early warning method and platform. The method comprises the following steps: acquiring slope settlement monitoring data; preprocessing the acquired slope settlement monitoring data; respectively constructing a multi-scale slope digital twinborn model and a hybrid intelligent prediction model; constructing a multi-level early warning index system; constructing a fuzzy neural network early warning model based on a multi-stage early warning index system through a multi-scale slope digital twinborn model and a hybrid intelligent prediction model; and performing visual slope settlement early warning by using the fuzzy neural network early warning model. According to the space-air-ground integrated monitoring network constructed by the invention, a satellite InSAR, an unmanned aerial vehicle LiDAR and distributed optical fiber sensing are fused, and full-scale monitoring from regional macroscopic deformation to slope surface microcracks and deep soil displacement is realized.

The invention discloses an intelligent identification and grading early warning method based on mine production abnormity, and a system and equipment thereof. The method comprises the following steps: obtaining space-time evolution data, earth surface deformation data and environment monitoring data of rock mass stress in a target area; performing abnormal mode detection on the data by using a space-time convolutional network to obtain accident risk probability distribution data; using an ultra wide band positioning system to track the movement track of the person entering the target area in real time to obtain the movement track data of the person; and constructing a three-dimensional early warning index system in combination with the accident risk probability distribution data in the target area and a dynamic early warning mechanism, performing dynamic early warning grading on different positions in the target area by using the three-dimensional early warning index system, and generating a grading response strategy matched with the personnel activity trajectory data. According to the invention, the problems of incapability of tracking a personnel movement track in real time and low timeliness of mine production abnormity early warning are solved.

The invention provides a contaminated site remediation technology scoring system which comprises a multi-dimensional evaluation index system construction module, a situational weight dynamic adjustment module, a remediation technology applicability scoring module, an uncertainty analysis and sensitivity test module, a scoring result visualization module, a technical scheme sorting and screening unit and the like. Through four innovations of a dynamic weight adaptation mechanism, a multi-model fusion scoring algorithm, a technology combination scheme evaluation module and uncertainty robust analysis, the problems of single dimension, weight solidification, difficulty in quantification of a synergistic effect and the like in pollution remediation technology evaluation are systematically solved; and an objective, efficient and transparent intelligent decision-making tool is provided for repairing a complex polluted site.

The invention provides an arch dam shape efficient intelligent optimization method and system based on an agent model. The method comprises the steps that an arch dam physical-numerical model is constructed, a double optimization target with structural safety and economical efficiency as the core is determined, design parameters are selected, a constraint function is set, and an evaluation index system is established; samples are generated through Latin hypercube sampling, a data set is constructed in combination with finite element calculation, and a multi-task learning architecture is adopted to train a high-precision agent model. And then, coupling the proxy model with a multi-objective optimization algorithm, quickly searching a Pareto optimal solution set, and screening out a comprehensive optimal figure by using a multi-attribute decision-making method. And finally, through a finite element simulation verification result, prediction precision and performance improvement are ensured. The method has the advantages of lightweight modeling, efficient prediction and accurate search, and provides an effective tool for intelligent optimization and rapid decision making of hydraulic structures such as arch dams and the like.

The invention discloses an intelligent ship steering capability multi-dimensional evaluation system based on virtual-real fusion, and relates to the technical field of intelligent ships and virtual-real fusion. The system comprises a visual platform and an integration module, wherein a simulation environment is constructed through a virtual-real data interaction engine, and ship behaviors under different sea conditions are simulated; a virtual-real data bidirectional calibration module is used for dynamically correcting simulation parameters, and it is ensured that the simulation parameters are consistent with real ship data; based on the multi-dimensional evaluation index system, the intelligent evaluation decision module comprehensively scores the steering performance; and the behavior guiding module outputs an evaluation report and a risk avoidance suggestion. According to the invention, part of real ship tests can be replaced, extreme working conditions can be simulated, the evaluation precision is guaranteed, the test period is remarkably shortened, the cost is reduced, simulation parameters are dynamically corrected through a bidirectional calibration mechanism, comprehensive and multi-dimensional quantitative evaluation on steering capability in a scene close to a real scene is realized, and a credible evaluation report is output.

The invention discloses an automatic auditing system and method for road engineering completion settlement. The system comprises a data acquisition and integration module; a data preprocessing module; a settlement index construction module; an intelligent auditing engine; an abnormity early warning and tracing module; a settlement result management module; and a data analysis and optimization module. The auditing method comprises the following steps: S1, collecting and integrating multi-source settlement data; s2, big data preprocessing; s3, constructing a settlement auditing index system; s4, performing intelligent automatic auditing; s5, performing abnormal early warning and tracing; s6, managing settlement results; and S7, performing big data driving optimization. According to the invention, multi-source data intelligent integration, full-process automatic auditing, abnormal accurate tracing and dynamically optimized big data driven settlement auditing can be realized; the method is applied to whole-process management of road engineering completion settlement, and data-driven intelligent auditing and continuous optimization control are realized in the process.

The invention discloses a multi-dimensional enterprise qualification evaluation method and system, and the method comprises the steps: obtaining multi-dimensional original data, and obtaining a standardized enterprise multi-dimensional feature data set through employing a data cleaning and normalization preprocessing technology; aiming at a standardized enterprise multi-dimensional feature data set, performing grouping optimization and weight calculation on indexes by utilizing an improved WP-PVC algorithm, and constructing a multi-dimensional evaluation index system; based on the multi-dimensional evaluation index system, a double-standard WP-PVC algorithm is adopted to carry out inter-index correlation analysis and score calculation, and an enterprise qualification comprehensive score result is generated; according to an enterprise qualification comprehensive scoring result, in combination with a multi-logarithm algorithm of random online sorting, calculating a matching degree between the enterprise and various science and technology projects, and outputting a project matching recommendation list and application success rate prediction; and automatically generating an enterprise qualification diagnosis scoring report based on the enterprise qualification comprehensive scoring result and the project matching recommendation list. According to the invention, comprehensive evaluation of enterprise qualification, accurate project matching and scientific application guidance are realized.

The invention relates to the technical field of intelligent supply chain management and multi-modal artificial intelligence crossing, and discloses a multi-modal large model-based supply chain toughness evaluation system, which comprises a data acquisition module, a multi-modal processing module, a toughness evaluation module, a cloud edge collaboration module and a decision support module, the data acquisition module is used for acquiring supply chain texts, images and time sequence heterogeneous data; the multi-modal processing module is used for realizing dynamic feature fusion through term matrix enhanced Transform; the toughness evaluation module quantifies toughness scores based on a three-level index system and a fuzzy matter element calculation engine; the cloud edge collaboration module realizes edge end real-time reasoning through a lightweight model; the decision support module optimizes node reinforcement and path planning based on network topology and real-time weather data. According to the method, the problems of insufficient data isomerism processing, single evaluation dimension and lagging real-time response in the prior art are solved.

The invention discloses a risk assessment method and system based on a Bayesian network and an evidence theory, and relates to the technical field of risk intelligent assessment, and the method comprises the steps: determining an assessment dimension and an assessment index of a high-investment low-income risk of an educational institution in MOOC learning according to a human-cargo-field model and an industry report; constructing a MOOC learning risk assessment index system according to the assessment dimensions and the assessment indexes; constructing a Bayesian network structure according to the MOOC learning risk assessment index system; obtaining questionnaire data and expert opinions according to the MOOC learning risk assessment index system, and determining Bayesian network parameters based on the questionnaire data and the expert opinions; and inputting the Bayesian network parameters into the Bayesian network structure to obtain an assessment result of the high-investment low-income risk, the assessment result including a risk prediction result, a key risk factor and a sensitivity analysis result. According to the method, the high-investment and low-income risk in MOOC learning can be accurately evaluated.

The invention relates to the technical field of mine ecological restoration management, in particular to a surface mine ecological restoration management evaluation system, which comprises a data acquisition module, a database module, a data index system construction module, a restoration strategy generation module, a restoration effect evaluation module, a visual display module, a management decision support module and an evaluation model module. Through dynamic updating of the data index system and timely adjustment of the restoration strategy, the system can adapt to various changes in the ecological restoration process, and smooth restoration work is ensured. Meanwhile, due to real-time evaluation of the repairing effect and scientific formulation of management decisions, the efficiency and effect of repairing work are improved, and waste of resources and blindness of repairing work are avoided. In addition, the dynamic adjustment mechanism can discover and solve problems occurring in the repairing process in time, the repairing risk is reduced, and the success rate and sustainability of repairing work are improved.

The invention relates to the technical field of data storage, and discloses a solid state disk total write-in data volume testing method, which comprises the following steps of: initializing a testing environment and self-adaptive parameter configuration of a solid state disk; creating a plurality of parallel data acquisition threads, acquiring test data through the data acquisition threads, and storing the acquired test data into a database; establishing a preset health degree evaluation model, analyzing the collected test data in real time according to a preset health degree index system, dynamically adjusting a test load based on a dynamic acceleration stress model and according to the real-time state of the solid state disk, executing a corresponding test operation according to an adjustment result, and recording a test result; and analyzing the test result, and automatically generating a test report according to the analysis result. According to the method, the dynamic acceleration stress model is introduced, so that the test load is dynamically adjusted according to the real-time state of the SSD, and the test efficiency and accuracy are improved.

The invention provides a typhoon disaster risk traceability and prediction method based on disaster grade clustering and an interpretable model. Comprising the following steps: constructing an index system containing multi-dimensional typhoon disaster influence variables, carrying out clustering analysis on disaster consequences by utilizing a Gaussian mixture model based on historical typhoon disaster event data, and dividing severity levels of typhoon disasters; a Borderline-SMOTE algorithm is adopted to process the problem of class imbalance, and an XGBoost model is utilized to construct a nonlinear mapping relation between disaster influence variables and disaster grades; an SHAP method is introduced, the contribution degree of each input variable to disaster grade prediction is clarified, key disaster-inducing factors and disaster-inducing paths thereof are disclosed, and the interpretability of a model result is realized. The method also supports typhoon information input before a disaster, realizes disaster grade prediction and risk tracing, proposes targeted disaster prevention and reduction suggestions based on an SHAP analysis result, provides real-time and accurate typhoon disaster early warning and risk intervention basis for coastal cities, and has relatively strong practical guidance significance and popularization and application values.

The invention relates to the technical field of document processing, and discloses a document knowledge retrieval method and system, electronic equipment and a storage medium. Based on a language model, synchronously generating abstract contents and a semantic association query set for each text fragment, and aggregating the abstract contents of all text fragments corresponding to the same document to form a fragment abstract set; constructing a multi-path retrieval pool based on the text fragment, the abstract content and the semantic association query set, and respectively constructing a plurality of independent retrieval data sources; the method comprises the following steps: constructing a dual-granularity abstract index system, receiving a query request of a user, executing query routing processing based on dual-granularity abstract index and a hierarchical retrieval process based on a metadata structure, returning retrieval result data, performing fusion calculation and duplicate removal processing on the retrieval result data recalled by multiple paths, and obtaining a retrieval result. And meanwhile, the document abstract short sentence group is injected into a search suggestion function of a search engine. According to the method, the retrieval accuracy can be improved, and the user experience is improved.

The invention discloses a unified search and page configuration rendering method and system based on a data model. The method comprises the following steps: S1, data acquisition and model mapping; s2, indexing and synchronizing data; s3, unified search request processing; s4, processing and returning a result set; and S5, dynamically rendering the page. The system comprises a data source layer, a data unification layer, an index layer, an application service layer and a display layer. The invention provides a set of end-to-end integrated solution for solving the problems that multi-source heterogeneous data is difficult to integrate, the cross-system search efficiency is low, page rendering lacks flexibility and the like. According to the scheme, by constructing a standardized data model, a unified search engine index system and a dynamic page rendering mechanism driven by configuration, a complete technical link from data source access to front-end display is achieved, and the efficiency and expansibility of the system in the aspects of data management, information retrieval and page display are remarkably improved.

The invention discloses an estuary coast embankment risk early warning evaluation system and method under composite disaster-inducing factors, and relates to the technical field of hydraulic engineering safety monitoring and risk evaluation. Comprising a multi-source data acquisition module, a data preprocessing module, a dynamic index system construction module, an adaptive weight determination module, a risk assessment module, a refined early warning grade division module and a visual decision support module. Real-time sensing, quantitative evaluation and graded early warning of the dike safety state are achieved, the method can be directly applied to coastal city disaster prevention and reduction, dike project full-life-cycle operation and maintenance, major storm surge disaster emergency response and other scenes, the technical bottlenecks of single disaster-inducing factor, static weight and insufficient early warning precision in a traditional evaluation method are effectively broken through, and the method has a wide application prospect. And a precise technical support is provided for the safety protection of the estuary coast embankment.

The invention belongs to the technical field of urban climate adaptability planning, and provides an urban toughness evaluation method, device and equipment based on heat island data and a medium, and the method comprises the following steps: collecting dynamic heat island data, humanity perception data and toughness potential data, and preprocessing multi-source data; constructing a three-dimensional index system of the pressure degree-coping capacity-toughness potential of the heat island; s3, determining an index weight by adopting a reinforcement learning adaptive weight model, and calculating to obtain a final toughness value; s4, predicting short-term and long-term toughness value changes based on an LSTM-attention mechanism model, forming a toughness level-potential level linkage matrix in combination with the final toughness value and the potential level, and determining an intervention priority; according to the method, short-term thermal risk early warning and long-term toughness trend prediction are realized through the LSTM-attention mechanism model, and a high-risk area is identified in advance; through the constructed toughness-potential linkage matrix, the intervention priority is defined, and the resource utilization efficiency is effectively improved.

The invention relates to a power distribution network optimal configuration method for a high-proportion distributed new energy access scene, and the method comprises the steps: obtaining the basic data of a power distribution network, and constructing a bearing capability evaluation index system; a robust optimization evaluation model considering the uncertainty of the source load is constructed, and the critical bearing capacity is solved in combination with a bearing capacity evaluation index system; based on the critical bearing capacity, energy storage, SOP intelligent soft switching and DR demand side response are sequentially configured, an updated power distribution network state is obtained, whether convergence conditions are met or not is judged, and if yes, an optimal configuration scheme including current energy storage, SOP and DR configuration and the current critical bearing capacity is output; otherwise, returning to re-optimize. Compared with the prior art, the power distribution network can safely and efficiently consume the high-proportion distributed new energy, and the bearing capacity of the power distribution network is effectively improved.

A test question recommendation method based on large language model adaptive multi-level evaluation constructs a multi-level architecture including semantic consistency verification, fine-grained fact alignment and dynamic cognitive evaluation, and comprises the following steps: constructing an initialized data stream and executing dynamic random sampling; calculating discrete semantic entropy by using NLI bidirectional implication clustering so as to quantify and eliminate illusion content with high uncertainty; under the RAG framework, the test questions are deconstructed into atomic statements, and a fact deviation is corrected by calculating a retrieval relevance vector and a logical implication consistency score; analyzing and screening low-quality texts based on multidimensional language features of syntax and logic; vector fusion is carried out on the generated intention and the cognitive portrait of the student, and a dynamic evaluation index system adaptive to a specific teaching scene is constructed in real time by utilizing context learning. The problems of accuracy and adaptability of automatic question setting are effectively solved, and intelligent closed-loop control from test question generation to cognitive alignment is realized.

The invention discloses a new energy power grid hybrid energy storage system multi-dimensional regulation and control capability quantitative evaluation method and system, and mainly relates to the technical field of new energy power grid hybrid energy storage system regulation and control. Comprising the following steps: respectively constructing layered evaluation index systems of the hybrid energy storage unit in frequency modulation and peak regulation based on short, medium and long time scales; determining the weight of each level index in the index system; based on the hierarchical evaluation index system and the weight of each hierarchical index, performing comprehensive potential evaluation on the hybrid energy storage unit; and according to an evaluation result, the regulation and control capability of the hybrid energy storage system under different time scales is comprehensively evaluated, and an optimization and scheduling strategy of the energy storage unit is formulated according to the evaluation result. The method has the beneficial effects that the frequency modulation, voltage regulation and peak regulation potentials of the hybrid energy storage system can be quantified under different time scales, and the optimal energy storage configuration and operation strategy can be formulated according to the frequency modulation, voltage regulation and peak regulation potentials.

The invention relates to a multi-level data collection method, system and device and a storage medium. The method comprises the steps that an engineering project cost file is received; performing structured analysis on the construction cost file of the engineering project, and extracting an original data field; performing term mapping processing on the original data field to generate a standardized data entity; and according to a preset project cost index system, carrying out hierarchical collection on the standardized data entities to generate a structured knowledge base, and storing the project cost file and the corresponding structured knowledge base into a data collection case library. The method has the effect of improving the data collection efficiency and accuracy of the engineering project cost file.

The invention relates to the technical field of computer simulation, and discloses a coal mine underground reservoir environment risk assessment method and system, and the method comprises the steps: constructing a digital twinborn body of a coal mine underground reservoir; establishing a risk assessment index system; collecting monitoring data corresponding to the index system in real time; calculating risk coupling factors among different dimension indexes; according to the risk coupling factor and the real-time numerical value of each index, dynamically adjusting the weight of the index system, and generating a dynamic weight set; calculating a current comprehensive risk level; and extracting physical field parameter values in the real-time monitoring data, inputting the physical field parameter values into a multi-physical field coupling simulation engine for simulation, and outputting a prediction report. According to the invention, dynamic assessment and advanced early warning of the environmental risk of the coal mine underground reservoir can be realized, the risk identification precision and the emergency response capability are improved, and the method is suitable for safety management and control of the whole life cycle of the underground reservoir under complex geological conditions.

The invention provides a method for preferably selecting a shale gas structure storage favorable area not based on formation pressure. The method comprises the steps that a target research area is selected, and a core exploration target layer series is determined; on the basis of a target stratum shale gas preservation mechanism, core parameters independent of stratum pressure data are screened, and a comprehensive evaluation index system containing target stratum self-sealing performance, regional cover stratum conditions and structural transformation action parameters is constructed; spatial distribution analysis is carried out on each parameter, grading is carried out according to geological laws and adjacent region experience, and weight coefficients are distributed according to the influence degree of the parameters on storage conditions; obtaining a comprehensive score of the structure storage condition of each evaluation unit through grade assignment and weighted stacking calculation; and delineating a shale gas structure storage favorable area according to the comprehensive score. The method is suitable for low-exploration-degree areas with complex structures, sparse drilling wells or lack of formation pressure data, and has the advantages of objective evaluation, high operability and high practical value.

The invention relates to the technical field of historic site restoration, and discloses a historic site surrounding landscape atmosphere perception simulation and historical authenticity reconstruction method, which comprises the following steps: (S1) carrying out site region multi-dimensional data acquisition and integration; (S2) analyzing historical authenticity factors and extracting value features; (S3) constructing a landscape atmosphere perception index system and quantifying factors; (S4) performing multi-period historical scene simulation and atmosphere perception modeling; and (S5) carrying out landscape atmosphere perception simulation analysis and authenticity verification. According to the historic site surrounding landscape atmosphere perception simulation and historical authenticity reconstruction method, multi-dimensional data acquisition and integration and historical element analysis are performed, the relevance between a site and surrounding natural, artificial and humanistic environments is systematically reconstructed, and the defect that only a single building is focused in the prior art is overcome; for example, oblique photography and ancient book map fusion are utilized to restore the spatial topological relation among the ruins, historical water systems and ceremony paths, and a complete environment system supporting historical functions is formed.

The invention discloses an intelligent fault injection and performance quantification system and method for a helicopter engineering simulator, and belongs to the technical field of flight simulation and testing, and the system comprises a hierarchical combinable fault model library module which is used for the flexible construction from a part level to a system level to a composite fault; the intelligent fault injection management module is used for realizing an intelligent fault injection strategy; the multi-dimensional performance index quantification module is used for collecting data before and after fault injection in real time and setting a performance evaluation index system; the automatic test and visual analysis module is used for comparing various quantitative indexes of different control laws or different parameters of the same control law in the same fault scene to generate a comprehensive evaluation report; according to the intelligent fault injection and performance quantification system and method for the helicopter engineering simulator, efficient, objective and deep testing of robustness, stability and efficiency of an advanced flight control law in a special condition state is realized through a hierarchical fault model, an intelligent injection strategy and automatic quantitative evaluation.

The invention discloses a forest degeneration degree, degeneration type and degeneration process identification method, and relates to the field of forest resource monitoring and ecological environment evaluation.The method comprises the steps that multi-source data obtained in a research area is preprocessed, and the preprocessed multi-source data is determined; selecting multi-dimensional indexes from three aspects of forest degradation structure, composition and function, and constructing a multi-dimensional index system according to the preprocessed multi-source data; the multi-dimensional indexes comprise forest coverage rate, crushing degree, tree variety diversity, aboveground biomass and net primary productivity; generating a forest degradation index according to each index in the multi-dimensional index system; determining a forest degeneration degree according to the forest degeneration index, generating a forest degeneration type graph in combination with land coverage data to reveal degeneration differences of different forest types, analyzing a dynamic change track of a forest degeneration region in combination with a normalized combustion index time sequence, and identifying a forest degeneration process; according to the method, the multi-dimensional characteristics of degradation can be comprehensively revealed.

The invention relates to the technical field of financial risk assessment, in particular to a financial risk assessment method and system fusing multi-dimensional indexes and combined weights, and the method comprises the steps: constructing a financial cooperation risk index system containing multi-dimensional heterogeneous data; executing a combined weight calculation process based on Bayesian inference logic; performing weighted aggregation on the standardized index data and the posterior combination weight, and calculating a comprehensive financial risk index of the target assessment object; and based on the comprehensive financial risk index, in combination with a preset risk threshold model, generating a systematic risk assessment result and a structural risk distribution map for a specific financial cooperation scene. According to the method, complex risk factors are converted into visual quantitative indexes, and macroscopic decisions in transnational financial cooperation are directly supported.