52 results about "Delphi method" patented technology

The invention discloses a territorial space planning index dynamic evaluation model, and particularly relates to the field of territorial planning, and the model comprises a multi-source heterogeneous data fusion module, an index system construction module, a dynamic adjustment model construction module, a scheme evaluation and optimization module, and a model application and dynamic updating module. According to the method, various spatial data are integrated through a multi-source heterogeneous data fusion technology, and the data quality is ensured by adopting a three-stage cleaning assembly line and an intelligent correction algorithm; the method comprises the following steps: constructing an index system based on six core contents of territorial space planning, and determining an index weight by applying a Delphi method and an analytic hierarchy process to realize adaptive adjustment of an index threshold; the model adopts time sequence analysis, regression analysis and a machine learning algorithm to predict a development trend, a dynamic feedback mechanism is established in combination with a system dynamics method, and an evaluation scheme is quantified through an analytic hierarchy process; the model performance is evaluated by adopting indexes such as accuracy rate and precision rate, and parameters are continuously optimized based on an evaluation result; finally, the model is integrated to a service system to realize real-time monitoring, and dynamic updating is realized through three mechanisms of data driving, performance triggering and regular maintenance.

The invention relates to a multi-agent-based bionic domain knowledge graph automatic construction method and system. The method comprises the following steps: constructing a bionic domain conceptual model; establishing a multi-agent system, and automatically extracting bionic entities and semantic relationships between the entities from an unstructured text; carrying out multi-dimensional collaborative verification on the extracted knowledge; based on a Delphi method consultation mechanism, collaborative decision making is carried out on verification results; and performing alignment and fusion on the verified knowledge to form a structured bionic domain knowledge graph. According to the method, three core technologies of a field fine-tuning multi-agent system, a multi-dimensional collaborative verification mechanism and Delphi method consultation decision are fused, so that automatic and high-efficiency construction of the bionic field knowledge graph is realized, and the generated knowledge graph has accuracy and comprehensiveness; the technical problems that a traditional construction method is low in automation degree and the knowledge accuracy is difficult to guarantee are effectively solved, and key knowledge infrastructure support can be provided for bionic theoretical research and technical innovation.

The invention relates to the field of target intention prediction, and relates to a target intention recognition method based on knowledge and data combined driving, and the method comprises the following steps: 1, collecting behavior variable data of an air flying target, and carrying out the data cleaning, thereby obtaining x; 2, expert knowledge is obtained through a Delphi method, and a confidence rule base is constructed; step 3, inputting the data into a confidence rule base module to obtain an embedded representation xe of expert knowledge, and splicing the embedded representation of the expert knowledge and the data to form lt; x, xegt; all the data are input into the neural network module; and step 4, iteratively optimizing parameters of the belief rule base and the neural network in a collaborative optimization mode until the model converges. According to the method, the effect of expert knowledge in the intention recognition process is fully utilized, and the accuracy of the model is improved. And high intention recognition accuracy can still be obtained under the condition that the data volume is not large.

The invention discloses an expert matching method based on structured data, and the method comprises the following steps: firstly, calculating the objective weight and subjective weight of each result index through information and a Delphi method based on the structured data in a database, and generating an expert comprehensive academic score; then, keyword information input by a front end is obtained, the matching degree of keywords and expert fields is calculated by adopting a word frequency-inverse document frequency algorithm, and experts are grouped according to the matching degree; and finally, according to the scale of the expert database and the number of persons to be extracted, adaptively selecting a random extraction or hierarchical distribution extraction mode to determine a target expert. According to the method, through a dynamic weight calculation model and an intelligent stratified sampling mechanism, the accuracy and flexibility of expert matching are realized, the score is continuously optimized in combination with the historical participation performance data of the experts, and the scientificity and practicability of expert extraction are improved.

The invention belongs to the technical field of intelligent automobile automatic test and evaluation, and particularly relates to an intelligent automobile lane change evaluation index dynamic construction method based on transferable utility, which comprises the following steps: constructing an expert dynamic game framework based on an improved Delphi method, screening core evaluation indexes through three-wheel anonymous feedback iteration, and constructing an expert dynamic game framework; a multi-dimensional evaluation index is constructed; based on the constructed multi-dimensional evaluation indexes, constructing a feature function of the transferable utility alliance by adopting an improved Shapley value algorithm; and identifying a typical scene to which the current vehicle currently belongs, analyzing a driving intention, activating a corresponding priority strategy based on a current scene state, and adjusting the weight of a multi-dimensional evaluation index in real time by reconstructing a transferable utility alliance. Compared with the prior art, the method can effectively coordinate the balance relation between the safety and the passing efficiency, and provides a more accurate quantitative evaluation means for verification of an intelligent automobile lane changing decision algorithm.

The invention relates to a method and a system for comprehensively evaluating and quantifying an aging transformation effect of an old community, and particularly belongs to the technical field of aging transformation evaluation. A three-dimensional model is constructed by fusing spatial, physical and environmental multi-source data through AR scanning and an algorithm, resident demands are extracted through natural language processing and a Delphi method, tags are matched and transformed, a multi-target scheme is optimized by adopting a simulated annealing algorithm, and a comprehensive index is calculated in combination with basic evaluation, investment benefits and property management coefficients. The system comprises five functional modules, achieves the precision and scientization of evaluation, effectively improves the rationality of a reconstruction scheme, and promotes the standardized development of the aging-suitable reconstruction industry of old communities.

The invention relates to a software evaluation method. The method comprises the following steps: compiling a product usability scale through an SPSS exploratory factor analysis method; constructing an expert consistency evaluation table by utilizing a Delphi method; obtaining a software overall feeling score in an online questionnaire form; obtaining a software efficiency experience score and a software performance experience score according to the user usage behavior data; the product usability scale and the expert consistency evaluation table serve as questionnaires, software usability scores and software design normative scores are obtained through online questionnaire survey, and software evaluation scores are obtained through weighted summation of software overall feeling scores, efficiency experience scores, performance experience scores and operation experience scores. According to the characteristics of the life insurance industry, a product usability scale and an expert consistency evaluation table suitable for life insurance industry personnel are compiled, and the problems that an index system in the prior art is universal, and indexes and scales which are based on the index system and can be suitable for tool product characteristics in the insurance industry are lacked are solved.

The invention discloses a real-time network security threat early warning analysis method, which comprises the following steps of: constructing a multi-dimensional value radar index system; establishing a multi-dimensional evaluation framework, and quantifying bridge and tunnel values; deploying a multi-source data acquisition network: constructing an integrated data acquisition system, and performing real-time mapping between a physical space and a digital space; and adaptive fusion analysis: constructing a quantum state superposition classifier, representing bridge and tunnel characteristics by using quantum bits, constructing a real-time digital twin mirror image engine, carrying out dynamic evaluation algorithm loading through linkage of a data acquisition network, a mirror image body and an algorithm pool, and introducing an ecological correction coefficient and a hidden value correction coefficient to carry out negative adjustment on an economic contribution value. Dynamically distributing an index weight by combining an entropy weight method and a Delphi method with a particle swarm optimization algorithm, and outputting an economic equivalent value in combination with the index weight; building a four-dimensional visual decision platform; and displaying the interactive radar map based on WebGL three-dimensional rendering and data binding technology.

The invention discloses an energy storage battery fault early warning method and system based on big data analysis, and relates to the technical field of big data analysis, and the method comprises the steps: collecting multi-source data, carrying out the preprocessing, extracting the features of the multi-source data, and constructing an input vector; setting an implicit state vector by using a Delphi method, and generating an input pair for prediction in combination with the input vector to obtain an optimal voltage prediction value; a compensation vector is constructed based on the optimal voltage predicted value, after independent MLP sub-networks are established for the positive electrode and the negative electrode of the energy storage battery respectively, the compensation vector serves as input, non-ideal voltage correction values under the positive electrode and the negative electrode are obtained, the optimal voltage predicted value is corrected, and a final correction voltage value is obtained; according to the method, the false alarm rate and the delay rate can be remarkably reduced, high-precision recognition and active early warning of early faults can be achieved in the energy storage field station-level application, and the system safety and the operation and maintenance efficiency are greatly improved.

The invention discloses an evaluation method, device and equipment for a clearing mode of a carbon market and a storage medium, and relates to the field of energy clearing modes and evaluation methods, and the method specifically comprises the steps: extracting high-frequency keywords for describing the clearing mode of the carbon market through a big data AI technology, and constructing an evaluation index system; performing translation correction on a zero value or a negative value in the index data, calculating a skewness coefficient after identifying and processing an abnormal value, correcting data skewness by adopting Box-Cox transformation when the skewness coefficient is greater than or equal to 0.5, and eliminating dimensional difference in combination with Z-score standardization; the subjective weight of the expert and the objective weight generated by the entropy weight method are obtained in combination with the Delphi method, and the comprehensive weight is generated through linear weighting; and constructing a weighted standardized matrix, calculating the distance and proximity between each scheme and the positive or negative ideal, and determining the optimal clearing scheme according to the proximity sequence. The technical problem of large data deviation in market clearing mode evaluation is solved, and the market resource allocation efficiency is improved.

The invention discloses a method, a device and a computer program product for mining an environment association rule of an electricity supplier, and the method comprises the steps: S1, collecting multi-source environment data of the electricity supplier, and carrying out the screening of a Delphi method to form a minimum data set of the association rule; s2, converting the minimum data set into a transactional database, and optimizing an Apriori algorithm by adopting a complete connection strategy and matrix vector space mapping to generate a frequent item set; s3, on the basis of the generated frequent item set, candidate association rules are generated by setting the threshold values of the minimum support degree, the confidence degree and the weight test coefficient, and the candidate association rules are filtered by applying a consequent constraint condition; and S4, constructing an analysis system integrated with the optimized Apriori algorithm, sorting the filtered association rules according to the priority order of the weight test coefficient, the confidence coefficient and the support degree, and visually outputting the sorted association rules. According to the method, the Apriori algorithm is improved, the multi-dimensional association rule in the electric power field is deeply mined, and electric power resource allocation is optimized.

This invention relates to a method for evaluating the energy-saving performance of green buildings based on a backpropagation (BP) neural network, belonging to the field of green building technology evaluation. Using the Delphi method and comparative analysis, 14 evaluation indicators are selected from five dimensions—energy-saving design, environmental energy consumption, building lighting, building ventilation, and building sunshine—to construct a quantitative indicator system. Then, the analogy-heuristic (AHP) method is used to determine the indicator weights, and consistency checks are performed to eliminate subjective bias. Finally, a BP neural network evaluation model is established, using the quantitative data of the 14 indicators as input. Through training and optimization, the energy-saving level of the green building is determined. This invention can accurately determine the indicator weights using a multi-dimensional quantitative indicator system and the AHP method, and it can ensure high accuracy of the evaluation results through the strong data processing and self-optimization capabilities of the BP neural network.

The invention relates to a Delphi consensus-based non-negative ridge regression risk sorting method and system, and the method comprises the following steps: 1) collecting expert scoring data based on a Delphi method, and constructing a scoring matrix containing post labels; 2) adopting K-means clustering in combination with nonparametric test, and extracting score divergence features; 3) constructing a sorting target variable, and introducing Gaussian disturbance to simulate score uncertainty; and 4) performing ridge regression modeling with non-negative constraint to obtain the sorting weight of each risk factor. According to the method, the stability and the organization suitability of a sorting result are improved, and the method is applied to a risk assessment scene in a complex engineering environment; the system is used for implementing the method. According to the method, the stability and organization suitability of the sorting result are improved, and the method is applied to a risk assessment scene in a complex engineering environment.

The invention provides an enterprise innovation ability portrait description method and device, electronic equipment and a medium, and relates to the technical field of data processing.The method comprises the steps that pre-acquired enterprise related information is preprocessed, and evaluation parameters are obtained; performing patent evolution technical index evaluation based on patent vectors over the years in the evaluation parameters, and mapping an evaluation result to obtain a cycle score; determining the word vector similarity of the first year of at least one companion enterprise, determining the word vector similarity of the second year according to the evaluation parameters, obtaining the companion cosine similarity between the enterprises based on the word vector similarity of the first year and the word vector similarity of the second year, and mapping the companion cosine similarity to obtain a similarity score; and on the basis of an interpretation framework constructed according to a Delphi method and a principal component analysis method, obtaining the enterprise innovation ability according to the evaluation parameters, the cycle score and the similarity score. According to the invention, the accuracy of the enterprise innovation ability portrait is effectively improved.

The invention discloses a cultural tourism economic operation data monitoring method, which comprises the following steps of: constructing a multi-dimensional value radar index system: establishing a multi-dimensional evaluation framework, and quantifying bridge and tunnel values; deploying a multi-source data acquisition network: constructing an integrated data acquisition system, and performing real-time mapping between a physical space and a digital space; and adaptive fusion analysis: constructing a quantum state superposition classifier, representing bridge and tunnel characteristics by using quantum bits, constructing a real-time digital twin mirror image engine, carrying out dynamic evaluation algorithm loading through linkage of a data acquisition network, a mirror image body and an algorithm pool, and introducing an ecological correction coefficient and a hidden value correction coefficient to carry out negative adjustment on an economic contribution value. Dynamically distributing an index weight by combining an entropy weight method and a Delphi method with a particle swarm optimization algorithm, and outputting an economic equivalent value in combination with the index weight; building a four-dimensional visual decision platform; and displaying the interactive radar map based on WebGL three-dimensional rendering and data binding technology.

The invention relates to the technical field of building heritage protection, and provides a railway building heritage protection method based on multi-source data fusion in order to solve the problems of data splitting, significant subjective deviation and decision staticization in the building heritage protection process. The method comprises the following steps: constructing a multi-dimensional digital file by comprehensively collecting a BIM model, an Internet of Things sensor network, a historical literature database and a geographic information system; establishing a hierarchical evaluation index system, setting an objective reference value, and determining the weight of a corresponding index by adopting a collaborative process integrating an analytic hierarchy process and a Delphi method; carrying out quantitative scoring through an expert team, and carrying out weighted calculation on a total score of a comprehensive value to determine a protection grade; and performing section division according to the spatial position, identifying regional dominant value features through clustering analysis, and generating a hierarchical protection strategy in combination with a protection rule base. According to the method, normal form conversion from subjective qualitative to objective quantitative in the evaluation process is realized, subjective deviation is remarkably reduced, and the accuracy and operability of protection decision making are improved.

The invention relates to the technical field of marine resource management, and discloses a coastline update potential evaluation method, which comprises the following steps: S10, constructing a coastline type database according to a related standard guide, and judging the type of a coastline to be evaluated based on the coastline type database; s20, constructing an update potential evaluation model according to the coastline type of the to-be-evaluated coastline, wherein the evaluation model comprises a target layer, a criterion layer and an index layer; s30, constructing the updated potential evaluation model into a multi-layer structure model according to an analytic hierarchy process, scoring the evaluation indexes by using a Delphi method to obtain index scores, performing normalization processing on the index scores, and performing consistency check; and S40, obtaining a data set of a to-be-evaluated coastline, inputting the data set into the multi-layer structure model, and outputting a coastline updating potential evaluation result through the multi-layer structure model.

The invention discloses an intelligent quantitative evaluation method and system for community fire-fighting toughness, and the method comprises the steps: collecting community fire accident cases, building a community fire accident text database in combination with a community fire-fighting toughness key stage, and recognizing community fire-fighting toughness related entities and mutual relationships; determining a community fire accident knowledge graph mode layer, establishing a knowledge graph, and concluding and extracting community fire-fighting toughness influence factors; a TOPSIS method is improved based on community fire-fighting toughness characteristics, key influence factors are screened, a community fire-fighting toughness evaluation index system is established, and a toughness network is constructed; and in combination with parameter learning and a Delphi method, establishing a Bayesian network evaluation model, carrying out causal reasoning and sensitivity analysis, quantitatively evaluating the community fire-fighting toughness level, identifying weak links and key influence indexes of the community fire-fighting toughness, and pointedly providing a promotion strategy. According to the method and the system, a practical tool is provided for a decision department to strengthen fire safety management and promote flexible sustainable community construction.

The invention relates to the technical field of drug signal detection, in particular to a drug safety signal detection method, device and equipment and a computer storage medium. According to the method, a multi-dimensional quantitative evaluation system is constructed through a Delphi method and an analytic hierarchy process, systematic integration and scientific weighting are carried out on statistical signal strength, predictability, severity, report quality and preset AE events for the first time, and the limitation that a traditional method depends on a single statistical index is overcome. By introducing a preset AE list and combining a traditional DPA method, the defect of missing detection of rare and serious signals by a traditional threshold rule is made up. And predictive intelligent judgment is realized by utilizing a large language model, so that the report processing efficiency is improved. By incorporating severity and report quality into an evaluation system, the credibility layering capability of the signal is enhanced. Finally, by integrating all dimension attributes and applying a dynamic weight system to carry out priority ranking, a risk signal list is generated, and the accuracy and timeliness of drug safety monitoring are improved.

An embodiment of the present application provides a method, apparatus, device, and storage medium for evaluating the reliability of a target system. Among them, the method includes: obtaining a statistical data set, where each statistical data in the statistical data set is obtained by screening the management data of different systems according to the corresponding defect attribute words; the defect attribute words include: discovered defects and / or repaired defects; determining at least one intermediate system included in the target system and at least one subsystem included in the intermediate system; based on the statistical data set, using the Delphi method to determine the probability level of each subsystem in the target system; based on the probability level of at least one subsystem included in each intermediate system, determining the repair damage probability of the corresponding intermediate system; based on the repair damage probability of each intermediate system, determining the repair damage function of the corresponding intermediate system; based on the repair damage function of each intermediate system, determining the reliability of the target system.

The invention discloses an evaluation system establishment method and device for children swimming, and the method comprises the steps: obtaining a questionnaire from an equipment end, and enabling the questionnaire to comprise the feedback content of each index in an initial index system; based on the feedback content, adjusting the initial index system by using a preset Delphi method and a preset analytic hierarchy process to determine a target index system; and actual measurement data of child swimming are acquired, and the target system is optimized based on the actual measurement data. Through the mode, the defects that the construction of the index system is limited by the influence of subjective factors of experts and is limited by relying on mass data construction are overcome.

The embodiment of the invention discloses an interaction model evaluation method and system based on an intelligent cabin user behavior sequence, and the method comprises the steps: collecting behavior sequence data of a user in an intelligent cabin, and the behavior sequence data comprises subjective feedback data and objective behavior data; determining evaluation indexes according to a Delphi method and a factor analysis method, wherein the evaluation indexes are divided into subjective indexes and objective indexes; determining a subjective index weight according to an analytic hierarchy process, determining an objective index weight according to an entropy weight method, and dynamically adjusting a comprehensive weight in combination with a normal ordered weighted average operator and a driving scene; constructing a structural equation model to quantify a path relationship between the user behavior pattern and the system performance; and outputting a comprehensive score of the interaction model through the prototype system, and carrying out anomaly detection and optimization suggestion generation on the behavior sequence. According to the method, the practicability and the expandability of the intelligent cabin interaction model can be improved.

The invention discloses a teaching process evaluation and accurate intervention method and system based on ability portray.The method belongs to the technical field of wisdom education, and the method comprises the steps that full-dimensional teaching data containing teacher and student recessive states are collected through a multi-source heterogeneous architecture, and refined preprocessing is carried out; a cognitive load theory and a multivariate intelligence theory are fused to construct a student multi-dimensional cognitive load label library and a behavior semantic unit chain model, a Delphi method and an analytic hierarchy process are combined to construct a teacher teaching ability index system, and a teaching and learning two-way linkage mapping model is established; an improved multi-modal deep learning fusion model and a transfer learning model are used for accurate evaluation, and based on an evaluation result and real-time data, hierarchical personalized intervention suggestions are generated and dynamically adjusted through an improved decision tree and reinforcement learning. The problems that existing teaching evaluation is one-sided, intervention lags behind, linkage lacks and the data security risk is high are solved, and the objectivity of teaching evaluation and the timeliness of teaching intervention are remarkably improved.

The invention provides a fuzzy risk assessment model for off-site construction, and relates to the technical field of off-site construction risk assessment. The method comprises the following steps: firstly, identifying potential risk factors related to off-site construction by adopting a Delphi method; then, an interval value intuitionistic fuzzy IVIF-DEMATEL method is used in combination with Choquet integration, the relation between adopted risk factors ARFs is analyzed, and the method comprises the steps of data collection, decision maker weight determination, matrix construction and the like; and finally, determining the individual weight of each decision maker by using an intuitionistic fuzzy TOPSIS method, carrying out aggregation evaluation to construct a matrix, calculating an ideal solution, a distance index and a proximity coefficient, and carrying out priority ranking on risk factors. According to the method, the defects of a traditional risk assessment model are effectively overcome, and the complexity and uncertainty of off-site construction risks are comprehensively considered. By integrating multiple methods, the key risk factors and the interrelation thereof can be identified more accurately, a scientific and comprehensive risk assessment basis is provided for decision makers, and making of a more effective risk coping strategy is facilitated.

This invention provides a method and system for optimizing the deployment of nearshore fisheries resource monitoring stations and navigation routes based on multiple objectives. The invention first determines the optimization objectives, then selects the optimal coupling model through evaluation indicators, and obtains the true distribution data of resource density through the optimal coupling model. It employs the Delphi method combined with information entropy and coefficient of variation as dual objective weights, along with a target-oriented correction coefficient, to obtain the dynamic weights of the optimization objectives. Three-level dynamic stratified sampling is performed using a heterogeneity threshold, and the optimal number of stations is determined through precision-cost elasticity analysis. Finally, a multi-objective optimization function is constructed, integrating navigation distance, fuel cost, and operational time matching. The optimal navigation route is solved using SA-PSO. This invention effectively solves the problems of systematic bias and insufficient resource adaptability in traditional surveys, significantly improves sampling representativeness and navigation operation efficiency, reduces survey costs, and can be dynamically adjusted according to resource conservation and fisheries production needs.

The invention relates to the technical field of national and provincial trunk line construction opening, in particular to a national and provincial trunk line construction digital transformation capability development evaluation method and system, and the method comprises the steps: setting an index system which represents the national and provincial trunk line digital transformation development level and comprises a first-level index, a second-level index and a third-level index; based on the characteristics of highway engineering construction, determining the index weight among the three-level indexes by combining a Delphi method and an analytic hierarchy process; performing consistency verification on the index weight to obtain a key influence factor weight matrix of the three-level index; calculating each secondary index value according to the key influence factor weight matrix; combining the weight of the second-level index with the second-level index value, and calculating a digital transformation development index; a Delphi method and an analytic hierarchy process are combined, so that subjective deviation can be effectively reduced, the accuracy and objectivity of an evaluation process are improved, the reasonability of index weights is ensured, and the scientificity of an evaluation result is enhanced.

The invention discloses a flammable and explosive process production line risk assessment method, device, equipment and medium, and relates to the field of flammable and explosive process production lines. The method comprises the following steps: carrying out risk analysis by utilizing a danger and operability analysis method to obtain risk factors, collecting subjective data and objective data from five dimensions of a man-machine material method for each risk factor, and constructing a five-dimensional data set; carrying out initial assignment on the risk factors by utilizing a Delphi method, carrying out weighting on an initial risk assignment result by utilizing a network analytic hierarchy process, and carrying out space-time slice decomposition on the risk sections to obtain space-time fragment data containing weight data; constructing a dynamic cloud model based on the spatio-temporal fragment data, generating a standard cloud atlas and a current dynamic cloud atlas based on historical normal working condition data and current working condition data, and performing offset degree analysis on the cloud atlas to obtain a risk assessment result; the objective consistency and dynamic space-time correlation analysis capability of risk assessment can be effectively improved, the accuracy is high, and the assessment efficiency is high.

The invention relates to the technical field of water environment treatment, in particular to a sewage storage tank multi-dimensional evaluation index system construction method and system based on a full life cycle. The method comprises the following steps: acquiring environmental parameters, design parameters, operation states, cost consumption and management record data of a target storage tank in construction, operation and maintenance stages; establishing an initial index pool covering construction, operation and maintenance stages based on the expert knowledge base and a Delphi method; performing index dynamic screening by adopting principal component analysis and Pearson correlation coefficient test to obtain an optimized index system; calculating the internal index weight of each stage by adopting a fuzzy analytic hierarchy process based on the optimization index system of each stage; configuring index data according to expert evaluation and target requirements; performing quantification processing on the index data to obtain a standard value; obtaining a comprehensive score based on the standard value; based on the comprehensive score, triggering an operation and maintenance decision according to Stotal, and reversely correcting parameters of the associated hydraulic model; and generating an evaluation report, an optimization suggestion and a weight configuration scheme.

The application discloses a risk control system and method for a financing guarantee industry, wherein an industry evaluation index system table module reduces the dimension of qualitative indexes, and a support vector machine model adopting recursive feature elimination is used to reduce the dimension of quantitative data to screen important indexes; a risk assessment model module adopts a multilayer Delphi method module to determine the weight of each index, sets an alarm signal, and sets a risk threshold of each index according to an industry standard; a risk value module is used to obtain each index value through a user input mode, and each business link risk value is calculated according to the risk assessment model module; a penalty factor module performs a credit rating prediction, and determines a credit rating binding penalty factor; and an early warning mechanism module monitors the system through an early warning task, triggers early warning monitoring according to early warning rules after a risk result is obtained, and performs early warning display. The application can effectively improve the risk control capability of a guarantee company.

The invention relates to the technical field of data processing, in particular to a smart campus service maturity assessment method based on dynamic weight and multi-modal data, and the method comprises the steps: collecting multi-modal data including educational activities, mental health, campus point cloud atlas and security events, and IT service capability, and carrying out the preprocessing to form a standardized assessment data set; constructing a six-dimension evaluation index system, determining an initial weight by combining a Delphi method with an analytic hierarchy process, and dynamically adjusting the weight based on a knowledge graph and an LSTM neural network; a feature level and decision level mixed fusion strategy is adopted for evaluation, dimension scores are calculated, and maturity levels are divided; and visually analyzing an evaluation result, generating a report containing resource configuration suggestions, and combining feedback to optimize a management strategy. According to the method, the problems of single evaluation data, fixed weight and insufficient practicability in the prior art are solved, accurate evaluation and dynamic optimization are realized, and support is provided for campus resource allocation and policy adjustment.