250 results about "Risk prevention" patented technology

The invention discloses a water quality monitoring method and system based on large model data analysis, and the method comprises the steps: collecting multi-dimensional environment index real-time data through a remote sensing device and an underwater mobile sensor, completing the noise filtering and format standardization through an edge calculation node, and inputting the data into a machine learning model; the method comprises the following steps: automatically extracting space-time distribution characteristics and intelligently identifying potential abnormal modes, immediately starting multi-parameter correlation analysis when an abnormal degree exceeds a threshold value, constructing a deviation correlation map to accurately invert pollution source space coordinates, further performing time sequence prediction modeling in combination with a historical data sequence, and deducing a future diffusion path track of pollutants. And finally, deeply overlapping and fusing the predicted trajectory and the ecological sensitive area map, quantitatively calculating the comprehensive risk score distribution of each intersection area by using a risk assessment algorithm, automatically generating a visual environment monitoring report, and updating a historical sequence to form closed-loop learning at the same time. According to the invention, the emergency response speed, the traceability accuracy and the risk prevention and control capability of the sudden pollution event of the water environment are greatly improved.

The invention relates to the technical field of sewage treatment, and discloses a risk early warning method and system for a sewage treatment trusteeship operation project. The method comprises the following steps: acquiring multi-source operation data of sewage treatment equipment, and generating a time sequence data set after time synchronization processing; identifying abnormal data points based on the data set and generating an abnormal mark sequence; performing time sequence fluctuation and persistence analysis on the sequence, and extracting features to construct an abnormal trend feature vector; performing correlation analysis in combination with medicament dosage records, and determining a cost risk assessment result; generating a layered early warning signal according to the risk level, and matching a response strategy; and integrating related data to form a push data set, sending a notification to an operator and updating a processing record, and finally generating a traceable exception processing file. According to the invention, timely early warning and accurate response in the sewage treatment process can be realized, and the efficiency and safety of operation management and the accuracy of risk prevention and control are improved.

The invention discloses an intelligent early warning system for safety of buildings around foundation pit construction, and relates to the technical field of construction safety monitoring. The platform adopts a four-layer architecture of a sensing layer, a transmission layer, a platform layer and an application layer. The sensing layer collects data in real time through a multi-class sensor array; the transmission layer wirelessly transmits data by using the Internet of Things technology; the platform layer serves as a core, comprises a data management module, a digital twin modeling module and an intelligent analysis early warning engine, and is responsible for data preprocessing, three-dimensional model driving and intelligent risk study and judgment based on machine learning and a dynamic threshold value; and the application layer provides visual display and early warning push service through a Web terminal and a mobile APP. All-weather automatic monitoring, intelligent advanced early warning and accurate risk prevention and control of the surrounding environment of the foundation pit are achieved, a complete intelligent management closed loop is formed, and the construction safety level is effectively improved.

The invention discloses a risk assessment method for power grid cascading failures, and the method comprises the steps: firstly determining an assessment range and a target, and carrying out the data collection after the assessment range and the target are determined; establishing a system model, and constructing a digital model capable of accurately reflecting physical characteristics, operation states and control behaviors of a real power grid in a computer; constructing an initial fault scene; analyzing a cascading failure propagation path; quantifying risk indexes; and evaluating the cross-domain association influence, supplementing and evaluating the linkage influence on the association system in combination with the cross-domain association characteristics, and proposing a risk prevention and control and optimization strategy. According to the method, potential cascading failure inducements in a power grid can be actively mined through risk assessment of power grid cascading failures, a traditional passive mode of failure reprocessing is broken through, weak links are positioned, key equipment which easily triggers the cascading failures is found out through initial failure scene screening and propagation path simulation, and long-term latent hidden dangers are avoided.

The invention discloses an uncertainty guided few-sample harmful speech detection method (U-GIFT). According to the method, a pre-training language model is finely adjusted based on a small number of labeled samples, and a semi-supervised self-training and uncertainty guiding strategy is combined. Monte Carlo Dropout is started in the reasoning stage, multiple times of random forward propagation are carried out to obtain sample posterior distribution, prediction entropy and information gain are calculated, pseudo-label samples are sorted and screened, and only high-confidence samples are selected to be added into a training set. And in order to reduce the influence of a pseudo labeling error, designing a stability weighting mechanism, giving a sample weight according to a prediction variance, and constructing a joint loss function, so that the model preferentially learns a stable sample to improve the detection performance. According to the method, the semantic and attention mechanism of the pre-training model is utilized, the detection effect is remarkably improved under the conditions of few samples, imbalance, multiple languages and cross domains, models such as BERT, RoBERTa, XLM-R, LLaMA2 and DeepSeek-R1 are compatible, and the method is suitable for content auditing and risk prevention and control.

The invention discloses a field operation video monitoring risk prevention and control method, system and device and a medium, and the method comprises the steps: analyzing the reference operation risks of the whole network over the years, and constructing a reference operation risk library according to the analysis result; establishing a first risk model through the reference operation risk library, and identifying risk influence factors; constructing a second risk model through the risk influence factors, determining weight values of the risk influence factors, outputting risk values, and performing risk grade division according to the risk values; deploying video monitoring equipment to identify operating personnel, synchronously monitoring an operation site, and analyzing and judging an abnormal condition through a pixel difference value of front and back frame images; and when the abnormal situation is judged, determining an early warning level in combination with the risk level, and giving an alarm. According to the method, historical risk data analysis and an intelligent video monitoring technology are deeply fused, so that risk assessment is fundamentally converted from static experience judgment to dynamic quantitative prediction.

The invention discloses a quantitative early warning method for coupling risks of an urban lifeline system, and the method comprises the steps: collecting the real-time data of each system, and constructing a multi-level network which reflects the physical connection and function dependence relation between the systems; determining risk source nodes in the network, and traversing all communicated potential risk transmission paths along a dependency direction; for each path, a path cascade failure probability is calculated by fusing a node historical fault probability and a real-time state; quantitatively evaluating the risk value of each path in combination with the key level of the affected node; and finally, according to the risk value sorting, outputting the path in the front of the sorting and the key node thereof as early warning information. According to the method, global identification and quantitative evaluation of the cross-system risk conduction chain are realized, weak links of the network can be accurately positioned, and a scientific decision basis is provided for targeted risk prevention and control.

The invention discloses a port operation risk early warning method and system based on multi-source data association feedback, relates to the field of port transportation, and solves the problem that the existing port operation risk early warning technology is poor in early warning effect, and the method comprises the steps: S1, obtaining a risk assessment priority coefficient corresponding to a port operation area, obtaining port operation historical analysis data, and carrying out the early warning of the port operation risk; s2, acquiring a priority evaluation operation area according to the port operation historical analysis data, performing real-time operation index analysis on the priority evaluation operation area, and acquiring real-time operation index analysis data according to an analysis result, and S3, performing operation index visualization processing on the priority evaluation operation area according to the real-time operation index analysis data, and S4, performing distributed operation risk early warning on the pre-selected freight port according to the port operation historical analysis data and the port operation risk assessment graph. According to the method, the pertinence and the high efficiency of port risk prevention and control can be effectively enhanced.

The present invention relates to the technical field of international trade risk management, and particularly relates to an intelligent international trade risk prevention and control method and system based on multi-modal data analysis. The method comprises: collecting transaction records, logistics information, policies, laws and regulations, and dynamic market data; extracting abnormal behavior features and evaluating a transaction risk grade; in view of logistics and policy data, evaluating the degree of influence of a cross-border transportation risk, so as to obtain a comprehensive risk index; and by means of the dynamic market data, estimating an overall risk level for early warning. The method can improve the accuracy and real-time response capability of international trade risk prediction, thereby meeting intelligent risk management requirements in complex environments.

The invention provides an urban flood disaster dynamic risk assessment method under multi-scale model coupling, and relates to the technical field of urban flood disaster risk prevention and control and emergency risk avoidance. The method comprises the following steps: evaluating the urban flood disaster risk according to urban underlying surface type data, vertical elevation data, drainage pipe network data, hydrogeological data, actually measured rainfall data, hydrological monitoring data and disaster-bearing system instability failure threshold data; constructing a multi-agent system model covering a disaster-inducing factor agent, a disaster-pregnant environment agent and a disaster-bearing body agent, and outputting a dynamic risk value of a disaster-bearing body; constructing a dynamic model of a disaster-affected body disaster-affected system by using a system dynamic modeling technology, outputting a risk change process of a disaster-affected body and quantifying a risk value; the flood disaster emergency prevention and control effect is evaluated by combining engineering and non-engineering measures, and emergency risk avoiding measures are optimized. According to the flood disaster assessment method and device, the flood disaster assessment can be more accurate through the combined action of the macroscale, the mesoscale and the microscale.

The invention relates to the technical field of information technology and industrial safety management, and discloses a hazardous waste whole-process risk prevention and control method and system. The method comprises the following steps: acquiring a real-time monitoring data set of each link of the hazardous waste management chain; calculating the fluctuation amplitude of the environment change indexes and analyzing the distribution characteristics of the operation deviation marks; when the two meet a preset condition, judging the initial signal intensity of risk upgrading by utilizing a classification model; screening high-intensity signals and inputting the high-intensity signals into the regression model to obtain a risk transformation trend; matching the risk conversion trend with a historical risk mode to generate a dynamic monitoring adjustment parameter; if the parameter indicates that the monitoring sensitivity is insufficient, fusing additional sensor data to generate an enhanced monitoring data set; and tracking a risk propagation path based on the enhanced data set, and predicting an occurrence position and a time point of a risk peak value. According to the method, the real-time performance, the accuracy and the response speed of hazardous waste management are improved, and the effect of risk prediction and management is remarkably enhanced.

The application relates to the technical field of research and development audit, and discloses a research and development expense allocation risk-oriented audit method and system. The method acquires multidimensional characteristic data of project stage division data of a research and development project and audit constraint conditions such as a time window constraint and a risk tolerance constraint; a risk coupling network model is constructed based on the project stage division data and the risk tolerance constraint, a risk-oriented audit rule set is generated; subsequently, an audit path is planned according to expense flow direction data and the rule set, and an initial audit scheme containing an audit node sequence and a risk monitoring threshold value is output; the time window constraint is taken as an optimization target, and timing optimization is performed on the audit node sequence, so that a dynamic audit scheduling scheme is obtained; risk transmission analysis is performed based on the scheme, and a risk prevention and control strategy set containing a multilevel risk disposal scheme and an emergency response mechanism is generated; in the audit process, the risk prevention and control strategy set is triggered for execution according to the risk monitoring threshold value.

The invention belongs to the technical field of aircraft test design, and particularly relates to a method and a device for determining risks of a manufacturer and an ordering party in a testability test. The method comprises the following steps: step S1, obtaining influence factors of a contractor risk and an ordering party risk; s2, calculating the maximum feature root of a first matrix constructed by the importance among the influence factors, and meanwhile, calculating the maximum feature root of a second matrix constructed by the influence degrees of the influence factors on the acceptor and the ordering party; s3, calculating a correction amount according to a ratio of the maximum feature root of the first matrix to the maximum feature root of the second matrix; and S4, according to the correction amount, correcting a given acceptor risk and a given ordering party risk. According to the method, the design requirements of the acceptor risk and the ordering party risk are met, and scientific balance between cost control and risk prevention and control is realized.

The application discloses a water resource system risk multi-link conduction method, mainly comprising the following steps. Firstly, risk element data in a researched area are collected and standardized processing is conducted; then, water resource system risk links are constructed by using the correlation between risk elements; then, a risk conduction mechanism is defined: ①risk opening stage: simple mechanism of risk conduction and opening condition of risk are described; ②resistance threshold effect: the resistance ability of a system in risk conduction is described, according to the conduction characteristics of the risk link, the risk conduction mechanism and the resistance threshold effect of risk links with different structures are revealed; ③recovery threshold effect: natural and social repair forces make the risk not exist all the time, therefore, the risk recovery effect is defined; ④threshold value updating calculation: the resistance and recovery abilities are increased by risk prevention and control, therefore, the threshold value is updated; ⑤risk termination stage: the risk termination condition is deduced according to the risk conduction mechanism; ⑥risk intensity and conduction speed relationship: the greater the risk disturbance intensity is, the faster the risk conduction speed is. By exploring the risk link conduction mechanism, the water resource risk evaluation system under complex conditions is improved.

The invention provides a multi-agent-based power market risk monitoring method and system, relates to the field of power market risk control, and integrates information perception, inference analysis and execution feedback functions by constructing a three-layer progressive multi-agent collaborative network composed of an information monitoring layer, a collaborative analysis layer and a supervision execution layer. A hybrid communication protocol based on semantic similarity is adopted, structural data transmission and a natural language collaborative discussion mechanism are combined, deep collaboration between agents is comprehensively supported from quantitative analysis to qualitative reasoning, and in the process of generating a power market decision scheme, the decision scheme of the power market is generated based on an antagonism debate mechanism. The efficiency optimization agent and the risk control agent are debate for multiple rounds, the weight is dynamically adjusted through the reinforcement learning algorithm to generate a balance decision scheme, the limitation of a traditional single-target optimization method is broken through, multiple targets of supervision efficiency and risk control can be completely considered, and self-adaptive decision support is provided for intelligent supervision and risk prevention and control of the power market.

The invention discloses a tunnel engineering construction drawing design risk event safety assessment and standardized prevention and control method, which comprises the following steps: constructing a sample library matrix containing risk sources, risk events and risk prevention and control technologies at the same time, training a random forest model, and extracting risk source parameter weights; weighting the risk source parameters of the tunnel to be built by using the weight, inputting the weighted parameters into the model, and predicting the risk event probability; carrying out binaryzation by adopting a self-adaptive threshold algorithm based on F1-score to obtain a risk event prediction result; calculating multi-dimensional similarity with a sample library in combination with a Gaussian kernel function, normalizing to obtain a sample weight, and recommending an excavation method and an advanced pre-reinforcement measure according to the sample weight; and finally, a field implementation result is fed back to the sample library, and the bandwidth and the threshold are optimized by using gradient descent to realize closed-loop updating. The method reduces human intervention, improves risk assessment objectivity and prevention and control scheme standardization level, and is suitable for safety risk assessment in a complex geological tunnel construction drawing design stage.

The invention belongs to the technical field of virtual power plant operation evaluation, and particularly relates to a virtual power plant operation comprehensive evaluation method and system.The method comprises the steps that a three-level multi-dimensional operation risk evaluation index system is constructed, and three types of weight vectors are obtained through an analytic hierarchy process, an entropy weight method and an inter-index correlation and conflict objective weighting method; carrying out collaborative correction through a non-cooperative game model to obtain an optimal comprehensive weight vector; a standard cloud model of each risk level is constructed based on an extension cloud model, an actual evaluation cloud model is constructed in combination with the score of a professional scoring system and an optimal weight, the score weight of the professional scoring system is determined through a grey correlation degree, an evaluation value is corrected, the actual cloud model is updated, and finally the digital characteristics of the actual and standard cloud models are compared. And quantitatively judging the operation risk level of the virtual power plant. According to the method, the comprehensiveness, reliability and scientificity of evaluation are improved, and support is provided for risk prevention and control of the virtual power plant.

The invention discloses an ethical decision chip for a home-based care service robot, the robot and an ethical risk prevention and control method. The chip comprises a scene identification module which identifies a service scene and a risk level; the hierarchical ethical rule storage module is used for storing an ethical rule system expressed in a quantization parameter form; the ethical rule engine is used for calling quantitative parameters to carry out multi-target ethical tradeoff calculation and blocking the highest emergency risk starting instruction filtering feature library; and the ethical auditing module is used for encrypting and storing decision process data. The invention further provides a robot comprising the chip and a prevention and control method based on the chip. Physical isolation of ethical constraint and task processing is achieved through independent hardware, abstract ethical values are converted into quantifiable technical parameters, scene self-adaption grading prevention and control are achieved, the technical problems that ethical rules cannot be quantified, the decision making process is opaque and the like are solved, and the ethical safety level of the robot is improved.

The application provides a RWA asset physical state off-chain photograph uploading watermark generation method, comprising: S1. Data acquisition and algorithm pre-judgment; S2. Photograph shooting and watermark generation; S3. Algorithm interaction and iterative optimization; S4. Hash calculation and on-chain evidence storage. The application aims to solve the problems of algorithm coordination loss, insufficient creativity, weak authenticity verification and risk prevention and control capability in the existing RWA asset photograph uploading scheme, and realizes the authenticity, security and efficiency of RWA asset physical state record by constructing an algorithm fusion interaction system and an optimization basic module, meets the business compliance and risk prevention and control requirements, and improves the scene adaptability, resource utilization efficiency and operation convenience, and is suitable for multiple types of RWA assets and complex business scenarios.

The invention relates to the technical field of bid evaluation risk prevention and control, in particular to a bid evaluation risk prevention and control system and method integrated with multi-dimensional intelligent analysis, and the method comprises the steps: carrying out the semantic vector mapping and fine-grained similarity calculation of a bid text through a pre-training language model, recognizing hidden similar contents, and carrying out the recognition of the hidden similar contents; generating a semantic-structure two-dimensional similar segment set; on the basis, calculating a text similarity matrix between bidding subjects and a key term matching offset, and screening an abnormal associated subject cluster; further extracting industry and commerce information, a behavior time sequence and network topology data, and constructing a subject association evolution trajectory chain; and finally, in combination with a risk threshold reference, measuring a semantic space distance and a behavior correlation critical distance, and screening a high-risk bidding path. The full-chain prevention and control from text detection to risk deduction is realized, and the recognition accuracy and early warning capability of hidden bid surrounding and stringing behaviors are remarkably improved.

The invention relates to a disaster area assessment method, system and device based on geological disaster exploration and a medium. The method comprises the following steps: analyzing multi-source exploration data to obtain a unit spatial-temporal characteristic tuple and a physical incidence matrix; performing graph neural network calculation processing based on the unit spatial-temporal feature tuple and the physical incidence matrix to obtain a dynamic risk assessment result, a multi-level attention weight and a physical state deviation amount; and based on the dynamic risk assessment result, the multi-level attention weight and the physical state deviation amount, performing report generation processing to obtain a geological disaster dynamic risk assessment report. According to the method, by means of multi-source data analysis, graph neural network calculation and the like, the accuracy, dynamism and interpretability of geological disaster assessment are improved, and the disaster risk accurate prevention and control and decision support capability is enhanced.

This invention relates to the field of digital asset analysis technology, and more particularly to the RWA digital copyright trading system in the cultural industry. It includes constructing a cultural asset value memory network and extracting implicit cultural value transmission relationships to provide a comprehensive and accurate data foundation and value correlation basis for subsequent transaction analysis and risk assessment; calculating the discrete entropy of trading groups to promptly identify abnormal group structures, enabling early detection of potential transaction risks and abnormal market fluctuations; tracing the transmission path and calculating the attenuation coefficient when a sudden change in discrete entropy is detected to pinpoint the source and intensity of risk propagation, providing crucial clues for risk prevention and control; calculating the repricing step probability by combining transmission intensity and price fluctuations to quantitatively assess the likelihood of significant price changes in target assets; and locking suspected bubble trading nodes and isolating the links when the repricing step probability exceeds a risk threshold, effectively blocking risk spread and ensuring the stability and security of the trading system.

The invention discloses a bidding margin intelligent management method and system based on a dynamic risk portrait, and the method comprises the steps: building a dynamic risk portrait through obtaining project attribute data and supplier multi-source heterogeneous behavior data, and inputting a pre-trained bidding risk prediction model to calculate a dynamic risk index; and synchronously executing cash deposit payment state rule verification and dynamic risk index evaluation at the bid opening verification node, generating a comprehensive verification report, calculating a real-time commercial credit score through a credit evaluation engine, generating a differentiated cash deposit management strategy according to the score, and outputting a final state scheme. According to the invention, the conversion of bidding margin management from formal review to risk intelligent early warning is realized, the bidding risk is effectively identified, the risk prevention and control accuracy is improved, and the safety and intelligent level of government purchase are significantly improved based on a differentiation strategy of real-time credit scoring.

This invention relates to the field of inventory cost analysis, addressing the problems of lagging information updates and lack of predictive warnings in cost accounting, which prevent the automatic triggering of targeted inventory optimization strategies. Specifically, it is a rolling analysis method for spot inventory costs with full-process tracking, including a pre-warehouse process cost statistics module, an in-warehouse cost statistics module, a rolling analysis module, an inventory cost prediction statistics module, and an inventory optimization decision-making module. Based on complete inventory cost accounting, this invention endows cost management with real-time and forward-looking capabilities through rolling analysis and dynamic prediction. Ultimately, through intelligent linkage between cost and profit and a multi-level decision-making mechanism, it achieves an intelligent closed loop from data to action, transforming inventory cost management from traditional recording into a core decision-making tool for profit protection and risk prevention, effectively improving the enterprise's inventory operation efficiency and overall profitability.

The invention discloses an electric power system risk management and control method, device and system and a storage medium. The method comprises the following steps: receiving inquiry data which is input by a user and is related to electric power system risk management and control; inputting the inquiry data into a language model for semantic analysis to obtain a semantic vector, and inputting the semantic vector into a classification model to determine a target intention category of the user; extracting scene keywords related to a power grid system from the target intention category, mapping the scene keywords into a preset professional knowledge base to obtain retrieval fields, performing retrieval in the professional knowledge base based on the retrieval fields to obtain risk knowledge fragments related to risk management and control, and performing risk management and control on the risk knowledge fragments. Filling the risk knowledge fragment into a preset answer template to generate a risk management and control scheme; and managing and controlling the risk prevention and control process of the power system based on the risk management and control scheme. The accuracy of risk management and control of the power system can be improved based on the professional knowledge base.

The invention discloses a financial information management method based on a knowledge graph, and the method comprises the following steps: S1, collecting multi-source heterogeneous financial data, and generating an initial financial data set; s2, extracting a financial entity and semantic relationship, constructing a triple set, and forming an initial financial knowledge graph; s3, performing semantic enhancement processing, and constructing a semantic enhanced financial graph; s4, setting an atlas updating scheduling mechanism, executing a dynamic updating operation, and generating a dynamic atlas structure; s5, inputting into an improved NodeFormer model, and outputting a risk path identification result; s6, constructing a map semantic question and answer structure, and outputting a structured query response result; and S7, constructing an atlas visual display module, and generating an atlas analysis view and an audit suggestion result. According to the method, the identification precision and the tracking capability of the risk path in the financial data are improved, and the transparency, the response efficiency and the risk prevention and control capability of the financial auditing process are effectively enhanced.

This invention provides a method and system for risk prevention and control management of shallow ditches on sloping farmland, comprising: acquiring multidimensional shallow ditch data of sloping farmland; constructing a twin environment of shallow ditches on sloping farmland based on the multidimensional shallow ditch data; employing a cluster of shallow ditch risk prevention and control intelligent agents based on a neuroevolutionary architecture to perform risk simulation and strategy exploration; generating a candidate shallow ditch risk prevention and control strategy set; constructing a shallow ditch association map of sloping farmland; strengthening the candidate shallow ditch risk prevention and control strategy set according to the shallow ditch association map of sloping farmland; generating a strengthened shallow ditch risk prevention and control strategy; acquiring actual feedback data of the strengthened shallow ditch risk prevention and control strategy; and optimizing the strategy based on the actual feedback data, thereby improving the efficiency and reliability of shallow ditch risk prevention and control on sloping farmland.

This invention provides a method for characterizing the risks of the preservation environment for museum collections, comprising the following steps: S1, constructing a risk characterization system and acquiring information on the museum collections and the environment; S2, acquiring environmental variables and environmental risk indicators, and identifying key environmental variables; S3, constructing an environmental risk status classification model and acquiring preset classification control limits; S4, acquiring several real-time environmental variables and determining the classification control limits at the current moment; S5, comparing the current classification control limits with the preset classification control limits to determine the current risk status classification and generate a risk control QR code; S6, displaying the generated QR code on a museum collection terminal device. Through the above steps, this invention can quantify and classify the risks of the preservation environment for museum collections and characterize them quickly and intuitively, enabling managers to promptly and fully grasp the risk status of the preservation environment, facilitating timely risk management, and improving the risk prevention, control, and protection capabilities for museum collections.

This application provides a traffic prediction method and related apparatus, relating to the field of software technology. The method includes: acquiring the temporal traffic characteristics and interface spatial characteristics of a target interface; retrieving a trained traffic prediction model, wherein the traffic prediction model is obtained by iteratively training a basic model using the temporal traffic characteristics and interface spatial characteristics of a calibrated interface as training samples, with the goal of the predicted traffic of the training samples approximating its actual traffic; and inputting the temporal traffic characteristics and interface spatial characteristics of the target interface into the traffic prediction model to obtain the predicted traffic of the target interface. This application achieves high-precision prediction and reliability assessment of interface traffic in complex business environments, providing data support for resource scheduling and risk prevention.

The invention relates to the technical field of computer data processing, and discloses a dynamic standing book and risk early warning method for a bill full life cycle, and the method comprises the steps: collecting structured bill information and external credit investigation data; establishing a dynamic machine account by using the collected information, and performing automatic circulation management on the life cycle state of the bill based on a state machine model; performing risk monitoring on bills in the dynamic machine account, calculating credit risk scores of acceptors through weighted fusion of external credit scores and internal performance scores, and further calculating bill cashing risk indexes in combination with bill amounts and remaining days; and finally, based on the state change event or the risk early warning result of the bill, business and financial integrated cooperative processing is executed. According to the invention, automation and refinement of bill management are realized, a quantitative and dynamic risk early warning mechanism is established, deep fusion of business and financial processes is promoted, and management efficiency and risk prevention and control capability are significantly improved.