31 results about "Total risk" patented technology

The invention relates to the technical field of databases, in particular to a database circulation track auditing method based on multi-source data fusion. The method comprises the following steps: collecting multi-source data of different logs, preprocessing to obtain preprocessed multi-source data, extracting key features of the preprocessed multi-source data, and serially connecting the key features according to a time sequence to generate a database circulation track; collecting operation behavior data of a user, calculating a mean value and a standard deviation corresponding to the operation behavior data to determine a normal range and generate an initial baseline, and designing an automatic trigger updating mechanism to dynamically update the initial baseline to generate a dynamic baseline; and calculating the deviation degree between the actual value of each operation behavior dimension and the dynamic baseline, carrying out weighted summation to calculate a total risk value, comparing the total risk value with a risk threshold, and classifying the total risk value into low risk, middle risk and high risk. According to the invention, the false alarm rate can be reduced, and multiple times of missing report of few hidden anomalies can be avoided; the auditing resources can be focused on the high risk preferentially, manual intervention of low-risk abnormity is reduced, and compared with single-dimension grading, the auditing efficiency is improved.

Disclosed herein is a method for diagnosing a medical condition in a patient. The method comprises: obtaining, from the patient, a plurality of physiological values; implementing a first model configured to determine risk values for at least one of a plurality of medical conditions, based on the physiological values. Implementing the first model comprises: obtaining a first risk value for the at least one medical condition, based on a first one of the obtained physiological values; and weighting the first risk value based on a second one of the obtained physiological values, to determine a total risk value of the at least one medical condition for the patient.

The invention discloses an electric equipment line risk online monitoring method based on multi-source data fusion, and particularly relates to the field of electric line monitoring, and the method comprises the steps: collecting the electric, insulation, physical and environmental data of a line according to a preset frequency, and carrying out the standardization processing to obtain corresponding standardization parameters; dividing the standardized parameters into input and output dimensions, calculating output dimension parameter weights by using an entropy weight method, and constructing a theoretical value model of each output dimension by using multiple linear regression; respectively constructing electrical, insulating and physical risk functions based on the standardized parameters and theoretical values; constructing a collaborative coupling matrix in combination with each risk function value and historical data, and calculating a total risk value through a nonlinear fusion logic construction function; defining a dynamic threshold value based on each risk value, judging an abnormal point when the threshold value is exceeded, and triggering iterative optimization of the model; the fault probability is calculated by combining the total risk value and the abnormal point data, and a three-level early warning mechanism is set to judge the line risk; according to the scheme, multi-dimensional risk collaborative monitoring is realized, and the risk identification accuracy and real-time performance are improved.

The embodiment of the invention provides a natural disaster risk evaluation method, device and equipment and a computer readable storage medium. The method comprises the steps of determining natural disasters possibly involved in a to-be-evaluated region based on geographical environment information of the to-be-evaluated region; determining each natural disaster risk index based on the survey evaluation data of each natural disaster; based on the natural disaster risk indexes, a total risk index and an overlapping risk index are determined, the total risk index is related to the risk of independent occurrence of each natural disaster, and the overlapping risk index is related to the risk of simultaneous occurrence of all natural disasters; and determining a comprehensive risk index of the to-be-evaluated region based on the total risk index and the overlapping risk index. According to the method, the risk superposition influence of various natural disasters is fully considered, so that the obtained risk assessment result is more suitable for areas influenced by various natural disasters, and scientific and comprehensive data support is provided for comprehensive risk assessment of local disasters, disaster control and emergency rescue work.

The invention belongs to the technical field of receiving-end power grid evaluation, and particularly relates to a receiving-end power grid active support capability evaluation method and system based on the total risk potential of a system, and the method comprises the steps: firstly constructing an active support capability evaluation index system of a receiving-end power grid; then calculating an individual risk potential function of each index and a coupling risk coefficient between each index and other indexes, and then calculating a system total risk potential based on the individual risk potential function and the coupling risk coefficient, the system total risk potential including a system individual risk potential and a system coupling risk potential; and finally, active support capability evaluation of the receiving-end power grid is realized based on the total risk potential of the system. According to the method, on one hand, a scientific and comprehensive evaluation system is constructed, the deep evaluation of the active support capability is realized, on the other hand, on the basis of quantifying the deviation degree by using the individual risk potential, the non-linear superposition risk additionally generated by the interaction or simultaneous degradation among multiple indexes is quantified through the coupling risk potential field, and the evaluation accuracy of the active support capability is improved. And the diagnosis precision is obviously improved.

The invention relates to the technical field of civil aviation operation risk management and control, in particular to a flight full-chain operation situation risk assessment method, which comprises the steps of constructing a full-chain risk event library, determining trigger time, calculating peak time and standard deviation and amplitude of a Gaussian pulse function, and constructing a Gaussian pulse energy representation model of a full-chain risk event. Calculating a link coupling weight and a risk amplification coefficient of the full-chain functional resonance analysis-cascade model coupling network; and calculating the probability that the risk module enters an abnormal state at the next moment according to the risk amplification coefficient, selecting various parameters through Monte Carlo simulation, calculating the total risk energy according to the various parameters and the amplitude after coupling amplification, identifying the link control priority, and outputting the risk level of each operation stage. According to the method, accurate characterization of a full-chain risk event, quantitative calculation of a cross-stage coupling effect and accurate identification of a high-risk link are realized, and pertinence and effectiveness of flight full-process risk management and control are improved.

The invention relates to a resource-pooling system and to a corresponding method for risk sharing of a variable number of risk exposure components. The risk exposure components are connected to the resource-pooling system by means of a plurality of payment receiving modules configured to receive and store payments from risk exposure components for the pooling of their risks. The total risk of the pooled risk exposure components comprises a first risk contribution associated to risk exposure in relation to loan losses, and a second risk contribution associated to risk exposure based on emergency expenses. The pooled risk is divided in a parameterizable risk part and a non-parameterizable risk part by means of an indexing module. In case of triggering a loss by means of a trigger module, the suffered loss is covered by releasing associated loans and emergency expenses of the risk exposure components.

The invention discloses a security risk assessment method and system based on attack chain deduction, relates to the technical field of network security, and solves the problem that security risks are difficult to comprehensively and accurately assess in the prior art. According to the embodiment of the invention, by establishing the asset-vulnerability-attack stage mapping relationship, the whole-process visual modeling of the attack chain from initial reconnaissance to target achievement is realized, the specific effect of the vulnerability in the attack chain is determined, and the problem that the vulnerability linkage effect is neglected in traditional assessment is solved, so that more comprehensive risk assessment is realized; in addition, the mapping relation can be updated in real time according to asset change and new vulnerability discovery, accurate basic data support is provided for attack path generation, and dynamic construction of an attack surface panoramic view is achieved. Besides, by introducing path selected probability parameters, subjective strategy preferences of the attacker are brought into quantitative evaluation of the risk, so that total risk evaluation better fits real attack decision logic, and a more accurate evaluation result is obtained.

This application relates to a method, system, device, and medium for environmental monitoring decision optimization based on reinforcement learning. The method includes: acquiring multimodal raw monitoring data in a hazardous waste management scenario and performing feature fusion processing to generate a continuous state vector; calculating the current risk potential scalar value based on the continuous state vector and a constructed differentiable risk potential function; correcting the potential scalar value based on expert experience and semantics; constructing a continuous reward function and calculating an immediate reward value based on the continuous reward function and the total risk potential value; inputting the continuous state vector, the immediate reward value, and the next-time continuous state vector after the environmental feedback following the intervention action into a proximal policy optimization network for iterative training until the network converges to obtain the optimal policy. This method can significantly improve the real-time performance, foresight, and intelligent decision-making level of environmental risk monitoring, effectively curbing illegal and criminal activities related to solid waste and preventing environmental risks.

The invention discloses a risk assessment method for the public security industry, and belongs to the technical field of public security management. The method is cyclically executed in a preset time period, and comprises the following steps of: constructing a multi-dimensional dynamic risk map: gridding an activity site, converging multi-source real-time data associated with geographic grids, and calculating a basic risk value of each grid through a multi-factor risk contribution model; a risk exposure degree deduction step: acquiring a real-time police force position, calculating a police force response delay index of each grid, and performing coupling calculation to obtain a risk exposure degree index of each grid; and a police scheduling suggestion generation step of generating a police scheduling suggestion aiming at minimizing the total risk exposure degree of the whole field through a resource optimization allocation algorithm based on the risk exposure degree index. The technical problem that in the prior art, risk assessment and police dispatching are separated from each other, and on-site dynamic changes cannot be handled is solved.

The application relates to the technical field of risk monitoring, and discloses a risk early warning method, device and equipment and a storage medium, which comprises the following steps: standardizing enterprise operation time sequence data of a target enterprise collected by the application, and generating a time sequence sequence in a preset format; inputting the time sequence sequence into an improved time sequence coding model, and outputting a deep time sequence feature vector of the target enterprise; predicting an operation characteristic value of the target enterprise according to the deep time sequence feature vector, determining a residual error between the operation characteristic value and an actual operation characteristic value, and obtaining a residual error anomaly score; generating a total risk score based on an attention weight and the residual error anomaly score, and performing risk early warning on the target enterprise according to the total risk score. The position coding based on the real time interval calculation of adjacent time steps is introduced to replace the traditional fixed position coding, so that the time sequence coding model can accurately perceive the uneven time interval characteristics caused by different collection granularities, and the timeliness and accuracy of risk early warning are significantly improved.

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

The application discloses a kind of based on quantification total risk loss Large-scale city bridge tunnel network evaluation method, the method is: one, to open source geographic platform crawler, obtain road network topology data and establish bridge tunnel network model;Two, according to road grade and intersection situation, the edge and node of bridge tunnel network model are simplified;Three, traffic speed data is converted, and daily traffic volume data is obtained;Four, the monomer structure score data in detection report is converted, and monomer structure failure probability is obtained;Five, define spatial non-homogeneous Markov chain simulation structure state evolution;Six, define the direct and indirect total loss quantification formula considering structure failure, casualties, traffic closed detour and additional carbon emission;Seven, the long-term annual total risk loss of a city large-scale bridge tunnel network is quantified and evaluated.The method solves the current evaluation bridge tunnel network method only concerns safety loss and lacks consideration of functional loss, and is suitable for efficient management and maintenance of large-scale bridge tunnel network.

The invention discloses a defense method and device for a context injection attack of a large language model, and relates to the technical field of artificial intelligence network security protection. The method comprises the following steps of: performing non-uniform sampling on an input context, and extracting a head system instruction area, a tail user query area and a plurality of representative text fragments in the middle; by calculating a text compression ratio feature value and an N-gram repetition rate feature value of the middle fragment, capturing structural anomaly in a non-semantic understanding mode; calculating a semantic similarity characteristic value of the tail query and the middle segment, and carrying out intention corresponding detection; a total risk score is calculated, and hierarchical non-intrusive intervention from adding a security instruction at the end of the context to applying a dynamic Logit bias in a model decoding phase is performed according to different risk levels. According to the method, the safety detection and defense of the millisecond-level delay of the ultra-long context are realized, the internal weight of the model does not need to be modified, the universality is high, and the false alarm rate is low.

The application relates to the technical field of biomedical engineering, and discloses a VTE system execution method and system combined with a standardized scale, wherein the method comprises the following steps: performing standardized processing on original data to obtain standardized data; constructing a risk intensity flow; performing integral operation to obtain a cumulative integral value of a risk factor; calculating a dynamic risk trajectory; fusing a baseline score value of the standardized scale with the dynamic risk trajectory to obtain a total risk trajectory; calculating an instantaneous risk probability, and judging whether a VTE risk early warning is triggered according to an adaptive threshold value; the four-dimensional risk intensity flow of a body position, anesthesia, hemostatic drugs and circulation parameters is constructed, continuous quantitative monitoring of VTE risk factors is realized, early identification and timely early warning of VTE risks are realized through a dual mechanism of continuous triggering and acute triggering, and the accuracy, real-time performance and individualization level of risk assessment are significantly improved.

The elevator operation risk scoring method based on time sequence anomaly detection and correlation analysis comprises the steps that multi-source data of the Internet of Things, the Internet and the like of an elevator are obtained, a plurality of initial risk indexes are constructed, and good and bad samples are divided by calculating risk initial values; calculating the correlation between each index and the good and bad attributes of the sample, and adopting chi-square test and V value quantification and screening out effective risk indexes; determining weights and scores of the indexes in multiple dimensions such as identity features and operation capability according to the correlation, forming a scoring rule, and calculating the score of each dimension; and carrying out weighted summation on the dimension scores to obtain a total risk score, and dividing the elevators into different risk grades according to the total elevator total score distribution. According to the elevator risk assessment method, objective, dynamic and efficient assessment of elevator risks is achieved through a data-driven full-process automatic model, and a scientific basis is provided for precise supervision and preventive maintenance.

The invention relates to a risk early warning method of a risk potential energy fusion risk field model based on truck braking temperature rise, which comprises the following steps: S1, acquiring a current vehicle state and an environment state, and calculating to obtain total risk potential energy; s2, judging whether the total risk potential energy is larger than a pre-configured first risk threshold value or not, and if yes, executing the step S3; s3, receiving one or more risk avoiding measures; s4, for any risk avoiding measure, the current vehicle state and the environment state are updated based on the risk avoiding measure, and the difference of the total risk potential energy before and after the risk avoiding measure is executed is calculated; s5, respectively calculating the execution cost of each risk avoiding measure; s6, the risk avoiding measures of which the difference between the total risk potential energy before and after the risk avoiding measures is negative are removed, and the income value of each risk avoiding measure is obtained through calculation; and S7, sorting the risk avoiding measures according to the profit values, and judging and displaying risk levels. Compared with the prior art, the method has the advantages that accurate early warning can be carried out on the brake failure risk caused by brake temperature rise of the truck on the long and large downhill road section, and the like.

The application discloses a kind of interbasin water transfer system risk control methods, comprising: obtaining the inflow scenario data of system to be analyzed, water demand scenario data and preconfigured water transfer scheme set;Water quantity scheduling simulation is carried out based on water transfer scheme set to scenario data, determine the water shortage risk index and water abandonment risk index of each spatial node in system under different schemes;Based on the above two types of risk indicators, the risk response function that the risk level evolves with the relationship of water transfer quantity is fitted;Based on the risk response function, the risk transfer marginal substitution index that the risk replacement efficiency between each spatial node is represented is calculated;The efficient balanced water transfer interval of system is determined in combination with risk transfer marginal substitution index and preconfigured risk space equilibrium criterion.The application can scientifically quantify the risk transfer efficiency of cross spatial unit, realize the double-target collaborative optimization decision of system total risk optimization and risk space equilibrium.

The application discloses an industrial safety management and control system and method based on a risk field and distributed autonomy. It relates to the technical field of industrial safety intelligent control, spatial intelligent modeling and complex system autonomous control, and comprises a multi-source sensing and collecting unit, a spatial risk field construction unit, a risk standardization processing unit, a nonlinear risk coupling calculation unit, a risk potential energy conversion unit, an autonomous evolution control unit, a distributed collaborative stability unit and a real-time incremental calculation and computing power scheduling unit. The application maps multi-source risks to a voxelized spatial domain by constructing a three-dimensional spatial risk field; introduces a nonlinear coupling matrix to describe the enhancement or inhibition relationship between risks, calculates the total risk field; constructs a risk potential energy function, triggers control actions based on the gradient descent control law; determines the system stability through the system total energy function and its time derivative; solidifies parameters and maintains local autonomy when communication is interrupted; and adopts voxel-level incremental updating and dynamic allocation of computing power.

To provide a transaction monitoring system for supporting a business to prevent financial crimes and to comply with different types of laws and regulations.SOLUTION: The computer system derives a total risk score for each of the group of entities based on the risk factors. Each of the risk factors is assigned a risk score. The computer system also detects an entity if the total risk score of the detected entity differs from a criterion derived from the total risk scores of a group of these entities by a predetermined margin. The computer system further assists the user to identify, for the detected entity, at least one transaction resulting in a total risk score that differs from a criterion derived from the total risk scores of the group of entities.SELECTED DRAWING: Figure 2

The invention relates to the technical field of data processing, and discloses a calculation method and system for multi-region risks, and the method comprises the steps: determining the risk value information of each key risk factor based on a to-be-evaluated object which needs to carry out the multi-region risk calculation and the risk value range information corresponding to each key risk factor; determining a local risk probability result corresponding to each key risk factor according to a set local risk probability calculation mode and set risk parameter information and risk value information of the to-be-evaluated object; and setting risk parameter information and a local risk probability result of each key risk factor according to a set overall risk probability calculation mode, and determining an overall risk probability result of the to-be-evaluated object. Therefore, the comprehensiveness and rationality of a calculation mode for multi-region risks can be improved, the risk assessment accuracy, reliability, efficiency and convenience of the to-be-assessed object are improved, and the region safety and stability of the to-be-assessed object are improved.

The invention discloses a navigation mark system safety assessment and early warning method and device and electronic equipment. The method comprises the steps that the position offset risk level, the mooring tension risk level and the environmental load risk level of a navigation mark are acquired; the position offset risk level, the mooring tension risk level and the environmental load risk level serve as input of a Bayesian network, and overall risk level probability information of the navigation mark is output; and sending the total risk level probability information to a user side. According to the application, multi-source risk information can be integrated, and probabilistic evaluation and graded early warning of the navigation mark safety state are realized, so that the safety and reliability of a navigation mark system are effectively improved.

The application relates to the technical field of data processing, and discloses a calculation method and system for multi-region risk, which comprises the following steps: determining risk value information of each key risk factor based on risk value range information corresponding to each key risk factor of a to-be-evaluated object which needs to perform multi-region risk calculation; determining a local risk probability result corresponding to each key risk factor according to a set local risk probability calculation mode, set risk parameter information and risk value information of the to-be-evaluated object; and determining a total risk probability result of the to-be-evaluated object according to a set total risk probability calculation mode, the set risk parameter information and the local risk probability result of each key risk factor. It can be seen that the application can improve the comprehensiveness and rationality of a calculation mode for multi-region risk, and further improve the risk evaluation accuracy and reliability, efficiency and convenience of the to-be-evaluated object, so as to improve the regional safety and stability of the to-be-evaluated object.

The application belongs to the field of safety identification, and discloses a safety identification method and system for an intelligent camera. The method comprises the following steps: generating a two-dimensional grid map containing semantic labels based on a real-time video stream of a construction site and a three-dimensional scene model; detecting and tracking a moving target in the video stream to obtain its continuous trajectory in a world coordinate system; identifying the behavior intention of the moving target by combining the trajectory and the semantic labels of the grid; generating a static risk field based on a static dangerous area, and generating a dynamic risk field of space-time diffusion for a preset risk intention target; obtaining a total risk field by fusing the static and dynamic risk fields, and calculating a real-time personal risk value of a person; and dynamically adjusting a warning threshold in combination with the area type, historical warning information and behavior intention, and generating a warning if the threshold is exceeded. The application accurately identifies intention through multi-dimensional features, filters normal operation to reduce false positives, realizes spatial quantization of risk and individual accurate dynamic measurement, and can balance the sensitivity and accuracy of the warning.

The present application relates to the technical field of risk assessment in automated safety detection, and discloses a construction engineering safety hidden danger detection method and system, comprising the following steps: according to the sensor sensing data definition, selectively determining a set of unexamined key check points which cannot be reached by defining a detection blind area or point-by-point path planning; then, accumulating the basic risk weight thereof, combining the surrounding high-risk operation type and risk exposure time, dynamically generating a quantitative total risk score, and generating a visual risk report and pushing it to a management terminal, wherein the present application couples the simple state description of physical obstruction with the importance of the structural key points and the dynamic influence of external high-risk operation, so as to convert an invisible detection blind area into a quantifiable decision basis which can reflect the risk accumulation process over time, and realizes the leap from physical perception to risk semantics.

The invention provides a tunnel shield construction risk assessment method based on static and dynamic risk factor integration, and belongs to the technical field of tunnel construction, and the method comprises the steps: S1, building an evaluation index system threatening tunnel shield construction safety through the statistics of the occurrence frequency and index types of various risk factors based on a real tunnel construction safety accident case, the evaluation index system comprises static indexes and dynamic indexes; s2, based on PSO-SVM, static risk assessment is realized; s3, realizing dynamic risk assessment based on a matter element extension theory; and S4, calculating a total risk score of the static risk level and the dynamic risk level, calculating a posterior probability under the total risk score based on a Bayesian network, and obtaining a comprehensive risk level according to the posterior probability. According to the scheme, static and dynamic indexes are integrated, and scientificity and effectiveness of tunnel construction risk management are improved.

The present disclosure provides a code evaluation method, which can be applied to the field of information security and testing technology. The method comprises: obtaining change information, level information and developer information of a code to be evaluated; determining a total risk weight of the code to be evaluated according to the change information, the level information and the developer information; determining an evaluation pass threshold of the code to be evaluated according to the total risk weight; and determining a target evaluation result of the code to be evaluated according to the evaluation data of an evaluator obtained and the evaluation pass threshold of the code to be evaluated. The present disclosure also provides a code evaluation device, equipment, storage medium and program product.

The invention relates to the technical field of e-commerce risk control, and discloses an automatic examination and approval method and system for a shopping mall refunding and changing only refund scene, and the method comprises the steps: collecting and preprocessing multi-dimensional data, such as orders, users and application behaviors, related to a refund application; based on a malicious behavior feature library dynamically updated through a K-means clustering algorithm, combining an analytic hierarchy process and objective data to determine a multi-dimensional risk model of a weight, and calculating a total risk score for the application; performing grade judgment on the risk score according to a preset threshold value, and automatically executing an approval decision of passing, rejecting or switching to manual rechecking; and carrying out iterative optimization on the weight of the scoring model through a gradient descent algorithm by taking an artificial review conclusion and subsequent dispute data as feedback. According to the method, malicious refund behaviors can be accurately identified, a novel fraud mode is dynamically adapted, the approval automation rate and accuracy are remarkably improved, and the platform operation risk and the labor cost are reduced.

The present application relates to the technical field of civil aviation operation risk management and control, and particularly relates to a flight full-chain operation situation risk assessment method, comprising the following steps: constructing a full-chain risk event library, determining a trigger time, calculating a peak time, a standard deviation and an amplitude of a Gaussian pulse function, and constructing a Gaussian pulse energy representation model of the full-chain risk event; calculating a link coupling weight and a risk amplification coefficient of a full-chain function resonance analysis-cascading model coupling network; calculating a probability of a risk module entering an abnormal state at the next moment according to the risk amplification coefficient, selecting parameters through Monte Carlo simulation, calculating a total risk energy according to the parameters and the amplified amplitude, identifying a link control priority, and outputting a risk level of each operation stage. The present application realizes accurate representation of full-chain risk events, quantitative calculation of cross-stage coupling effects and accurate identification of high-risk links, and improves the pertinence and effectiveness of flight full-process risk management and control.

The invention belongs to the technical field of research, development and design, and relates to a task program operation risk pre-recognition method and related equipment thereof, and the method comprises the steps: carrying out the statistics of the risk alarm times of all sub-service items in a historical operation log; constructing a program operation risk identification model; identifying all sub-service items involved in the latest task data; inputting into a program operation risk identification model to obtain a total operation risk value; and according to the total running risk value, judging whether alarm processing is carried out on the latest task data or not. According to the method, a program operation risk identification model is constructed by combining a historical operation log of a target task program, so that when latest task data is obtained and before an actual program is operated, a preposition identification mode can be adopted to avoid most service calling failure risks in advance; and particularly, the operation stability and reliability of a multi-service-item joint service program are improved in a financial service or online medical service operation scene with more involved sub-service items.