150 results about "Risk quantification" patented technology

The invention provides a power grid running safety risk quantification method. The method comprises establishing a risk quantification model, wherein the power grid value risk is equal to consequence value*probability value; determining the category of influence factor items required to participate in risk quantification estimation to obtain the weighted value among all influence factor sub-items contained by each screened influence factor item; selecting the corresponding influence factor sub-items from each influence factor items participating in risk quantification estimation, multiplying the selected influence factor sub-items to obtain a probability value, multiplying the probability value by a consequence value to obtain the power grid risk value during the occurring of the dangerous factors of the power grid, and obtaining the power grid grade according to the power grid risk value. By the aid of the method, high risk quantification scientificity and accuracy is provided, and risks can be quantified reasonably to be used as the object measurement basis for guiding actual power generation.

The invention discloses an acquired safety guaranteeing method and the system thereof based on settable information safety objectives, the system is composed of a controllable safety working station, a safety guaranteeing system and a network element management and controlling system, a practical safety objective is composed of multi-layer characteristic vectors of practical safety objectives mapped by a reference safety objective formed by setting a key protection scope and target components and the running state information of a real-time objective detecting network, the conformity assessment is performed, the results of threat and risk measurements and safety situation evaluation are combined, the safety gradual processes of verification, enforcement, prevention and inhabitation are self-adaptively selected, the corresponding risk inhabitation, the transfer of security policy and controlling instructions distributed to the net element management and controlling system are formed, and corresponding controlling measures are actuated; therefore, the task of service application and safety cooperative safety guaranteeing are realized. The acquired safety guaranteeing method and the system have the advantages that the system self adapts to safety gradual dynamic defending and safety and service cooperative guaranteeing of the network, therefore, the false alarm or misreport, the transparency and the sustainability of the safety guaranteeing are solved and improved.

The invention provides a virtual power plant combined heat and power scheduling robust optimization model. A model aggregation unit comprises a distributed generating set, a wind turbine generator set, a photovoltaic set, a combined heat and power (CHP) set, a boiler, electric energy storage, heat energy storage, an electric load and a heat load. Participation of the CHP set in the SRM (Spinning Reserve Market) situation is considered. Aiming at the facing uncertain problem of a virtual power plant (VPP) and resulting risks, robust optimization (RO) is utilized to process uncertainty of the EM electricity price, the SRM electricity price, the wind power capacity, the photovoltaic capacity, the electric load and the heat load, and risk quantification indexes are established, and thus robustness and economical efficiency of a RO model are balanced. The model provided by the invention well solves the existing combined heat and power scheduling optimization model establishment problem of the VPP when participating EM and SRM at the same time, and improves flexibility of decision making, and thus the profit of the VPP is increased. Meanwhile, the introduction of the RO model effectively reduces system risks, and thus the effective reference is provided for a decision maker to select a proper robust factor.

The invention discloses a safety margin risk quantification method. The risk value of the safety margin is quantified by acquiring the assets, threat, vulnerability and the existing safety protection measure information of the safety margin. The method comprises the following steps of: quantifying the asset value through the confidentiality, integrity and available evaluation value of specified assets in the safety margin; quantifying the asset damage possibility by acquiring an attack alarm event suffered by the assets in unit time, the asset vulnerability scanning result and the protection degree of the existing safety protection measures on the assets; calculating the risk quantification value of the assets through the asset value and damage possibility; and calculating the risk quantification value of the safety margin through the calculated risk quantification value of all the assets in the safety margin in the unit time. The system comprises an asset value definition module, a threat detection module, a vulnerability detection module, a safety protection measure definition module, an asset risk quantification module and a safety margin risk quantification module.

The invention relates to the technical field of data processing, particularly relates to data processing of an automobile driving assistance system, and particularly provides a driving data risk quantification method. The method includes collecting air-weather data in a driving process, collecting ground data in the driving process, collecting automobile condition data of the automobile itself, collecting driving data in the driving process, building a driving model by utilizing the air-weather data, the ground data and the automobile condition data of the automobile itself, and performing risk quantification with the driving data in the driving model. The method can acquire data according to needs, thus avoiding data congestion, achieving efficient collection and data processing without data errors, ensuring accuracy of quantification analysis, and reducing unwanted road risks. In addition, safety of the driving data is ensured, interference and damage of lawbreakers such as crackerson automatic drive in pilotless automobiles can be avoided, and the safety coefficient in an unmanned driving state is increased.

An apparatus and method for cyber risk quantification calculated from the likelihood of a cyber-attack on the target enterprise and / or cyber ecosystem based on its security posture. The cyber-attack likelihood can be derived as a probability-based time-to-event (TTE) measure using survivor function analysis. The likelihood probability measure can also be passed to cyber risk frameworks to determine financial impacts of the cyber-attacks. Embodiments of the present invention also relate to an apparatus and method (1) to identify and validate application attack surfaces and protect web applications against business logic-based attacks, sensitive data leakage and privilege escalation attacks; and / or (2) that protects web applications against business logic-based attacks, sensitive data leakage and privilege escalation attacks. This can include implementing an intelligent learning loop using artificial intelligence that creates an ontology-based knowledge base from application request and response sequences. Stochastic probabilistic measures are preferably applied to a knowledge base for predicting malicious user actions in real time.

The present invention relates to a method and a system for an adaptive pattern recognition for psychosis risk modeling with at least the following steps and features: automatically generating a first risk quantification or classification system on the basis of brain images and data mining; automatically generating a second risk quantification or classification system on the basis of genomic and / or metabolomic information and data mining and further processing the first and second risk quantification or classification systems by data mining computing so as to create a meta-level risk quantification data to automatically quantify psychosis risk at the single-subject level. Preferably the first and / or second risk quantification or classification system(s) extract specific surrogate markers by multi-modal data acquisition and / or the surrogate markers are categorized and / or quantified by a multi-axial scoring system. Data can be controlled and outliers can be detected and eliminated preferably by determining cut-off thresholds. More preferably an outlier detection method transfers the brain image into a calibrated image, a segmented image and / or a registered image. Uni-modal data can be further generated and optionally optimized on the basis of the data acquired and one or more similarity and / or dissimilarity between the multi-modal data and the uni-modal data can be quantified.

The invention provides a driver relative risk evaluation method based on benchmark analysis. The driver relative risk evaluation method includes the steps: by installing a GPS data collector on a motor vehicle, obtaining natural driving behavior data of a driver; based on the vehicle operation parameters, extracting key events, and determining dangerous driving behaviors of a driver; classifying the driving behaviors with different danger degrees by adopting a clustering analysis method; and calculating comprehensive risk indexes of the individual drivers relative to other drivers by utilizinga benchmark analysis method, and meanwhile, obtaining dangerous driving behavior weight distribution reflecting individual differences of the drivers. According to the driver relative risk evaluationmethod, the traditional absolute risk is replaced by the relative risk of the driver, so that the absolute risk quantification of various dangerous driving behaviors is avoided. Relative risk evaluation is carried out on dynamic driving behaviors of individual drivers, and technical support can be provided for safe driving intelligent reminding and feedback of the drivers, personalized insuranceevaluation based on the driving behaviors and road traffic safety management.

The invention discloses a high-voltage circuit breaker component maintaining method. The method comprises the following steps: performing module division on a circuit breaker by adopting an FMEA (failure mode and effect analysis) in combination with functions and components of the circuit breaker, establishing a risk assessment index system for a high-voltage circuit breaker component on the basis of risk assessment, and performing weight determining on risk assessment indexes by using an analytic hierarchy process; then establishing an importance level assessment index system for the circuit breaker component by applying risk quantification values of failure modes of a weighted grey relationship analysis model to obtain an importance level index of the circuit breaker component; establishing a two-dimensional relationship model between the failure risk degree and the importance of the component according to importance level indexes and the risk quantification values of the circuit breaker component, and taking the degree of urgency of needing maintaining equipment as an intermediate quantity to finally obtain a standard maintaining sequence value.

The invention discloses a static safety analysis based power grid meteorological disaster risk assessment method. The static safety analysis based power grid meteorological disaster risk assessment method comprises the following steps of analyzing a meteorological disaster (comprising thunder, forest fire, high wind, coating ice and the like) influence range and giving out a meteorological disaster influence device list in combination with power grid GIS (Geographic Information System) information; performing static safety analysis on devices within the meteorological disaster influence range, performing quantitative evaluation on power grid risks through a static safety analysis result and dividing five-level alarm according to risk values. Additionally, the invention also discloses a static safety analysis based power grid meteorological disaster risk assessment device. The static safety analysis based power grid meteorological disaster risk assessment method and device provide accordance for power grid meteorological disaster risk quantification and provide aid decision making for power grid comprehensive disaster prevention.

The invention discloses a supply chain financing platform capable of risk quantification and real-time automatic processing. The platform includes a crediting client module, a core manufacturer module, a monitoring party module, a bank module and a plurality of cameras. The crediting client module, the core manufacturer module, the monitoring party module, and the bank module conduct mutual communication through a network and are connected to a cloud database. The crediting client module, the core manufacturer module, the monitoring party module, and the bank module are separately connected to a camera. The cameras are used for photographing file information.

A system for insurance process management employing an advanced decision platform has been developed. A high speed data retrieval and storage module retrieves insurance related data from a plurality of sources. A predictive analytics module performs predictive analytics functions on normalized insurance related data. A predictive simulation module performs predictive simulation functions on normalized insurance related data. An interactive display module displays results of activity of the predictive analytics module and the predictive simulation module as pre-programmed by analysts of an investigation, and re-display results in ways differing by additional representation programming instructions over the course of a viewing session.

The invention discloses an information system security risk assessment method. The method includes the steps of constructing a threatening behavior model bank, matching calling behaviors recorded in an information system with threatening behaviors in the threatening behavior model bank to obtain decision values of the matched calling behaviors, determining weighted values of the threatening behaviors according to the decision values of the matched calling behaviors, and enabling the weighted values of the threatening behaviors to be combined with a vulnerability weighted value and a remedial measure weighted value to obtain a risk grade. The invention further discloses an information system security risk assessment device. Through the scheme of the information system security risk assessment method and device, security risks of the information system can be measured in multi-dimensional mode, the defects of existing risk evaluation quantification are greatly made up for, the accuracy and credibility of threat evaluation are improved, and the core problem of risk quantification of the information system can be solved; consequently, users can conveniently and objectively know the condition of running risks of the information system, and the risks of the information system can be perceived.

The invention discloses a system accident reserve capacity coordination distribution method based on risk quantization, which belongs to the field of power system safe planning and operation. According to the invention, the accident probability in a region, the system reserve adjustment cost and the system outage loss are considered; consideration is given to the reserve configuration scheme risk quantization evaluation indexes of the system reliability and economy; quantization is carried out on accident reserve configuration and risk caused by insufficient configuration; and the system accident reserve capacity is shared according to the percentage of the accident reserve configuration risk index of each region in the risk index of the whole system. According to the invention, the probability of different accidents is discriminated; different requirements of different loads on the reliability are considered; and compared with the traditional accident reserve capacity distribution method, the system accident reserve capacity coordination distribution method based on risk quantization is more rational and scientific.

The invention relates to a power grid optimization technology, in particular to a risk-considering power grid optimization planning method, which comprises the following steps of: respectively carrying out probability modeling on wind power, photovoltaic output and load to describe the random volatility of the wind power, the photovoltaic output and the load, and proposing charging and dischargingstrategies of energy storage; secondly, taking load reduction minimization as a target, and performing power flow calculation on the power system according to a probability optimal power flow methodbased on Latin hypercube sampling; and finally, analyzing the whole life cycle cost of the planning project, further constructing a power grid two-layer planning model based on an improved whale optimization algorithm, quantifying the risk into risk loss cost, and counting the risk loss cost into a target function. Risk-considering power grid optimization planning is carried out, so that the adaptability of a grid frame planning scheme under a new situation is improved, and the safety risk brought to system operation by uncertain factors is reduced from the source.

The present invention provides a quantitative evaluation method for failure risk of high-risk petroleum and petrochemical equipment, including the following steps: S1: analyzing the risk factors of failure modes in high-risk petroleum and petrochemical equipment to obtain the hierarchical structure of main failure modes; S2: establishing high-risk equipment The fuzzy fault tree analysis model and the fuzzy event tree analysis model of the system; S3: According to the fuzzy fault tree analysis model and the fuzzy event tree analysis model, establish the fuzzy Bow‑tie Model; S4: determine the fault in the fuzzy fault tree and fuzzy event tree analysis model Occurrence probability of each event in ; S5: Fuzzy risk and sensitivity analysis based on fuzzy Bow‑tie Model. Through the present invention, the quantitative evaluation of risk in the case of missing or uncertain data in risk analysis is realized, and the risk coefficient and risk ranking of key events are calculated, which can guide us to take appropriate equipment maintenance and risk control measures, thereby contributing to Enhance the reliability of high-risk equipment and reduce the probability of major risk accidents.

A tax-involved risk assessment method for a real-estate project comprises the following steps: according to the type of a real-estate project to be analyzed, selecting a similar project formation sample set from an existing real-estate cost information base; calculating an average value and a corresponding interval for each cost subject according to cost data in the sample set; comparing the cost subject with the corresponding interval, determining the cost subject as a low risk subject if the subject falls within the interval, and determining the cost subject as a high risk subject if the subject falls outside the interval; and if the local government formulates a cost limitation value and presets it to a forced value, once the cost subject exceeds the preset value, adjusting the risk value to a higher value. A risk quantification method analyzes risks and associates the analyzed risks in combination with the interval, conducts calculation by weight value, assigns values to high and low risks, and compares the risks with a plurality of preset risks areas to obtain an assessment result indicating risk levels.

The invention discloses a security gateway based on intelligent behavior analysis, comprising: a traffic parameter extraction function module for calculating a user network traffic behavior mode parameter through real-time sampling; a user behavior intelligent analysis module; and an application intelligent identification and traffic management and control function module for performing intelligent protocol identification on a mainstream application protocol based on the user behavior intelligent analysis module. The invention further discloses a security protection system, comprising: an intelligent cloud security center, and a security gateway; the centers of the intelligent cloud security center and the security gateway are linked in real time, the security gateway transmits the extracted user network traffic behavior mode parameter in the network to the intelligent cloud security center and executes a defense instruction issued by the intelligent cloud security center in real time,and the intelligent cloud security center performs deep learning and security analysis on the traffic behavior mode parameter, generates the defense instruction based on a risk quantification resultof an abnormal behavior and issues the defense instruction to the security gateway. The security gateway disclosed by the invention is applicable to the security detection of most network traffic, andcan achieve an accuracy rate of more than 80% in actual network test.

The invention relates to an overseas investment risk assessment method and system based on omni-media big data technology. The assessment method comprises the following steps: acquiring the historicalinvestment data of the overseas investment country as a training sample through cloud computing and network crawler method; Normalized the training sample to get the historical risk quantification index; According to the quantitative index of historical risk, the risk prediction model is established. Monitoring current venture capital data in countries to be invested; Normalizing the current riskinvestment data to obtain a current risk quantitative index; Determining an investment risk situation in the country to be invested based on the risk prediction model and the current risk quantitative index. The invention can comprehensively obtain the historical investment data of the overseas investment country, obtain the historical risk quantitative index, further establish a risk predictionmodule, monitor the current risk investment data of the country to be invested in real time, thereby determining the investment risk situation of the country to be invested, and improving the accuracyof the investment.

The invention belongs to the technical field of big data applications, and discloses a system and method for the quantitative analysis of a foreign exchange investment risk through big data, so as toestimate the maximum risk loss values of different foreign exchanges at different settlement moments under the normal dynamic fluctuation of a market, and to provide the maximum risk loss values for an enterprise as a visual reference. The method comprises the steps: a, inputting the system data of the lowermost foreign exchange services, the third-side website data and a part of manual operationdata into a database for storage in different modes; b, carrying out the ETL processing of the foreign exchange service data according to data requirements proposed by a model; c, carrying out the correlated storage of the collected original data and the processed data; d, building a model according to the processed data, finally outputting a big data foreign exchange investment VaR risk model through continuous optimization and machine learning, so as to achieve the quantitative measurement of a risk; e, carrying out the graphical visualized display of the measurement result of the foreign exchange investment risk quantification model.

The invention discloses a communication equipment spare part configuration method based on risk quantification control. The method comprises the following steps of S1, according to an experience value, setting an upper limit value and a lower limit value of a probability P(T) of a same model equipment usage quantity which exceeds a spare part stock quantity in a risk assessment period T which can be borne by an existing network; S2, calculating an upper limit value and a lower limit value of a spare part stock quantity m of same model equipment; and S3, according to the upper limit value and the lower limit value of the spare part stock quantity m of the same model equipment, configuring an actual spare part stock quantity of the same model equipment, wherein the upper limit value and the lower limit value are calculated in the S2. In the invention, according to a risk which can be borne by existing network operation, a required spare part warehouse quantity is accurately configured. According the spare part stock quantity of the same model equipment, a probability of the spare part usage quantity exceeding the spare part stock quantity of the same model equipment is calculated so that a risk condition of a current spare part stock quantity is assessed and corresponding changes and adjustments are performed.

The invention provides a risk identification method and device based on transaction behaviors of electricity selling enterprises in an electricity market, and storage equipment, and aims to carry out risk judgment. Complete transaction behaviors are decomposed into a risk module for calculation, a calculation result is compared with a final result of an actual transaction, then a user puts in new transaction information, a default risk evaluation result of an electricity selling enterprise is calculated, and the result is compared with user margin; and in the transaction process, new transaction information is continuously imbedded, and the transaction is automatically suspended when the risk evaluation result is higher than the margin of the user. According to the technical scheme, the risk quantification total value for the transaction behavior of the electricity selling enterprise is obtained in a two-dimensional accumulation mode, the risk quantification total value is finally expressed in the form of the actual amount, and comparison is carried out with the actual margin according to the calculated value. The setting range of the margin is confirmed very scientifically.

The present invention provides a satellite network coordination risk quantification assessment method and system. The method comprises: receiving a frequency track assessment demand input by a user to generate a risk assessment task; obtaining basic data of a pre-stored satellite application environment and a satellite network coordination environment; screening the basic data according to the frequency track assessment demand to obtain the basic data participating in assessment; receiving external data input by the user according to an electromagnetic compatibility environment to complete the basic data participating in assessment; receiving an assessment index system through user input configuration; and according to the completed assessment index system and the basic data participating in assessment, constructing a flexible assessment model to perform assessment of dynamically arranged flexible assessment index system, integrate the assessment value of each assessment index and calculate and obtain a total assessment result. The satellite network coordination risk quantification assessment method and system can perform quantification assessment of the satellite network coordination risk to obtain a frequency track scheme having competitiveness so as to improve the efficiency of satellite network frequency track report and coordination.

The invention provides a substation operation risk assessment method considering the time-varying state of electrical main equipment, and the method comprises the steps: obtaining the state score of each part in the electrical main equipment according to the layering and grading of a fault tree, determining the weight coefficient of each part through an analytic hierarchy process, and solving thefuzzy comprehensive evaluation result of each electrical main equipment, carrying out electrical main equipment state classification; considering the influence of the state of the electrical main equipment and the weather condition on the fault probability, solving the fault probability of the electrical main equipment in the current time period; by adopting a Monte Carlo method, determining the normal operation or fault shutdown state of the main equipment, and evaluating the short-time operation risk index of the transformer substation by taking the connectivity between the power inlet wireof the transformer substation and a load point as a risk quantification index; and if the short-time operation risk index of the transformer substation meets the preset condition, sending early warning information. According to the method, preventive measures can be taken in advance, the influence of accidental faults and weather disasters on the transformer substation is reduced, and the operation reliability level of the transformer substation is improved.

The invention discloses a safety production early warning system and method. The system comprises a production equipment measurement module, a safety equipment monitoring module, a processing analysis module, an evaluation index module, a risk model database, an early warning information platform and a monitoring room. According to the scheme, the data and the image of the equipment during normal production are pre-stored in the risk model database, and the score of the equipment is preset according to the importance degree of the equipment, so that the real-time data and the image in actual safety production can be conveniently compared and analyzed, and the operation conditions of the production line and each piece of equipment can be timely judged; therefore, timely alarm and early warning of different degrees can be made, and a powerful guarantee is provided for safe production. Meanwhile, according to the scheme, the risk factors in the actual safety production process can be subjected to identification analysis, risk quantification and risk alarm prompting through the safety production early warning system, and in this way, type identification and grade quantification processing can be conducted on the actual risk factors.

The invention discloses a power grid dispatching operation process risk auxiliary pre-control system which comprises a man-machine interaction module, a core computing module and a database module. The core computing module is connected with the man-machine interaction module, the database module and an external system. The database module is connected with the external system. The core computing modules comprises a risk assessment module and a risk practical module. The risk assessment module further comprises a risk assessment auxiliary module and a risk computing module. The risk assessment auxiliary module further comprises an interface management module, an individual order operation sequence generation module and a power grid risk status generation module. The risk assessment module further comprises a risk quantification module and a risk level classification module. According to the invention, intelligent dispatching process risk quantification is realized; and based on risk quantification values, dispatching bill risk verification, dispatching simulation billing risk assessment rehearsal, optimum dispatching time selecting, optimal dispatching scheme selecting and other risk auxiliary pre-control functions are realized.

The invention provides a fault probability calculation method of secondary electric power equipment. The fault probability calculation method of the secondary electric power equipment comprises the following steps of obtaining the quantification value of the operation state of the secondary equipment; obtaining the fault probability of equipment with different state grades; and performing correlation fitting on the quantification value of the operation state of the equipment and the fault probability by a least square method. The invention provides a fault probability resolving method based on secondary equipment state evaluation; and on the basis of completing a state parameter model, a correlation curve of the operation state and the fault probability is fit by the least square method. The method has the advantages that the on-site and historical operation records can be sufficiently used; the fault probability of the secondary equipment is measured and calculated according to the mathematical law; and the data support is provided for the risk quantification evaluation of the secondary equipment.

Simultaneous, real-time, multi-option loan pricing and adjudication for automobile consumers is described herein. Through risk-quantification and pricing technology, auto loan contracts are generated on an entire vehicle set of any size for a consumer. Relevant predictive data is obtained about the shopper from credit bureaus, social media, public record, click-thru data, or the like. Based on data retrieved from physical and virtual vehicle lots and personal data of the consumer, a vehicle set of relevant options is provided to the consumer for selection.

The invention discloses a method for evaluating the risk of a clinical test, and the method comprises the steps: dividing collected data into two types, i.e., key data related to the safety of a subject and data quality data, and carrying out the risk evaluation of a hospital where the clinical test participates. According to the method of the invention, various clinical test data can be combinedand then subjected to risk quantification to obtain clinical test safety risk sub-item index data, data quality risk sub-item index data and risk index data of clinical test participation hospitals, and human resources are allocated and monitored according to clinical test risk levels to accurately enter the clinical test participation hospitals. And on the basis of the specific safety risk sub-item index data and the data quality risk sub-item index data, the risk degree of each formed data index is monitored, corresponding monitoring work is executed to achieve the purpose of controlling theclinical test in real time, the rights and interests of the testee are maintained, and the clinical test quality is improved.

A system for insurance process management employing an advanced insurance management platform has been developed. A high speed data retrieval and storage module retrieves insurance related data from a plurality of sources. A data analysis module determines an activeness metric for an object, such as a physical asset, in order to categorize risk and also receives a plurality of individual, entity, and object data to create one or more cognitive maps which may analyzed to determine a propensity for risk. The data analysis module generates a cognitive density metric based on the activeness metric and cognitive map. A predictive analytics module performs predictive analytics functions on normalized insurance related data and using the cognitive density metric. A predictive simulation module performs predictive simulation functions on normalized insurance related data. As a result, the system can produce various models to determine risk and loss associated with an insured physical asset.