57results about How to "Accurate risk assessment" patented technology

A user device is associated with a dynamic trust score that may be updated as needed, where the trust score and the updates are based on various activities and information associated with the mobile device. The trust score is based on both parameters of the device, such as device type, registered device location, device phone number, device ID, the last time the device has been accessed, etc. and activities the device engages in, such as amount of transactions, dollar amount of transactions, amount of denied requests, amount of approved requests, location of requests, etc. Based on a transaction request from the user device, the trust score and a network reputation score is used to determine an overall trust/fraud score associated with the transaction request.

The invention discloses construction of a chronic disease risk assessment hyperbolic model and a disease predication system applying the chronic disease risk assessment hyperbolic model. A Shandong multi-center health management longitudinal observation queue is constructed according to longitudinal health management data of more than 20 health management centers in Shandong province to study the actions of heredity, environment, individual life style, health intervention factors and the like on the processes of outbreak, development and lapse of a major chronic disease, the risk assessment hyperbolic model suitable for various chronic diseases for health examination people of Shandong province and the disease predication system are established, and the scientific evidences are provided for the health intervention of the chronic diseases.

The invention relates to the field of network information security, and aims to provide a user risk assessment and analysis method based on a multi-dimensional behavior model. The user risk assessmentand analysis method based on the multi-dimensional behavior model can evaluate the user risk of an application with a log. Users are acquired by a product log; behavior features of the users are searched; behavior data form sample data; a cluster of normal behaviors is obtained by birch; lastly, normal behavior probability distribution of the user is obtained through a mixed Gauss model; and thenBayesian linear regression is adopted to obtain a linear model capable of accurately generalizing normal behaviors of the users. Through adoption of the method, risk assessment can be performed on online user states accurately, efficiently and intelligently.

The invention relates to an enterprise risk assessment method and device, a computer device and a storage medium, and belongs to the technical field of risk assessment. The method comprises the following steps: obtaining corresponding enterprise clusters according to a plurality of enterprises; determining a risk assessment value of the enterprise cluster; wherein the risk assessment value is determined according to the characteristic index of the enterprise cluster; wherein the characteristic index is determined according to operation data of the enterprise cluster; and determining risk assessment results of the plurality of enterprises according to the risk assessment values. According to the technical scheme, the problem that the enterprise risk assessment accuracy is not high enough issolved. Risk association relationships among the enterprises are fully considered, and risk assessment results can be quantized through determination of the risk assessment values, so that enterpriserisk assessment is more accurate.

The invention provides a risk assessment method of urban gas pipeline based on a 'five-scale method', belonging to the pipeline risk assessment category. On the basis of summarizing the main factors of pipeline leakage failure, the intermediate events and basic events of pipeline failure are established by fault tree method, and the main factors are further analyzed and identified. Then the fuzzycomprehensive evaluation method is used to evaluate the pipeline risk, in which the weight is calculated by AHP, the traditional 'nine-scale method' is improved to 'five-scale method', and the fuzzy comprehensive relationship matrix is improved, finally the risk level of urban gas pipeline accident is obtained. The improved fuzzy comprehensive rating method not only can fully reflect the objectivity of evaluation factors and evaluation process, but also is more practical and reliable than the traditional fault tree method and the single fuzzy comprehensive evaluation method, and solves the problem that the factors in the risk assessment are not objective enough, so as to achieve a more accurate risk assessment of urban gas pipelines.

The invention provides a fire control risk assessment method based on a single building. The fire control risk assessment method comprises the following steps: establishing a high-rise building fire risk assessment index system; adopting a fuzzy analytic hierarchy process to form a multi-level analysis structure model according to the mutual relation and the membership relation of the first-levelindexes and the second-level indexes and different levels of aggregation and combination; performing quantitative processing according to the relative importance of the secondary indexes scored to each level by experts so as to determine weight coefficients; constructing a judgment matrix A; calculating the weight of each index according to the judgment matrix A; and carrying out consistency checkon the judgment matrix A, calculating a consistency ratio, giving an evaluation result when the consistency ratio is smaller than 0.1, and otherwise, correcting the judgment matrix A again. Accordingto the fire control risk assessment method, under the condition of fully considering various effective resources, the risk assessment of the building is more objective, fair and accurate, and meanwhile, the urban building control and risk resistance capabilities are improved by utilizing a technical means.

The invention describes a risk assessment system based on situation awareness alarm, and the system comprises: an asset assessment module which carries out the recognition of the types of target assets of a target information system, carries out the assessment and assignment of the target assets, and obtains the value score of the target assets; a vulnerability assessment module which is used forchecking vulnerabilities and configuration items involved in target assets of the target information system to obtain vulnerability risk values and configuration item vulnerability values so as to obtain vulnerability scores; a threat evaluation module which is used for identifying and evaluating the threat faced by the target asset based on the situation awareness alarm so as to obtain a threat severity score; and a risk assessment module which is used for obtaining a risk value of the target asset based on the value score, the vulnerability score and the threat severity score so as to obtaina risk level of the target asset of the target information system. Therefore, efficient and accurate risk assessment can be performed on the target assets of the target information system.

The invention discloses an in-vehicle high-temperature protection system and a method thereof. The in-vehicle high-temperature protection system mainly consists of a vehicle state detection system, anin-vehicle personnel detection system, a high-temperature protection controller, an independent power supply, a high-temperature alarm system and a high-temperature emergency protection system. The in-vehicle high-temperature protection system is characterized in that relevant parameters of an in-vehicle environment are detected through the vehicle state detection system, whether personnel existsin a vehicle is detected through the in-vehicle personnel detection system, energy supply uncontrolled by a power switch of the vehicle is provided through the independent power supply, logical operation is carried out on a detection result through the high-temperature protection controller, identified crises are alarmed through the high-temperature alarm system, and emergency protection is carried out on the in-vehicle personnel through the high-temperature emergency protection system. The detection accuracy of a sensor is improved by adopting multi-mode redundancy detection, and potential danger when the in-vehicle personnel is stranded can be warned and eliminated reliably. When the condition that the in-vehicle personnel is stranded occurs really, the life safety of the in-vehicle personnel can be effectively protected, and meanwhile, the safety of in-vehicle property is ensured.

The invention provides a power transformer time-varying outage risk assessment method considering weather factors. The method comprises the following steps: S1, establishing a comprehensive meteorological risk index system influencing the operation state of the power transformer; S2, according to the aging failure probability and accidental failure probability of the power transformer, obtaining the comprehensive time-varying operation failure probability of the power transformer; S3,using synthetic meteorological risk index to modify the synthetic time-varying operation failure probability ofthe power transformer, and obtaining the time-varying outage risk assessment model of the power transformer considering weather factors. According to the power transformer time-varying outage risk assessment method of the present invention, the meteorological factors which have great influence on the stable operation of transformer are quantified, and the fault outage model of transformer considering normal aging and accidental fault is optimized by using the synthesized meteorological risk index, and the time-varying outage risk model considering weather factors is obtained to make the riskassessment of transformer more accurate.

The invention discloses a user risk classification method, apparatus, medium based on machine learning, belonging to the technical field of artificial intelligence. The method comprises the followingsteps: firstly, static characteristic data of a user which is not combined with network behavior and dynamic characteristic data which is combined with network behavior are obtained; Then, inputting the above two kinds of feature data into a pre-trained stochastic forest model after the target feature data is removed and the user risk level is output. Secondly, inputting the feature data after removing the feature data from the above two feature data and the user risk grade output from the stochastic forest model into the pre-trained logistic regression model and then the user risk score is outputted. Finally, classifying users according to the user risk rating output by the stochastic forest model and the user risk rating output by the logistic regression model. The invention classifies the user risk by using the user static characteristic and the dynamic characteristic data through the machine learning model, and effectively improves the accuracy of the risk classification.

The invention discloses a sudden water pollution event risk evaluation method for a water conveyance project. The method comprises the following steps: to begin with, with characteristics of the water conveyance project and characteristics of sudden water pollution events and influence thereof being taken into comprehensive consideration, and based on a DPSIR module, an index system is established, and risk evaluation indexes covering driving force, pressure, state, influence and response five aspects, index grading standard and an index calculation model are provided; a risk evaluation index weight determination method based on an analytic hierarchy process is provided; and finally, overall influence of the sudden water pollution event on the water conveyance project and risk grade are determined through a comprehensive evaluation method. The method and the risk grade evaluation result can effectively judge the influence degree of the sudden water pollution events on the water conveyance project; a more accurate risk evaluation system is established; and the method can provide decision information support for making scientific and effective early warning and preplanning of management personnel of the water conveyance project, and has wide practical prospect.

The embodiment of the invention provides a method for multi-party joint training of a risk assessment model for an IoT machine. The multiple parties comprise a machine end computing node, a merchant end computing node and a payment platform computing node which are used for respectively storing machine privacy data of a plurality of machines, binding merchant privacy data of a plurality of merchants of the plurality of machines and payment privacy data related to the plurality of merchants, and respectively maintaining partial parameters in the risk assessment model. In addition, the payment platform computing node also stores a machine risk tag. According to the method, a machine tool end computing node and a merchant end computing node determine an intermediate computing result based onstored private data and maintained partial parameters, and a payment platform computing node computes the intermediate computing result based on the stored private data, the maintained partial parameters and labels. And then, the three parties provide respective calculated intermediate calculation results based on a secure multi-party calculation MPC technology, determine training loss, and then respectively adjust partial maintained model parameters.

The invention discloses a risk evaluation method based on multi-variety electricity transaction, which comprises the following steps of: firstly, acquiring transaction basic data of various markets; then on the basis of mean-variance risk evaluation, calculating VaR(Value at Risk) values under the electricity transaction by adopting a VaR model method; and finally, comparing the VaR values under the electricity transaction to a transaction portfolio expected return rate, when the transaction portfolio expected return rate is greater than or equal to the VaR values under the electricity transaction, obtaining a result that transaction portfolios are all effective multi-variety power transaction portfolios, and when the transaction portfolio expected return rate is greater than the VaR valueunder the electricity transaction, obtaining a result that the transaction portfolios are optimal transaction portfolios. According to the invention, transaction risks of different electricity markettransaction goods are researched, and on the basis of a mean-variance model of multi-variety electricity transaction portfolios, a VaR constraint is added, so that the transaction risk of a generation company is comprehensively considered.

The invention belongs to the technical field of communication, and particularly relates to a network element equipment performance detection method and device and a computer readable medium. The method comprises the steps that historical communication data of network element equipment is acquired, a risk source is determined according to the historical communication data, and the risk source is a factor influencing the performance of the network element equipment; constructing a risk assessment index system based on the risk source; optimizing a weight and a threshold value in the risk assessment index system to obtain a risk assessment model; inputting the risk assessment index of the network element equipment into the risk assessment model to obtain a risk assessment value; and determining the risk level of the network element equipment according to the risk assessment value. Therefore, the risk assessment index system is constructed through the risk source, and the weight and the threshold value in the risk assessment index system are optimized, so that the risk assessment model which is more consistent with the actual situation can be constructed, the predicted risk assessment value is more accurate, and the risk assessment result is more reliable.

The invention provides an online public opinion risk identification method, which comprises the steps of inputting each piece of text information obtained from a monitoring website into a first classification model, and outputting a first classification result used for representing that the text information is related or unrelated to a target object; according to the first classification result, inputting each piece of target text information related to the target object into a topic model, and outputting topic information expressed by each piece of target text information; and inputting eachpiece of target text information and the theme information of the target text information into a second classification model, and outputting a second classification result used for representing risk information of the target text information. The invention further provides a construction method of the online public opinion risk identification model, an online public opinion risk identification device, a construction device of the online public opinion risk identification model, electronic equipment and a computer readable storage medium.

The invention relates to the technical field of Internet of Things warehouse intelligent management. The invention discloses a pledge subject matter intelligent management monitoring system and methodbased on an Internet of Things block chain. The system comprises a warehouse which is provided with a video monitoring device and is used for storing pledge subject matters, a data monitoring modulearranged at a key asset point of a pledge party, at least three supervision computers/hand-held devices respectively used by the pledge party, a pledgee party and a third supervision party, and a server in data connection with the video monitoring device, the data monitoring module and the supervision computers/hand-held devices and connected to the Internet. The management monitoring method comprises a pledge input step, a pledge supervision step, a pledge supervision step and a supervision monitoring step. The supervising computer/handheld devices for visually accessing monitoring data are provided for the pledge party, the pledgee party and the third supervising party participating in pledge items, and a secret key and key information are uploaded to a block chain to be stored, so thatthe non-modifiability of the data and the traceability of a data source and an access record are ensured.