668 results about "Risk index" patented technology

The invention relates to a method and apparatus for predicting a sudden heart abnormality for an individual patient. In order to provide a prediction mechanism that is suitable for acute care, three sub-indices are determined based on medical data obtained from the patient. The first sub-index indicates the level of deterministic chaos in the heart rate variability of the patient, the second sub-index indicates the energy level in the myocardium of the patient, and the third sub-index indicates the degree of ventricular arrhythmia of the patient. Based on the first, second, and third sub-indices, at least one overall risk index is then determined, the overall risk index indicating the risk level of a sudden heart abnormality for the patient.

The invention provides an electrical equipment state maintenance system. The electrical equipment state maintenance system comprises an operation and maintenance base layer platform, a state monitoring module, a state evaluation module, a risk assessment module, a fault diagnosis module and a maintenance strategy module, wherein production area I data of a power grid system and production area III data of the power grid system are integrated on the operation and maintenance base layer platform, the state monitoring module is used for collecting on-line monitoring data of electrical equipment and operating environment information of the electrical equipment through the operation and maintenance base layer platform, the state evaluation module is used for evaluating the on-line monitoring data according to state evaluation standards of the electrical equipment to acquire an electrical equipment health state represented by the on-line monitoring data, the risk assessment module is used for calculating the risk index of the electrical equipment according to risk assessment standards of the electrical equipment, the fault diagnosis module is used for diagnosing faults of the electrical equipment and generating a fault diagnosis report according to the health state and the risk index of the electrical equipment, and the maintenance strategy module is used for generating maintenance strategy information of the electrical equipment according to the health state, the risk index and the fault diagnosis report of the electrical equipment. By means of the electrical equipment state maintenance system, evaluation, assessment and predication are automatically carried out on the power grid system, and therefore the automation level and the intelligentization level of the power grid system are improved.

A method for assessing a cyber security risk, the method comprising the steps of: obtaining cyber security precursor information from a plurality of sources, wherein the cyber security precursor information can be obtained from one or more online or offline sources; normalizing the obtained cyber security precursor information to a common information model; generating, from the normalized cyber security precursor information, one or more events; producing, from the one or more generated events, one or more facts; calculating a plurality of risk indicators from the one or more facts; normalizing the plurality of risk indicators to a common model; calculating, using the normalized plurality of risk indicators, one or more cyber risk index component scores; and calculating, using the one or more cyber risk index component scores, a cyber risk indicator index.

Methods and systems are provided for evaluating the risk of conducting financial transaction such as money transfers through representatives. In one embodiment, information generated by a money transfer system regarding a plurality of financial transactions conducted by one or more representatives are received, records of the information are stored in a transaction database, a risk processor is configured to access the transaction database and retrieve risk element data related to transactions conducted by the representative and an analysis of the risk element data is performed using the risk processor. The risk processor may be configured to process the risk element data into one or more risk element values and to calculate a Transaction Risk Index for the representative by comparing one or more of the risk element values to an appropriate risk proxy.

The invention discloses a different-scale regional flood damage risk evaluation method. The method comprises: collecting space data of a to-be-analyzed region and attribute data associated with the space data as initial data, compressing the initial data and storing the compressed data in a created space database; standardizing the initial data, and unifying units; coupling a model by utilizing an analytic hierarchy process (AHP) method and an entropy weight method, and determining each factor combination weight; and evaluating and researching a regional flood damage risk value, classifying risk grade, and generating a flood damage risk index diagram. According to the different-scale regional flood damage risk evaluation method, by utilizing the collected natural and social data as input and various algorithm coupling models, the weights are determined, and finally the flood risk grade evaluation index diagram is generated; therefore, the accuracy of flood damage risk evaluation is improved, objective and efficient advantages are achieved, and the flood damage risks, which have possibility of occurring in a research region, under given conditions are further intuitively shown.

A method and apparatus including a mobile device for administering and quantitatively determining a Risk Index that a user has suffered an impairment of brain function.

Improved risk categorization is provided for clinical decision support and forecasting future health care spend. A risk index is provided that improves on other risk stratification models by synthesizing electronic medical records and health questionnaires with an individual patient's claim histories. Machine learning algorithms catalogue patients into distinct group clusters, based on risk which may be associated with annual health care spending, thereby enabling administrators to forecast future health care spending on the individual and population level.

The invention belongs to a risk evaluation method for the operation of a large power grid. The method comprises the following steps of (1) statistics of fault and risk factors; (2) computation of risk probability; (3) risk quantitative evaluation based on the load loss; (4) classification and result evaluation on risk index. According to the risk evaluation method for the operation of the large power grid, the occurring probability of power system accidents and the number of load loss of the system are combined to form a new quantitative index, so a scheduling person can be helped to perform real-time risk evaluation and analysis, can further comprehensively master the safe operation condition of the power grid, and controls the risk level of the system within a reasonable range by adopting necessary measures, and the occurrence of the disaster fault is avoided. The real-time evaluation and management and control on the risk are realized by a power gird scheduling center and the method belongs to a load loss-based risk evaluation method for the operation of the large power grid.

Systems and methods implemented in a cloud node in a cloud based security system for network access control of a mobile device based on multidimensional risk profiling thereof include receiving posture data from the mobile device; determining a device fingerprint and a risk index of the mobile device based on the posture data; and, responsive to a request by the mobile device for network resources through the cloud based security system, performing a multidimensional risk analysis based on the device fingerprint and the risk index and allowing or denying the request based on the multidimensional risk analysis.

The invention discloses a freight transportation safety evaluation model based on a man-vehicle-road-freight multi-risk source. The model is characterized in that a freight transportation safety sensing system is constructed and driver, vehicle, road (environment) and freight information is obtained; a causing factor of a freight vehicle accident is analyzed by using an accident causation theory, attribute sets of four kinds of man, vehicle, road, and freight risk sources are defined, and the attributed sets are analyzed and screened by using an accident tree analysis method; according to the screened attribute sets, a freight transportation safety risk index system is built by using an analytic hierarchy process and weights of the driver, vehicle, road(environment) and freight information factors for accident occurrence are determined; and according to the established integrated freight risk evaluation index system as well as all evaluation index weights, a freight transportation safety risk evaluation model is established by using a fuzzy evaluation theory. Therefore, the technical support for intelligent early warning can be provided for the road freight transportation safety work.

The invention discloses an operation risk evaluation method comprising a wind-power plant electric system. With view to affection on the electric system from a wind-power plant, the operation risk evaluation method traces back to nodes and includes that real-time importance degree weights of the nodes are introduced into risk indexes, affection of a network topology and real-time tide state information is comprehensively reflected, real-time risk variation of the electric system under the action of the wind-power plant can be truly reflected, updating of various state parameters and risk level sequence is completed in real time in a short calculation period of system running risk evaluation, the problem that operating monitoring of power plants or substation busses high in importance degree is ignored is avoided, value-at-risk is converted into a dimensionless utility value by evaluating a function through consequence severity of exponential risk-preferred utility function, the risk-at-value is increased at different degrees so as to increase risk level difference identification degree and differentiation degree under same low-loss-load probability and scientifically compare different risk levels.

The invention provides a method for grading flood risk according to a plurality of space scales. Under each space scale, the method comprises the following steps of: S1, calculating a flood risk index by taking a precipitation amount index, a river-lake index and a terrain index as risk evaluating factors of flood; S2, calculating a vulnerability index after calculating vulnerability evaluating factors of the flood by taking a population density index and an economic GDP (Gross Domestic Product) density index as evaluating factors; and S3, generating a flood risk index by synthesizing the risk index and the vulnerability index, and further grading the flood risk index to generate a flood risk level. The method is implemented in a sequence from larger space scales to smaller space scales. Due to the adoption of the method for grading the flood risk, areas with social and economic damages possibly caused by flood disaster phenomena and risk levels can be analyzed on different space scales, and the monitoring frequency of highly-risky areas is increased.

The invention belongs to the technical field of cloud computing and network safety, and in particular relates to a cloud data center real-time risk assessment method based on mainframe log analysis. The method comprises: providing four risk factors, namely alarm quantity, alarm type, alarm type and alarm threat level, influencing an asset risk index based on an intrusion detection system and a vulnerability scanning tool OSSEC of a mainframe log, and using the four risk factors as evidences for assessing the risk situation of asset, combining evidence theory (D-S theory) with thought of fuzzy mathematics, designing DSFM (D-S Fuzzy Mathematic) algorithm, and combining the evidences to obtain the asset risk index RI; combination of the risk index and asset value is the risk value R of the asset; combination of all asset risk values of one data center is the risk value of the data center. Simulated strike experiment shows that the method can be used for assessing the risk of whole cloud data center system in real time, and the obtained assessing result is high in accuracy.

The invention relates to an anti-fraud identification method and an apparatus for insurance claim settlement, wherein the method comprises: after a claim settlement anti-fraud system receives a claim settlement application with the claim settlement information, determining the type of the claim settlement case corresponding to the claim settlement application; obtaining a pre-trained and generated anti-fraud identification model corresponding to the claim settlement application; obtaining the risk factors for the anti-fraud identification model corresponding to the claim settlement application; obtaining from a booked financial system the risk factor information of the anti-fraud identification model corresponding to the claim settlement application; inputting the risk factor information to the anti-fraud identification model; outputting the risk index value corresponding to the claim settlement application; based on the risk index value and the preset risk processing rules, determining the risk processing manner corresponding to the claim settlement application; and based on the risk processing manner, performing risk processing to the claim settlement application. With the method and the apparatus of the invention, it is possible to quickly process the claim settlement applications in batch, to increase the efficiency of anti-fraud identification, and to identify the hidden fraud risks to the largest extent.

The invention relates to the field of loan risk early warning and discloses a loan risk early warning method and system based on multi-industry data. The obtains user information related to a borrower from a plurality of angles by using multi-industry data; compares the user information with the historical information of the borrower to identify the abnormal behavior of the borrower; and classifies risk events according to abnormal information in an abnormity recognition result, and finally evaluates the loan risk of the borrower according to a preset risk index to determine the loan risk level of the borrower and output a warning report. The method and system can continuous monitor the borrower after the borrower loans by the multi-industry data, and can identify the loan with overdue tendency more accurately and effectively, make corresponding warning, raise the loan recovery rate and reduces the bad assets of credit and loan financial institutions such as the banks or the like.

A server configured to profile a mobile device for a cloud-based system, includes a network interface, a data store, and a processor communicatively coupled to one another; and memory storing computer executable instructions, and in response to execution by the processor, the computer-executable instructions cause the processor to, based on communication to a client application on the mobile device, cause the client application to collect data associated with the mobile device; receive the collected data; and determine a device fingerprint and a risk index for the mobile device based on the collected data, wherein the device fingerprint is utilized to uniquely identify the mobile device and the risk index is utilized to manage the mobile device

The invention discloses a bank credit system risk assessment method and device. When enterprise credit risk assessment is performed, enterprise profit capability and assets and other traditional indexes are examined, and business contact activity between enterprises and the cash flow situation are also comprehensively considered. Mass data are utilized, potential useful new evaluation indexes are mined, and the current new technologies, such as data mining and social networks, are integrated in the assessment process so that accuracy of the assessment result can be enhanced. Therefore, the new indexes are combined with the conventional indexes, and a new enterprise credit risk assessment system is given and applied to a BP algorithm of machine learning so that a concrete and feasible support model is provided for formulation of the risk avoiding scheme of the financial system, and the problems in the prior art that accuracy is low and overall performance is poor due to the fact that only the conventional risk indexes or part of financial phenomena act as the risk assessment method can be solved.