44 results about "Risk Estimate" patented technology

In an embodiment of this invention, a diagnosis engine refers to a risk assessment DB and anti-risk measure DB, calculates along the time sequence a risk estimate amount in case of failure for each device and a maintenance cost in executing a measure method in advance, and adds the risk estimate amount and maintenance cost along the time sequence to calculate an optimum maintenance period of the device. When a failure has occurred in the device, the diagnosis engine refers to a failure diagnosis DB on the basis of the identification information of the device and the failure mode and analyzes, on the basis of an operation record, a failure which is different from a secular change.

An electric-power-generating-facility operation management support system includes a condition-input unit inputting costs of electric power generation in electric power generating facilities, probability distribution of predicted values of the demand for electric power, and probability distribution of predicted values of the transaction price of power on the market. An optimal-operational-condition calculating unit calculates the performance of power generation of the power generating facilities based upon the costs of power generation, the probability distribution of predicted values of the demand for power and the probability distribution of predicted values of the transaction price of power on the market, input from the condition-input unit so as to obtain the optimal operational conditions which exhibit the maximum performance of power generation A risk estimating unit calculates and estimates a risk value of damage of the optimal operation under the optimal operational conditions. A calculation-result display unit displays the optimal operational conditions and the risk-estimation results.

According to one aspect, transaction information is received and applied to multiple fraud risk mathematical models that each produce a respective raw score, which are transformed with respective sigmoidal transform functions to produce optimized likelihood of fraud risk estimates to provide to a merchant. In one embodiment, the respective fraud risk estimates are combined using fusion proportions that are associated with the respective risk estimates, producing a single point risk estimate, which is transformed with a sigmoidal function to produce an optimized single point risk estimate for the transaction. The sigmoidal functions are derived to approximate a relationship between risk estimates produced by fraud risk detection models and a percentage of transactions associated with respective risk estimates, where the relationship is represented in terms of real-world distributions of fraudulent transaction and non-fraudulent transaction. One embodiment is directed to computing respective risk test penalties for multiple risk tests in one or more of the multiple fraud risk mathematical models used to estimate the likelihood of fraud, given a certain pattern of events represented by the transaction information, wherein the respective risk test penalties are computed as the inverse of the sum of one and a false positive ratio for the respective risk test.

A system and apparatus generates trading algorithms as data feeds. These data feeds are derived from market data feeds from electronic trading platforms. Functions of invention include the generation of the feeds as market microstructure analytics, trading algorithm building blocks, market behavior and risk estimates that are synchronized with underlying market data feeds. The invention incorporates utilities for agent-driven simulation of multiple electronic markets, and real-time testing and calibration of trading strategies. By delivering critical market dynamics that have not been available so far to market participants, the invention is projected to cut the cost of designing, implementing, and validating trading strategies while also increasing trading performance significantly. The invention will have an equalizing effect on trading by enabling retail investors to remain competitive with high speed traders. This equalizing effect will complement many trading platforms' initiatives for attracting retail flow to enhance their trading volumes and liquidity quality.

Transaction information is received and applied to multiple fraud risk mathematical models that each produce a respective raw score, which are transformed with respective sigmoidal transform functions to produce optimized likelihood of fraud risk estimates to provide to a merchant. Respective fraud risk estimates are combined using fusion proportions associated with the respective risk estimates, producing a single point risk estimate, which is transformed with a sigmoidal function to produce an optimized single point risk estimate. The sigmoidal functions approximate a relationship between risk estimates produced by fraud risk detection models and a percentage of transactions associated with respective risk estimates; the relationship is represented in terms of real-world distributions of fraudulent and non-fraudulent transaction.

Methods and systems for estimating fetal weight at birth and risk of macrosomia are disclosed. Information regarding maternal characteristics and ultrasound measurements are obtained for the fetus. A computer program selects the most accurate equation from a hierarchy of birth weight / risk of macrosomia estimation equations based on the available information. Program outputs include estimated birth weight, risk of macrosomia, and confidence intervals.

The invention relates to a typhoon disaster risk estimate method. The method includes performing statistics and analysis on loss data caused by a typhoon disaster in a specified monitored area, selecting disaster-inducing risk, disaster-formative environment sensitivity, disaster-affected body vulnerability and disaster preventing and reducing capacity to build a typhoon disaster risk estimate index system, building a typhoon disaster risk estimate model with the theory of fuzzy transformation, taking typhoon estimate results as start conditions and input conditions of the estimate model, and judging whether the estimated area is induced a typhoon disaster or not in a future period of time and determining a disaster-inducing risk level through calculating and analyzing of the estimate model. Accordingly, early-warning capability of meteorological disasters is improved by the typhoon disaster risk estimate method.

An apparatus is disclosed for managing the joint contribution of noise exposure of the ear of a user of the apparatus from a loudspeaker of the apparatus as well as from ambient noise so that the risk of risk of noise induced hearing losses is reduced. By assessing the joint actual sound energy delivered to the ear and feeding said assessment to a model describing the accumulated risk of hearing loss due to said sound energy accumulated over a time period, an estimate of the current risk of hearing loss is obtained. When said risk estimate passes a predetermined threshold, one or more protective measures are taken.

The invention discloses a CEEMD and wavelet packet-based ultrasonic signal denoising method. The method comprises the steps of firstly performing mode decomposition on a signal by utilizing a CEEMD algorithm to obtain a series of intrinsic mode functions and a trend term; secondly performing soft threshold denoising on noise dominant modes in the intrinsic mode functions, and performing adaptive rule denoising of an unbiased risk estimate principle for signal dominant modes; and finally further denoising the signal by utilizing a fine decomposition capability of wavelet packet analysis. According to the CEEMD algorithm, two opposite white noises are added to an original signal, EMD is performed and results are averaged; the end effect and the mode aliasing problem can be effectively eliminated; and the signal is further denoised under the condition of not adding auxiliary noises through wavelet and wavelet packet decomposition. The denoising method has better performance in comparisonwith that of a conventional denoising method. The denoising method can be widely applied to the material defect signal processing.

In an embodiment of this invention, a diagnosis engine refers to a risk assessment DB and anti-risk measure DB, calculates along the time sequence a risk estimate amount in case of failure for each device and a maintenance cost in executing a measure method in advance, and adds the risk estimate amount and maintenance cost along the time sequence to calculate an optimum maintenance period of the device. When a failure has occurred in the device, the diagnosis engine refers to a failure diagnosis DB on the basis of the identification information of the device and the failure mode and analyzes, on the basis of an operation record, a failure which is different from a secular change.

During a drilling operation, measured data from the drilling operation may be received with a panistic inversion and risk estimate module. The panistic inversion and risk estimate module may generate a plurality of mathematical solutions from a panistic inversion that uses the measured data and one or more earth models. The one or more earth models having various parameters may be selected prior to drilling and / or while the drilling operation occurs. For each solution of the plurality of mathematical solutions generated from the panistic inversion, the panistic inversion and risk estimate module may determine if the measured data exceeds one or more probability risk thresholds associated with the drilling operation. If the measured data exceeds the probability risk threshold associated with the drilling operation, then the panistic inversion and risk estimate module may generate an alert.

The invention discloses a watershed water ecological security monitoring pre-warning platform and a watershed water ecological security monitoring pre-warning method, and relates to the field of watershed water ecological security. The watershed water ecological security monitoring pre-warning platform comprises a data monitoring module, an information preprocessing module, an index system managing module, a model managing module, a water ecological comprehensive evaluating module, a risk estimating pre-warning module and a risk plan managing module which are in single-direction communication connection in sequence. The watershed water ecological security monitoring pre-warning platform and the watershed water ecological security monitoring pre-warning method disclosed by the invention can be used for solving the problems that the existing watershed monitoring method is low in efficiency, poor in instantaneity and incapable of adapting to the monitoring and pre-warning requirements of the existing water quality.

Collected trial data is weighted to, for example, reflect the relevance of the data. A weighted confidence interval determination and application process described herein determines a confidence interval used to interpret the data. The confidence interval is derived by adjusting the sample size N to account for the impact of weighting when determining confidence intervals. The sample size N is adjusted in a downward trend to avoid overestimating the confidence interval. Lower and upper bounds of the confidence interval are determined using weight influenced variables. Thus, interpretation of weighted trial data, such as product demand data, can be achieved and acted upon with an accurate estimation of risk.

A risk estimating system of network intrusion event comprises engine module for carrying out effectiveness analyzing filter and risk estimating calculation to intrusion event according to set condition , controlling and managing unit of engine module , display and report module of risk estimation result on intrusion event .

Apparatus for testing a conducted energy weapon includes analyzer means to produce characteristic signals representative of characteristics of electrical current pulses delivered by the weapon into a resistive load when the weapon is discharged. Risk estimation means responsive to the characteristic signals produces a risk estimate representative of a risk of injury to a targeted subject due to electrical stimulation, or alternatively representative of a risk of failure to incapacitate the targeted subject. Indicator means responsive to the risk estimate indicates the risk of injury, or alternatively the risk of failure to incapacitate, and warns the user of the apparatus when the risk exceeds a predetermined threshold. Advantageously, automatic testing and risk analysis provided by the apparatus allows weapon tests to be easily and routinely conducted by persons having no knowledge of electrical principles, laboratory techniques, or risk analysis methodologies, such persons including peace officers or other individuals who may be associated with a law enforcement agency.

Apparatus for testing a conducted energy weapon includes analyzer to produce characteristic signals representative of characteristics of electrical current pulses delivered by the weapon into a resistive load when the weapon is discharged. Risk estimation device responsive to the characteristic signals produces a risk estimate representative of a risk of injury to a targeted subject due to electrical stimulation, or alternatively representative of a risk of failure to incapacitate the targeted subject. Indicator device responsive to the risk estimate indicates the risk of injury, or alternatively the risk of failure to incapacitate, and warns the user of the apparatus when the risk exceeds a predetermined threshold.

A method for creating a risk estimate for a tool includes creating a plurality of source patterns from tool data and maintenance data related to a plurality of tools. The method also includes creating a risk model from the plurality of source patterns, the risk model including a plurality of example stressors each having an associated risk value. The method also includes creating at least one stress pattern from tool data related to the tool and comparing the at least one stress pattern to the risk model to create a risk estimate for the tool.

The invention discloses a regional debris flow disaster risk assessment method which comprises the following steps: a regional debris flow disaster risk assessment model is called; a risk assessment plug-in is created according to the regional debris flow disaster risk assessment model; at least one disaster-gestating factor and at least one disaster-inducing factor of at least one debris flow disaster site in a region of interest acquired from different data sources are input to the risk assessment plug-in, and at least one disaster-bearing body vulnerability evaluation factor is also input to the risk assessment plug-in. The risk assessment plug-in is used for executing the following operations that a debris flow disaster sensibility index is calculated based on at least one disaster-gestating factor, a debris flow disaster danger index is calculated based on the debris flow disaster sensibility index and at least one disaster-inducing factor, a debris flow disaster vulnerability index is calculated based on at least one disaster-bearing body vulnerability evaluation factor, a debris flow disaster risk index is calculated based on the debris flow disaster danger index and the debris flow disaster vulnerability index, and a debris flow disaster risk is assessed according to the calculated debris flow disaster risk index.

The invention provides a method and a system for evaluating the integrity of a foundation enhancement system. The method for evaluating integrity of foundation enhancement system comprises the following steps: acquiring a positioning error time sequence and a protection level time sequence and acquiring corresponding safety factor samples; acquiring a core distribution mean value, a core distribution standard deviation and a core distribution model according to the safety factor samples; acquiring a threshold parameter and the position parameter of a GP tail distribution model according to the core distribution model and a preset GP tail distribution model; acquiring a superthreshold sample set according to the position parameter of the GP tail distribution model; resampling the superthreshold sample set by use of a BootStrap method and acquiring a self-service sample set; then performing estimation treatment on each sample in the self-service sample set by use of a maximum likelihood estimation method so as to acquire distribution of shape parameters in the GP tail distribution model and distribution of scale parameters in the GP tail distribution model; acquiring a mean value of risk estimated values and taking the mean value of the risk estimated values as the integrity evaluation value.

The present invention discloses a Down's syndrome risk assessment method for prenatal screening in pregnant metaphase, which includes the following steps: 1) collecting serological index testing results of pregnant women who meet the requirement of age, gestation age and weight; 2) determining gestation ages; 3) determining a median of a serological index of normal pregnant women of each of pregnancy days to obtain a regression formula of the median of the serological index of the normal pregnant women of each of pregnancy days relative to pregnancy days; 4) determining a multiple of the median of the tested pregnant women; 5) adjusting the multiple of the median of the tested pregnant women by the regression formula; 6) establishing a coefficient of a risk assessment formula of Down's syndrome by Logistic regression; 7) establishing the risk assessment formula of a triple test scheme and a double test scheme of Down's syndrome. The method based on pregnancy days and applied to prenatal screening aims at Chinese pregnant women, and has high positive rate and low false positive.

The risk analysis system according to the present invention includes: a storage apparatus which stores subject data including information related to health of a subject; an analyzer which analyzes a risk related to the health of the subject based on the subject data acquired from the storage apparatus; and an output apparatus which outputs an analysis result by the analyzer. The analyzer has: a risk estimating unit which estimates an event onset risk of the subject based on the subject data; and a medical expense predicting unit which predicts future medical expenses, which are medical expenses to be incurred in the future by the subject, based on the event onset risk estimated by the risk estimating unit and the subject data.

A method of genetic screening and analysis, particularly for prenatal genetic screening to determine a risk estimate or probability of genetic disorders for a specific pregnancy integrating a patient's family history data (r1) with a patient's biological test data (r2p) to generate a final prenatal risk factor (Rf). A comprehensive risk factor (CRf) is generated by running a multiplicity of tests on the Rf for screening various genetic disorders.

A brain tumor keyhole operation path planning method based on image guidance comprises the following steps: (1) acquiring a T1 and dMRI tumor segmentation data set, and registering an image sequence to the same coordinate space system after preprocessing; 2) using the training sample to realize accurate positioning of important functional regions of brain tumors, blood vessels and ventricles through a 3D convolutional network, and taking the segmented tumor centroid as an end point of surgical path planning; 3) establishing operation path risk estimation of voxels; 4) establishing risk estimation of each operation path through voxel risk estimation and operation path length constraint; 5) through spatial search, selecting five paths with the minimum risk from the surgical paths as candidate paths, and taking the path with the minimum risk as a planned path; 6) normalizing risk values, and establishing surgical path risk map through color coding. According to the brain tumor resection keyhole operation path planning method, the dependence of brain tumor resection keyhole operation path planning on doctors is reduced, and the track optimality is guaranteed.

The invention belongs to the technical field of traffic safety, and relates to a driver violation risk estimation method based on a duration model, which comprises the following steps: A, constructinga driver violation interval time sample database; B, estimating overall distribution of driver violation interval time; C, fitting a violation interval time duration model, and estimating a regression parameter of the calibration duration model; D, estimating the cumulative survival rate of the driver violation interval time; And E, estimating the risk of violation of the driver. According to themethod, deleting data is considered, and driver violation interval time distribution is estimated more accurately. Identifying significant influence factors of the violation behavior, and estimatingthe violation risk probability of the driver in a future period of time. Therefore, violation early warning prompt is provided for the driver, the possibility of violation and accident events of the driver is reduced, and the road traffic safety is improved.

Construction of factor risk models that more advantageously predict the future volatility of returns of a portfolio of securities such as stocks, bonds, or the like is addressed. More specifically, factor risk models with more than one estimate of specific risk or, alternatively an original specific risk estimate together with a set of specific risk differences derived from more than one estimate of specific risk.

During a drilling operation, measured data from the drilling operation may be received with a panistic inversion and risk estimate module. The panistic inversion and risk estimate module may generate a plurality of mathematical solutions from a panistic inversion that uses the measured data and one or more earth models. The one or more earth models having various parameters may be selected prior to drilling and / or while the drilling operation occurs. For each solution of the plurality of mathematical solutions generated from the panistic inversion, the panistic inversion and risk estimate module may determine if the measured data exceeds one or more probability risk thresholds associated with the drilling operation. If the measured data exceeds the probability risk threshold associated with the drilling operation, then the panistic inversion and risk estimate module may generate an alert.

The invention discloses a multi-stage series-parallel risk management method, which comprises the steps of constructing a first-stage risk assessment model, the first-stage risk assessment model beingcomposed of a first risk assessment layer and a second risk assessment layer, and the first risk assessment layer comprising two first-stage risk assessment links; obtaining initial user information,and substituting the initial user information into the first-level risk assessment model to obtain a first-level risk estimated value of the initial user; screening the initial users for the first time according to the first-stage risk estimation value to form medium-stage users; creating a second-level risk assessment model conducting second-level risk assessment on the medium-term users meetingthe second-level risk assessment conditions to obtain a second-level risk estimation value, wherein the second-level risk assessment model comprises three second-level risk assessment links divided according to user types; and carrying out risk processing on the user according to the secondary risk estimation value. Different processing measures are adopted in different stages of pre-loan loan, so that accurate and soft post-loan management early warning is realized, the overall risk level is finally optimized, and the business income of post-loan conversion is increased.

The invention relates to a method for the reclassification of a subject to a more appropriate risk assessment to that obtained using the algorithms for such risk estimation such us but not limited to Framingham, Regicor, Score, Procamor Qrisk based on the presence of different polymorphisms. The invention also relates to a method for determining the risk of suffering a cardiovascular disease by combining the absence or presence of one or more polymorphic markers in a sample from the subject with conventional risk factors for CVD as well as computer-implemented means for carrying out said method.

The invention provides a wind power plant power climbing risk estimating method based on a cloud model. The method includes the steps of S1, dividing risk grades, and generating standard risk cloud through a standard risk cloud model; S2, collecting wind power plant power climbing risk related data according to risk estimating requirements, and preprocessing the collected wind power plant power climbing risk related data; S3, generating risk attribute cloud through a risk attribute cloud reverse generating model; S4, calculating the risk attribute cloud through a comprehensive risk model to obtain comprehensive risk cloud; S5, estimating risks; S6, calculating a current risk value. By means of the wind power plant power climbing risk estimating method, with the aid of a cloud model theory,according to the wind power plant power climbing main characteristic quantity, the cloud model is established, the risk value is determined and the risks are quantitatively analyzed.

The embodiment of the invention provides a driving risk estimation method and device. The driving risk estimation method comprises the following steps: acquiring possible actions of the driving risk estimation device during working; obtaining a driving risk state corresponding to each driving risk type; if the driving risk state change is caused by the action change of the driving risk estimationdevice, determining the corresponding state transition probability; estimating a risk coefficient in the driving process according to the state transition probability, and then determining the total income corresponding to the action executed by the driving risk estimation device in the preset time period according to all risk coefficients estimated in the preset time period; and finally, determining the action of the driving risk estimation device after the estimation according to the risk coefficient and the total income so as to execute the risk estimation work according to the action, thereby improving the income of the estimation action and reducing the resource consumption of the driving risk estimation device while the accuracy of the risk estimation is ensured.