30 results about "Hazard model" patented technology

Systems and processes for more accurate mortgage scoring are described. A proportional hazards model is employed in which not only the occurrence of an event, but also the time to an event such as default of a loan, is considered. In this approach, a hazard rate can be viewed as the chance that an observation will experience an event in the next instant. There are two components to the response, and a binary variable is utilized to indicate whether the event was observed or not, and a time variable. As a result, the number of loans used for modeling is greatly increased, and the time it takes to observe the event, a valuable piece of information in itself, is included in the process. In addition, nonlinear effects are advantageously modeled in a continuous fashion using hat functions to map a series of independent variables. This approach typically yields smaller prediction errors near boundary points.

A multi-operating mode frame type portable landslide testing device for a geomechanical model belongs to the field of geological hazard model test. The testing device comprises a frame-beam-type testing bed, a rainfall simulator, a water level regulator and a self-weight horizontal loading mechanism, wherein the frame-beam-type testing bed mainly comprises a cuboid framework, a front panel, a rear panel and a base plate; the rainfall simulator is arranged at the top of the frame-beam-type testing bed and comprises a plurality of spraying pipes and nozzles on the spraying pipes and is used for simulating rainfall in the frame-beam-type testing bed; the water level regulator comprises a left-side trough and a right-side trough respectively formed on the left and the right sides of the frame-beam-type testing bed, and a plurality of drainage holes are respectively formed on the right panel of the left-side trough and the left panel of the right-side trough and used for changing the water levels of water level simulation libraries in the left-side trough and the right-side trough; and the self-weight horizontal loading mechanism is arranged above the right-side trough and used for bearing weights, so as to exert horizontal load to the landslide model in the frame-beam-type testing bed.

The invention discloses a stomach cancer prognostic marker screening and classifying method based on a gene expression profile. The stomach cancer prognostic marker screening and classifying method comprises that a gene the expression of which is changed is screened out from data of the gene expression profile Cox proportional hazard model analysis is established aiming at the screened gene, a gene which has statistical significance is selected as a seed gene, a maximum likelihood model is constructed by means of clinical follow-up information data of the patient to screen out prognosis key genes, then the risk coefficient of each prognosis key gene in the patient is calculated, classification and statistic verification are carried out in dependence on the number of prognosis key genes of the patient, and an optimal classification mode is selected. According to the invention, dimensionality of high-dimension miscellaneous gene expression profile data can be effectively reduced, several key genes which can be applied to clinical detection easily are screened out from tens of thousands of genes, survival and the recurrence risk of the patient are predicted by means of the expression case of the several key genes.

The invention provides a duodenal adenocarcinoma patient postoperative prognostic prediction system based on a COX proportional hazard model. The system comprises a memory, an information processing module and a prediction result displayer. The information processing module is configured for performing the following calculation and comparing the calculation result with the duodenal adenocarcinomapostoperative prognostic prediction index pre-stored in the memory and outputting the prediction result to the prediction result displayer: (I) the score of each risk factor is calculated according tothe following relation; (II) summation of all the scores obtained in the (I) is performed and the total score Z is calculated; and (III) the three-year survival rate (Y3) or the five-year survival rate (Y5) of the patient is calculated according to the following relation.

The invention relates to a power cable operation maintenance method based on historical fault information and an operating state, wherein the method is used for predicting the residual life of a power cable and formulating a replacement strategy of the power cable. The method comprises the following steps of establishment of a weibull proportional hazard model, solution to parameters in the weibull proportional hazard model, resolving of a power cable state decision curve, prediction of the residual life of the power cable; and formulation of a maintenance and replacement strategy of the power cable. With the method, reasonability and reliability of cable fault prediction are improved; the operating situation of the cable can be displayed visually and clearly; and a reference can be provided for making a decision of cable maintenance and replacement. A minimum cost method and a maximum availability method are brought forward based on the weibull proportional hazard model; and with consideration of economic factors, a proper strategy of cable maintenance and replacement can be formulated.

The invention discloses a method for predicting the service life of a key system of rail transit vehicles. The method comprises the following steps of firstly, determining the key system of urban rail vehicles, and bringing in a proportional hazard model to carry out service life prediction on the key system; secondly, screening historical overhauling data of the key system to obtain concomitant variable factors, and processing concomitant variables by applying a principal component analysis method so as to obtain a concomitant variable matrix; thirdly, solving a parameter estimation value in the proportional hazard model by adopting a maximum likelihood estimation method and a Newton iteration method; finally, calculating the predicted service life of the key system of the rail transit vehicles by utilizing the obtained proportional hazard model. According to the method disclosed by the invention, the influence of the concomitant variable factors on the service life of the key system of the rail transit vehicles is considered, and the defect that the service life prediction is inaccurate as only system failure is considered in traditional service life prediction is overcome.

The invention discloses a method for predicting the residual service life of a wind turbine gearbox bearing. The method is a method for predicting the residual service life of the gearbox bearing based on a competitive improved proportional failure model. The method comprises the following steps: carrying out principal component fusion on temperature and vibration data of a gearbox bearing in a whole life cycle from use to failure to obtain a one-dimensional characteristic quantity so as to reflect the degradation performance of the bearing; and considering the particularity of a wind turbinegenerator gearbox bearing, and establishing a competition failure reliability evaluation model of a Wiener degradation process and Weibull distribution sudden failure by adopting an improved proportional hazard model. Through example analysis, residual life analysis of the degradation failure and burst failure competition model, the irrelevant model and the independent degradation failure and burst failure model is compared, and reliability and optimality of the competition model are verified. The invention provides an effective, practical and high-precision prediction method for analyzing theresidual service life of the wind turbine gearbox bearing.

The invention discloses a system to score assets such as patents based on an event on which information is publicly available and is correlated to a number of intrinsic and extrinsic variables which characterize the assets. More specifically, the invention improves over the prior art by taking due account of yearly life expectancy statistics of patents of the same family in multiple jurisdictions where related patents owned by the same assignee have been filed. For doing so, the system of the invention provides a method to use statistical models of the semi-parametric type such as Cox proportional hazard models or the parametric type, such as Weibull accelerated failure models. These models yield a much improved precise estimation of patents families filed in multiple jurisdictions, the possibility to make available to the users the breakdown of the explanatory power for each relevant variable and validation criteria and the option to choose between different models the one best fitted to their usage scenario.

The invention provides a SKIP mode quickly selecting method based on Bayesian minimum hazard decision. The SKIP mode quickly selecting method based on Bayesian minimum hazard decision comprises the concrete steps of taking the rate-distortion cost of the SKIP mode of a current coding unit as decision features to count and learn first four frames, and for different quantization parameters and different coding unit depths, performing non-parametric probability density estimation to obtain the conditional probability distribution of the decision features in an optimal SKIP mode and an optimal non-SKIP mode; based on the statistical information of online learning, utilizing a Bayesian minimum hazard model to discriminate the SKIP mode of surplus frames in advance. The SKIP mode quickly selecting method based on Bayesian minimum hazard decision can rapidly achieve SKIP mode discrimination under the condition of ensuring the coding performance, thereby skipping predictive coding mode computation, effectively reducing the coding complexity of an HEVC (high efficiency video coding) encoder and facilitating implementation of real-time application of the HEVC encoder.

The invention discloses a fault single influence factor analysis method based on power cable fault information, which mainly comprises two steps of sample size estimation and single influence factor analysis based on a Cox proportional hazard model. Firstly, cable fault data is preprocessed on the basis of a data preprocessing principle to obtain sample data, and sample size is estimated based on the sample data, so as to guarantee the applicability of the sample data. Then, the Cox proportional hazard model is used for carrying out single influence factor analysis on influence factors of cable faults. The fault single influence factor analysis method based on power cable fault information can determine the influence factors of cable faults and influence degree of each influence factor according to cable fault data, so as to guide procurement, construction and maintenance of the cable, and improve the reliability of cable lines as well as operational reliability and stability of a power grid.

The invention discloses a method and system for optimizing maintenance of a mechanical system based on a proportional hazard model. The maintenance method comprises the steps that a proportional hazard model is established; data is collected; analysis processing is conducted on the collected data; statistical processing is conducted on historical lifetime data to obtain correct historical lifetime data; concomitant variables, the correct historical lifetime data and parameters of a Weibull PHM function estimated through a maximum likelihood function are respectively introduced into an established reliability function to obtain the reliability of a testing moment, the reliability is compared with a preset reliability threshold value to calculate maintenance time, and whether the mechanical system needs maintenance or replacement or not is judged according to the maintenance time. By adopting the method, the time for maintenance or replacement of equipment can be accurately calculated, the time for maintenance or replacement of the equipment is accurately calculated, unnecessary economic losses can be avoided, the maintenance time can be shortened, the service life of the equipment can be also prolonged, and the reliability of the equipment can be improved.

An embodiment of the invention relates to a prediction method and a prediction device. The prediction method comprises the steps of: training a Cox proportional hazard model according to acquired historical technical indexes, and acquiring a rising model, a declining model and a covariate; determining a risk function according to the covariate; determining an accumulative risk function according to the risk function; and calculating a probability of future rise and a probability of future decline according to the accumulative risk function, current technical indexes composed of time of previous rise and time of previous decline, the rising model and the declining model, and conducting a transaction based on the probability of future rise and the probability of future decline. Therefore, the prediction method and the prediction device are higher in precision of prediction results, are conductive to helping investors to make the most reasonable decision, increase profits and reduce the risks.

The invention discloses a spectrum contract based multi-user collaboration spectrum sharing method. The market driving based spectrum contract mechanism characteristics are combined to establish a PU (Primary User) and SU (Secondary User) model. The constraint on the selfishness and the individual rationality of the communication of both parties of a contact is considered to propose a spectrum contract framework to balance interests of the both parties so as to establish a multi-user collaboration spectrum sharing contract model under the symmetrical network information condition. The analysis on the moral hazard problem under various hidden action conditions is performed in the contract design process according to the asymmetry of the network information, a moral hazard model under the PU behavior measurable and SU behavior hidden condition, a moral hazard model under the PU behavior hidden and SU behavior measurable condition and a moral hazard model under the PU behavior hidden and SU behavior hidden condition are established, contract parameters are set to motivate the action of the both transaction parties, and accordingly the win-win situation of the interests is implemented and meanwhile the optimization on the network communication performance and the sharing of spectrum resources are ensured.

The invention provides a GIS (Gas Insulated Switchgear) evaluation method which is implemented on a GIS, wherein the GIS comprises a plurality of subsystems and every subsystem comprises a plurality of elements. The GIS evaluation method comprises extracting historical data of the GIS and obtaining the fault rate of every element arranged in the corresponding subsystem according to a proportional hazard model; calculating probability values and evaluation values of every subsystem according to a preset algorithm, wherein the probability values are corresponding to the healthy state, the sub-healthy state and unhealthy state respectively and every probability value is correspondingly combined into the corresponding evaluation value; obtaining the defect and fault state of every subsystem to revise the evaluation values of every subsystem; establishing a bayesian network according to the GIS logical relation; obtaining the conditional probability of the GIS through the bayesian formula according to the bayesian network and the revised evaluation values to determine the system reliability. According to the GIS evaluation method and device, multiple information sources can be integrated, the complexity of the GIS can be combined, the numerical value of the reliability of the GIS can be quantized, and the reliability of the GIS can be accurately and rapidly evaluated.

The invention relates to a VR-based safety hazard checking and eliminating exercise method and system. The problems that in a troubleshooting system, safety hazard prompts are difficult to dynamicallygenerate randomly, and dynamic interaction of a UI and the vivid safety hazard eliminating process are difficult to achieve are effectively solved; according to the technical scheme, the method comprises the steps that 1, a safety hazard checking and eliminating exercise system VR scene is designed and made; 2, a safety hazard model in the safety hazard checking and eliminating exercise system isdesigned and made; 3, VR roles are designed; 4, according to the function and interaction requirements, the VR system UI is designed; 5, a navigation map of different scenes of a VR system is designed and made; 6, hazard points in all scenes of the VR system are designed and made; 7, dynamic random prompts of all the hazard points in the VR system are designed and made; 8, an eliminating means ormethod of the hazard points in the VR system is designed and made; 9, integration is conducted, and a system is obtained. Accordingly, the user can feel safety hazard checking and eliminating in theVR environment, and the safety hazard checking and eliminating skill of the user is increased.

The invention relates to the technical field of geological hazard model test, in particular to a method for monitoring and early warning of landslide thrust based on a stability coefficient. The method comprises the following steps of step one, parameter determination; step two, thrust monitoring; and step three, calculation of the stability coefficient and early warning. Compared with traditionaldetection methods, the method provided by the invention establishes a corresponding relationship between the monitoring data and slope stability by monitoring the landslide thrust to visually and quantitatively display the safety level of the slope, thereby improving applicability and reliability of the monitoring of early warning and forecast of slopes of different types and different states.

The invention provides a wireless state monitoring and maintenance decision system for a numerically-controlled machine tool by a PLC (programmable logic controller). The system comprises a wireless control module and a wireless controlled module; the wireless control module comprises wireless transmitting and receiving modules and a computer, the wireless controlled module comprises wireless transmitting and receiving modules, an information acquisition module, the PLC and a controlled body, namely the machine tool, and the information acquisition module is mainly used for acquiring information of the operating state of each point of the machine tool. Reasonable monitoring is adopted for the machine tool, and on the basis of deep analysis of fault data, a double Weibull proportional hazard model including early fault and random fault is established.

The present invention provides methods, systems and equipment for prognosis or evaluation of treatment of solid tumors. Gene markers that are prognostic of solid tumors can be identified according to the present invention. Each gene marker has altered expression patterns in PBMCs of solid tumor patients following initiation of an anti-cancer treatment, and the magnitudes of these alterations are correlated with clinical outcomes of these patients. In one embodiment, a Cox proportional hazards model is used to determine the correlations between clinical outcomes of RCC patients and gene expression changes in PBMCs of these patients during the course of a CCI-779 treatment. Non-limiting examples of genes identified by the Cox model are depicted in Tables 4A3 4B, 5 A and 5B. These genes can be used as surrogate markers for prognosis of RCC. They can also be used as pharmacogenomic indicators for the efficacy of CCI-779 or other anti-cancer drugs.

A chemical, biological, radiological and nuclear (CBRN) hazard detecting system. In one embodiment, the CBRN hazard detecting system includes a plurality of sensors, a plurality of acoustic sensors, one or more weather sensors and a level 3 fusion engine. The level 3 fusion engine is in communication with the plurality of CBRN sensors, the plurality of acoustic sensors and the one or more weather sensors. Moreover, the level 3 fusion engine is adapted to detect and track CBRN hazards based in part on data received from the CBRN sensors, the acoustic sensors, the one or more weather sensors and predictive hazard models.