30 results about "Survival modeling" patented technology

Methods and systems for using survival modeling methods with pipeline inspection data to determine causal factors for corrosion under insulation comprise determining a first corrosion condition of a pipeline joint at a first time; determining a second corrosion condition of the pipeline joint at a second, subsequent time; determining joint attributes, pipeline attributes, and location attributes associated with the pipeline joint; and repeating the process for a plurality of pipeline joints in one or more pipelines. This information is fed into a multiple regression and survival analysis process that determines regression coefficients reflecting the estimated degrees to which various factors contribute to corrosion under insulation. The survival analysis also determines one or more survival models capable of predicting when a given pipeline joint is likely to transition from a first corrosion state to a different second corrosion state, given values for its various attributes.

The invention relates to a method for predicting RDR of an electric vehicle battery based on big data machine learning. The method is composed of a corresponding application framework, a flow and a calculation model. The method comprises the following steps: firstly, performing data consolidation and cleaning on battery real-time data collected in the running process of an electric vehicle batteryand other operation data of the electric vehicle; carrying out characterization processing on the data; and establishing a model and training a verification algorithm through big data machine learning, wherein a nonlinear hybrid algorithm model, a survival model and a random forest are mainly used for modeling, and results are evaluated and optimized from different angles, so that an electric vehicle battery RDR prediction model is established, maintenance and replacement of a battery are optimized, and the safety index of a vehicle owner is improved, and the balance between system performance and economic benefits is achieved.

Embodiments of the present disclosure provide a data processing method and device, an electronic device, an interactive system, a terminal device, and a storage medium, including: collecting target behavior information of multiple users for a target event, and the target behavior information includes target behavior events and target behaviors Data, according to the target behavior information, the preset survival model and the preset portraits of multiple users, determine the risk level of the target event, generate and display prompt information corresponding to the risk level, collect target behavior information and portraits, and The collected information (that is, target behavior information and portrait) is combined with the survival model to determine the risk level. Since the dimension for determining the risk level is increased, the reliability of the risk level can be improved, thereby improving the security of user information.

The invention provides a simulated survival ability judging method for a network information system. A work flow model for the system is established to describe the state of the structure and the performance of the system when, ideally, no failure occurs; a failure model and an error-tolerant model are established for resources with failure possibility to describe the failing process and reactionsafter the failure of a member; an information system survival model is established with combination of the two to describe the influence of certain failure resources on the whole system in a specialnetwork environment; a simulation method is adopted to inject safety events into the synthesized model, specifically including failure rate of the member, influence of invasive events on the member and survivability of the member; through statistics of accessible state information in SPN, survivability parameters of the information system service are computed to perform evaluation of the survivalability of the information system. The invention can analyze the completion quality of services of a network information system in a specific application environment according to the survival attributes of the construction members.

The embodiment of the present application discloses a data processing method and a related device. For the product to be promoted, the historical content push data of the target product related to the product to be promoted is acquired, and the historical content push time and history in the historical content push data are obtained. At the actual conversion moment, you can obtain the information on how long the historical pushed object has been converted after being pushed. When training the survival model based on the object characteristics of the historical pushed object, the aforementioned data dimension of the conversion time is introduced, and the object is in the The probability of conversion occurring in multiple consecutive time periods turns the problem of whether to convert into a problem of delayed conversion, which enhances the learning of delayed conversion in the survival model in the time dimension, and realizes a strong correlation between the original historical content push data and the target product The decoupling of , so that the first survival model trained can also temporarily replace the conversion rate model in the cold start phase to provide conversion rate prediction for products to be promoted.

The invention discloses a survival prediction system for T3‑LARC patients before treatment, which includes a risk factor acquisition module, a risk factor preprocessing module, a risk factor comprehensive analysis module, an operator selection module, a survival model generation module and a survival rate display In addition, the present invention also provides a prediction method for the survival prediction system of T3‑LARC patients before treatment. The present invention can provide clinical doctors with individualized risk factor analysis of patients before treatment, predict the recurrence rate and mortality of patients in N years after operation, and provide references for clinicians to formulate individualized treatment and follow-up plans, which has important significance Clinical significance, can greatly improve the prognosis of patients, prolong survival and improve quality of life.

The present invention relates to the application of compound P7C3-A20 in the preparation of medicines for treating cerebral ischemic diseases. The present invention confirms through cell experiments that P7C3‑A20 can improve the survival rate of mouse cerebral cortex neurons cultured in vitro in the model of hypoxia and glucose deficiency. These results indicate that P7C3‑A20 has a protective effect on cerebral ischemia, can prevent and treat brain damage caused by cerebral ischemia, and has broad application prospects in the preparation of drugs related to cerebral ischemic injury and / or cerebral infarction.

The present disclosure relates to a media attribution system that improves multi-channel media attribution by employing discrete-time survival modeling. In particular, the media attribution system uses event data (e.g., interactions and conversions) to generate positive and negative conversion paths, which the media attribution system uses to train an algorithmic attribution model. The media attribution system also uses the trained algorithmic attribution model to determine attribution scores for each interaction used in the conversion paths. Generally, the attribution score for an interaction indicates the effect the interaction has in influencing a user toward conversion.