9 results about "Surrogate data" patented technology

Apparatus for ensuring data accuracy and related methods include a processor and a memory connected to the processor, wherein the memory contains instructions configuring the processor to receive a data structure with a plurality of data attributes, validate the data structure, using a validation machine-learning model, by comparing each data attribute of the plurality of data attributes against at least a validation metric, identify an error by identifying at least an erroneous data attribute as a function of the validation, display, using a user interface, an annotation as a function of the error, wherein the annotation comprises an indication of rationale, generate at least a substitute data attribute for replacing the at least an erroneous data attribute, receive supplemental input in response to the at least a substitute data attribute, and update the data structure by resolving the error as a function of the supplemental input.

The application discloses a kind of hierarchical system data migration method, device, equipment and storage medium, it is applied to hierarchical system total center in the field of data migration, comprising: obtaining the cascade registration request sent by target subcenter is cascaded, and according to the data migration task of surrogate migration data is generated;Get migration task execution instruction, and the corresponding surrogate migration data and the agent information of several to-be-migrated collection agents are issued to target subcenter;Data receiving information returned by target subcenter is acquired, cascade instruction is issued to to-be-migrated collection agent to realize the cascade of to-be-migrated collection agent and target subcenter, and target information that data migration succeeds is generated, and the end of surrogate data migration task is marked according to target information.Through the data migration between nodes and node cascade, the information and the right of original node are effectively and safely migrated to new node, while the function of original node is not interrupted, new node can obtain the management right of the data and assets of original node.

The invention relates to a method for predicting a subsea pipeline vibration and local scouring coupling process, and belongs to the technical field of ocean monitoring. The method comprises the following steps: training a PINN model fusing structure vibration-flow field change-scouring development physical information, and finally, in the training process, through minimizing a neural network loss function, predicting the local scouring coupling process of a subsea pipeline. And training a PINN model fusing structural vibration-flow field change-scouring development physical information, and carrying out numerical simulation on the vortex-induced vibration and local scouring long-duration process of the elastic submarine pipeline. According to the method, physically-guided data learning is used for replacing data-driven physical solution, so that the physical reliability of traditional numerical simulation is reserved, and the high efficiency and generalization of a data model are achieved. For the engineering problems of high risk, difficult monitoring and strong coupling such as subsea pipelines, a rapid tool can be provided for multi-scheme comparison and selection in the pipeline design stage, and a feasible technical path can be provided for vibration-scouring risk real-time early warning in the operation stage.

The application relates to the technical field of data processing, and discloses an arteriovenous fistula remote monitoring and warning system which comprises the following steps: collecting monitoring data of multiple dimensions of an arteriovenous fistula; performing graph clustering on all-dimensional monitoring data at each moment to obtain a category division result at each moment, obtaining a change point and a change abnormality rate according to the category division result, and obtaining an abnormal time period, abnormal data and an abnormal dimension sequence; performing EMD decomposition on each abnormal dimension sequence to obtain a plurality of IMF components, obtaining a cycle length of each IMF component, obtaining replacement data and a conversion vector of each segment of abnormal data according to the cycle length, and compressing the replacement data and the monitoring data to obtain compressed monitoring data; and completing the arteriovenous fistula remote monitoring and warning according to the compressed monitoring data and the conversion vector. The application aims to solve the problem that abnormal data destroys the regularity of monitoring data and affects the compression efficiency and transmission efficiency.

A unified method for neural operator training and partial differential equation system solving based on variational principle, medium and product, comprising: sampling from the parameter space of the partial differential equation system to form a data set containing only discrete parameter field, divided into offset set, test set, unlabeled set, the unlabeled set is divided into multiple batches, and a mask tensor of boundary condition is formed; using a neural operator module to predict the node solution of the discrete parameter field sample in the unlabeled set, obtaining a discretized functional as an estimate of the system functional; calculate the gradient of the functional estimate with respect to the node solution, take its norm as the minimization target, obtain the update step of the current node solution, and update the weight of the module. The application unifies the two tasks of solving the partial differential equation system operator and training the neural operator in one framework, introduces a variational operation to construct an unlabeled optimization target to replace the data-driven training error term, saving the time and computing power required to generate a large number of labels for constructing the data-driven error term.

The invention discloses an IBIS model data processing method and apparatus, a computer device and a storage medium. The method comprises the steps of obtaining a pull-up curve and a pull-down curve of a target IBIS model; judging the effectiveness of the pull-up curve and the pull-down curve; in response to the judgment that only the pull-up curve is a valid curve and the pull-down curve is an invalid curve, generating a replacement pull-down curve based on a preset complementary relationship according to the numerical value of the pull-up curve; in response to the judgment that only the pull-down curve is a valid curve and the pull-up curve is an invalid curve, generating a replacement pull-up curve based on a preset complementary relationship according to the numerical value of the pull-down curve; wherein the effective curve and the generated alternative curve are used for circuit simulation. According to the method, under the condition that a curve is missing, available alternative data is generated through reasonable logic inference and construction, it is ensured that the simulation process can continue to be carried out, and a relatively accurate simulation result meeting physical significance is obtained.

The invention relates to the technical field of ground vehicle navigation and positioning, in particular to an integrated navigation method integrating fault recovery and multi-task uncertainty estimation, and solves the problems that when an existing IMU / ODO integrated navigation system seriously distorts ODO data due to slipping, a traditional FDI method only removes and does not supplement the ODO data, the system is forced to be degraded into a pure inertial navigation resolving mode, and the navigation efficiency is low. The invention provides an integrated navigation method integrating fault recovery and multi-task uncertainty estimation, which has slip sensing and intelligent recovery capabilities, organically integrates three core links of'detection, replacement and fusion ', and comprises the following steps: data initialization, detection, replacement and fusion. ODO anomaly detection based on innovation is executed, multi-task pseudo odometer replacement data is generated, according to an ODO anomaly detection result based on innovation, an observation mode is dynamically selected, a measurement noise covariance matrix is constructed, IEKF is adopted as a data fusion center, and measurement updating and time recursion are carried out.

This invention discloses a method and related equipment for handling CEMS carbon emission data failures, belonging to the field of online carbon emission monitoring and data quality assurance. The method includes: constructing a working condition knowledge base containing historical "backtracking window-future sequence" key-value pairs; real-time monitoring and identification of CEMS carbon emission data failures; retrieving the K most similar historical segments from the knowledge base as evidence using the backtracking window before failure as the query key; fusing the backtracking window and the retrieved evidence into a time-series prediction model to generate predicted values ​​for the failure period as replacement data; and simultaneously outputting an interpretability report containing the source, similarity, and contribution of the evidence. The system is an intelligent agent executing this method. This application solves the problems of low accuracy and poor interpretability caused by existing fixed-rule substitution methods by explicitly introducing historical similar working condition evidence to constrain and enhance predictions, significantly improving the accuracy, auditability, and adaptability to complex working conditions of data repair.