15 results about "Multidimensional model" patented technology

The embodiment of the present application provides a data storage method, device and storage medium. In the embodiment of the present application, the multi-dimensional model data of a spatial object is divided into model data of multiple layers of entity objects from the constituent elements of the spatial object, and for the model data of each layer of entity objects, a reference object is introduced to compressively store a plurality of target entity objects that can be stored in combination in each layer of entity objects. On the one hand, the plurality of target entity objects can share one copy of model data, the compressive storage of the model data of each layer of entity objects is realized, the storage amount of the model data of the spatial object can be reduced, and storage resources can be saved. On the other hand, the upper layer entity objects in the spatial object can also share one copy of the model data of the lower layer entity objects, the storage amount of the model data of the spatial object can be further reduced, storage resources can be saved, and double compression of the multi-dimensional model data of the spatial object is realized.

The invention discloses an intelligent network proxy access system, which comprises a proxy resource layer used for constructing various types of proxy IP pools, storing IP resources in the corresponding proxy IP pools in a classified manner, and performing quality rating processing on the IP resources at the same time; the intelligent scheduling layer is used for synchronizing tasks with an intelligent marketing multi-dimensional model operation platform and a global data acquisition and analysis system in real time and realizing task linkage scheduling; the compliance control layer is used for simulating and avoiding platform rule risks according to the multi-platform agent compliance library in combination with human behaviors; the adaptive docking layer is used for providing a multi-type standardized interface to be docked with the intelligent marketing multi-dimensional model operation platform and the global data acquisition and analysis system; and the monitoring operation and maintenance layer is used for providing a multi-dimensional monitoring board and intelligent alarm and supporting full-link operation and maintenance management. The method has the advantages of high adaptability, high stability, high concurrent support, high compliance, service value increment and the like.

The present disclosure relates to the technical field of data processing, and specifically discloses a multi-dimensional statistical data processing method and device and computer equipment. The method comprises the following steps: acquiring transaction data of a business system in real time, and storing the transaction data in a message queue; performing initial processing on the transaction data in the message queue to obtain transaction detail data and initial processing data; acquiring metadata configuration information of a multi-dimensional model, and acquiring a current result of multi-dimensional statistical data to be processed according to the metadata configuration information; and calculating the multi-dimensional statistical data according to the transaction detail data, the initial processing data and the current result to obtain an update result of the multi-dimensional statistical data. The present disclosure adopts a set of multi-dimensional models to uniformly plan data models, realizes real-time collection and processing of transaction data, and improves data processing timeliness.

This invention discloses a distributed, block-based, multi-dimensional storage method and apparatus for seismic data volumes. The method includes: separating the header information from the seismic traces in the acquired seismic volume file and storing the header information in a preset storage space; determining multiple dimensions based on the keywords of the seismic traces to construct a multi-dimensional model; dividing the multi-dimensional model into multiple multi-dimensional data cubes and determining the name of each multi-dimensional data cube, as well as the extreme values ​​of operational values, the total number of location numbers, and the total number of multi-dimensional data cubes in each dimension; storing the multi-dimensional data cubes on a distributed storage system using a mapping algorithm; calculating the physical storage location of the target data based on the acquired target data information, and extracting the target data from the distributed storage system and / or the preset storage space. This method improves data storage flexibility and query efficiency by optimizing the seismic data storage structure and index calculation.

The invention provides a partner training strategy engine optimization method, system and device and a medium, and the method comprises the steps: obtaining a first partner training strategy engine and a to-be-partner training model in a current partner training optimization process, and business training data; the first partner training strategy engine is an original partner training strategy engine or a second partner training strategy engine obtained in a previous partner training optimization process; constructing a digital twin environment according to the service training data; according to the digital twin environment and the first partner training strategy engine, performing simulated environment partner training on the to-be-partner training model to obtain multi-dimensional model index data of the to-be-partner training model; and according to the multi-dimensional model index data, performing reward optimization on the first partner training strategy engine to obtain a second partner training strategy engine. According to the method, a partner training strategy engine can be provided, the partner training effect of the model can be effectively improved, and then the performance of the partner training model facing complex unknown challenges can be improved. The invention relates to the technical field of artificial intelligence.

The invention discloses a data processing method and device, and relates to the field of data processing, and the method comprises the steps: obtaining input data of a multi-dimensional model, the input data indicating a to-be-updated value of a specified node in the multi-dimensional model; the multi-dimensional model comprises at least one dimension, each dimension comprises one or more levels, each level comprises one or more nodes, and the specified nodes are nodes in all nodes included in the multi-dimensional model; determining an increment value of the specified node, wherein the increment value of the specified node indicates a numerical value variation between a to-be-updated value of the specified node and a storage value of the specified node in the multi-dimensional model; and updating a storage value of a relative node of the specified node based on the increment value of the specified node, wherein the relative node of the specified node comprises nodes of other levels influenced by the specified node in the multi-dimensional model. The storage value of the affected relative node is updated through the increment value of the specified node, the calculation amount of multi-dimensional aggregation calculation is reduced, the calculation performance is improved, and the existing calculation bottleneck problem is solved.

The invention discloses a data verification and early warning system based on an OLAP engine, and relates to the technical field of data processing. The system comprises a data processing module, a modeling optimization module and a data verification module: the data processing module is used for accessing enterprise original data, verifying data access accuracy based on a preset access standard, generating access abnormity prompt information if the data access accuracy does not reach the standard, and forwarding the data to a data cleaning module; if the data access accuracy reaches the standard, directly entering a modeling optimization module; the modeling optimization module is used for executing dynamic modeling optimization processing on the cleaned data by utilizing an OLAP engine, and the dynamic modeling optimization processing comprises a data storage unit and a multi-dimensional model construction unit; and the data verification module is used for performing output verification on the data processed by the OLAP engine based on the multi-dimensional verification parameters, and generating alarm information when the data meets an alarm triggering condition.

A method comprising receiving, by a computer system, a parameter value for each of multiple parameters for an application for an enterprise and determining, by the computer system based on a first database table lookup, a recommended authentication vector for the application based on the parameter values. The recommended authentication vector comprises assurance level values for authenticator strength assurance level (ASAL), Post Authentication Assurance Level (PAAL), and Origin Point Assurance Level (OPAL). The method further comprises determining, by the computer system based on a second database table lookup, one or more enterprise-certified authentication infrastructures for the application based on the recommended authentication vector and implementing the one or more enterprise-certified authentication infrastructures in the application for a production deployment of the application by the enterprise.

The invention provides a project cost data management system, and relates to the technical field of project cost, the project cost data management system comprises a dynamic association engine, a cost index multi-dimensional model module and a distributed block chain storage module, the dynamic association engine is used for establishing an association relationship among a project quantity list, a quota library, a real-time market price and design change data; a cost result is automatically generated and a cost deviation is updated in real time based on the association relationship; the cost index multi-dimensional model module is used for constructing a cost index multi-dimensional model based on a data warehouse and an online analysis processing technology; according to the method, a four-dimensional binding model of the bill of quantity-quota library-real-time market price-design change is constructed through the dynamic association engine, automatic data association is realized by presetting association rules, and manual matching and input are not needed; the cost is updated in real time and the deviation is calculated when any data changes, compared with traditional manual operation, the efficiency is higher, the cost deviation rate is smaller, and the cost risk caused by manual errors is reduced.

Disclosed are systems and method for determining information related to building materials based on determined measurements from a multi-dimensional building model comprising features and elements embodying such materials and measurements. The multi-dimensional model may be based on a plurality of received images, such as ground-based images of a building. The multi-dimensional model may be scaled, or a scale extracted based on data of the model. The multi-dimensional model may comprise architectural elements, and the scale used to determine measurements of such architectural elements. With the scaled measurements of the architectural elements in the model, product information related to multi-dimensional model and its elements may be derived and combined in alternative means.

The invention provides an electric power prediction method and system based on a multi-source and multi-dimensional CIM model, and relates to the field of electric power system automation and communication. Comprising the steps of expanding an existing information model standard to construct a multi-source and multi-dimensional information model, integrating data of multiple energy types, including power generation power data, meteorological data and environmental data, and forming a standardized model by analyzing an existing class and inheriting or creating a new class to add attributes and relationships; historical data in the multi-source multi-dimensional information model are preprocessed, and abnormal data are cleaned by adopting a multi-dimensional verification mechanism and are intelligently corrected; constructing and training a neural network model, and processing a time sequence data capture dependency relationship; the neural network model after deployment training interacts with the multi-source multi-dimensional information model through an interface, real-time prediction of the generated power is realized, the long-term dependency relationship and complex nonlinear characteristics of the water-wind-light generated power are effectively captured, the prediction precision and reliability of the generated power are improved, and the safety and stability of power grid operation are improved.

The application provides a resistive device and a manufacturing method thereof, comprising: predicting an electrical resistance value of a phase change process caused by a phase change of a resistive material of the resistive device based on a tensor-based multi-dimensional model; and manufacturing the resistive device according to the prediction result. The method of the application can greatly reduce the calculation amount required for prediction by introducing a tensor to abstractly describe the material; meanwhile, the method can solve the problem that the channel behavior of the resistive device depending on the phase change material is complex, nonlinear and difficult to predict by sequentially changing the value of the tensor element to simulate the gradual phase change process of the material and tracking the change of the overall resistance of the material in the process to predict the behavior. The method is simple and easy to implement, the prediction is relatively effective, and the method has a wide application prospect.

The invention relates to the technical field of engineering data sharing, in particular to an engineering project data security sharing collaboration method and system based on federated learning. The method comprises the following steps: acquiring an initial model gradient update parameter of each participant, and constructing an initial global model parameter data set; according to a multi-dimensional model security enhancement strategy, performing multi-dimensional security enhancement processing on the initial global model parameter data set, and determining an enhanced gradient update data set; the multi-dimensional security enhancement processing comprises anti-poisoning processing and anti-sensitive role inference processing; and performing aggregation processing on the enhanced gradient update data set, embedding a feature trap verification mechanism in the aggregation processing process, and generating and distributing a security enhancement global model. According to the method, the security of federated learning in the engineering data security sharing process can be comprehensively improved while the efficiency of the model is ensured, and the balance and unification of the security and the efficiency of the federated learning model are realized.

The invention provides a multi-dimensional model intelligent modeling method based on intention analysis and knowledge driving, and relates to the technical field of simulation calculation, and the method comprises the steps: receiving multi-source heterogeneous input data of a target; analyzing the multi-source heterogeneous input data based on a first AI model to obtain a modeling intention and a feature information set; according to the modeling intention and the feature information set, generating an entity hierarchical semantic ontology model instance based on a predefined entity hierarchical semantic ontology model, a modeling feature knowledge base and a second AI model; and based on the entity hierarchical semantic ontology model instance, generating an executable simulation construction script of the target through a third AI model. According to the method, agile, extensible and standardized entity intelligent construction is realized, and the simulation deduction efficiency is improved.

The invention discloses a multi-dimensional model and data driven photovoltaic power station aggregation output attenuation evaluation method. Comprising the following steps: constructing a multi-dimensional spatial-temporal feature matrix; establishing an output attenuation nonlinear dynamic model; outputting a reliability state sequence through a data-physics dual check mechanism; and carrying out attenuation rate aggregation and trend prediction based on a verification result. According to the method, the problems of incomplete evaluation, poor dynamic nature and low reliability in the prior art are solved, and accurate, dynamic and reliable evaluation of the output attenuation characteristics of the photovoltaic power station is realized.