8 results about "Data model" patented technology

A framework for automatically provisioning computing devices includes a central database system and a central file system. Information stored in the database comprises a model of the individual devices, as well as the interconnections of the devices. The central file system stores the software components to be installed on the devices. When provisioning is carried out, the database sends commands to agents located on each device which cause them to retrieve and install the software components from the file system, and to configure the components according to the stored model.

The invention discloses a metal sample 3D printing forming method with a defect presetting process. The 3D printing forming method comprises the following steps that 1, according to the actual size and shape of a required metal sample, a three-dimensional modeling software is adopted for data model designing; 2, different types of defects of a certain number, size and distribution are designed, and modifying is carried out in a three-dimensional model; 3, the slicing treatment is carried out on the designed model, contour data of each layer are obtained, and a forming path is planned; and 4, proper 3D printing metal powder is selected according to the material of the metal sample, and an SLM 3D printer with appropriate forming size is selected for printing and forming. According to the method, the 3D printing forming method is introduced into the preparation of the metal sample internally provided with the defects for the first time, the existing sample preparation difficulty is greatly simplified, and the sample preparation precision is improved; and a selective laser melting (SLM) 3D printing device is used so that the metal samples with various complex shapes can be prepared.

The invention discloses an improved CIM-based power data processing method. The method comprises the steps of firstly performing storage by type on data in different systems according to data sourcesand attributes; secondly performing data extraction, cleaning, transformation and loading in sequence to build an improved CIM; and finally finishing ETL of data of different system sources by utilizing the improved CIM on an integrated bus. The CIM of a power system is introduced in the ETL process, so that the problem that data models cannot be unified when power system data of diversified sources is processed in a conventional ETL method is solved, the overall effect of the ETL process is improved, and the power data is efficiently integrated.

The invention provides a data sheet analyzing and processing method and device. The data sheets comprise a common data sheet on a data common layer and an external data sheet on a non data common layer. The data sheet analyzing and processing method comprises calculating the processing cost data of a common data sheet on a data common layer; determining a common data sheet which the external data sheet of the non data common layer depends on; and calculating the usage cost data of the external data sheet on the basis of the processing cost data of the common data sheet. Thus, when the cost of each common data sheet on the data common layer is evaluated, self storage and computational consumption of the current data sheet are not individually considered, several upstream data sheets and brother data sheets of the data sheet are comprehensively considered, and therefore the processing cost of the common data sheet can be evaluated reasonably and accurately, the quality of the data model construction of the data common layer can be reflected, and decision support can be provided for optimization and operation of the data common layer model.

The invention discloses a power station boiler balanced combustion optimization method based on data driving, which includes a front-end sensor, a data model, a balanced combustion control center, flow velocity adjusting equipment, combustors and a flow velocity and flow measurement sensor, wherein the front-end sensor is used for detecting parameters reflecting the combustion state in a hearth, the data model analyzes and judges whether deviated combustion and insufficient combustion exist in the hearth or not, the balanced combustion control center receives output of the data model and air powder flow velocity and flow parameters measured by the flow velocity and flow measurement sensor, then analyzes and calculates an adjusting instruction, and sends the adjusting instruction to the flow speed adjusting equipment, and the flow speed adjusting equipment can change the resistance of a primary air pipeline and adjust the air powder flow speed and flow of the corresponding combustor, so that air powder combustion of all the combustors is optimized, sufficient combustion is achieved, and the combustion efficiency is improved. Primary air powder deviation can be adjusted on line under data driving, deviation combustion in the furnace is effectively solved, the combustion efficiency is improved, and coal consumption is reduced.

Image identification is disclosed including acquiring N images, N being a natural number greater than 1, extracting target characteristic information from respective ones of the N images to obtain a first data set corresponding to the N images, and determining, using a data model, a category associated with the first data set corresponding to the N images.

The embodiment of the invention discloses a data model configuration method and device, a storage medium and computer equipment, and relates to the field of data processing. When application development is carried out based on the data model, dynamic expansion of the service capability is carried out on the data model based on the graphical interface, the data model does not need to be modified in a code modification mode, the time of a function coding link and the code testing time are saved, and the testing efficiency is improved. The defect of data model capability caused by difference of personal programming capability during function coding is avoided, and the use reliability of the data model is ensured.

According to the nonlinear system recognition method provided by the invention, the following data models are constructed: u is a zero-mean Gaussian sequence of an input unit variance, z (u) is a vector for mapping u to a finite dimension, omega o is an optimal weight vector, and v is system interference noise; d is a desired signal; collecting input data and output data of a controlled system toobtain a training sample; inputting the training sample into the data model, and training the data model; and when the adaptive weight vector omega approaches the optimal weight vector omega o in thetrained data model, outputting the data model to realize system tracking. The method is suitable for system recognition of a controlled system with unknown parameters or characteristics or frequentlychanged parameters or characteristics, and the recognition accuracy is improved.