31 results about "Data approximation" patented technology

A spray injection analysis and nozzle configuration system is described having a user input unit that collects spray system input parameters and relays the collected parameters to a fluid performance matching unit and / or problem geometry unit for subsequent processing. The user inputs basic system parameters, including the desired spray fluid characteristics, to obtain suggested system configuration, including spray nozzle types and quantities. Accuracy of suggested spray nozzle type and configuration is increased via approximating the viscosity and / or surface tension parameters of the desired spray fluid with that of collected performance data. When a user already knows the desired spray nozzle type and associated system parameters, the user input unit routes this information to the problem geometry unit for creation of a problem geometry file, including calculation of the drop size distribution and spray velocity, and performance modeling via the fluid modeling unit.

A computer implemented device is described that is adapted for improving memory efficiency for conducting machine learning on multi-dimensional vectors stored as specially configured data structures. The device includes network interfaces adapted for receiving data sets and communicating with data harvesting applications, as well as data storage and memory for storing the configured data structures. The multi-dimensional vectors and the system provide a data architecture that processes disparate data sets to programmatically extract features transformed from raw information, the extracted features stored in the form of data values suitable for conducting data approximations and neural network processing.

The present invention provides a method for extracting well seismic data based on Euclidean distance approximate matching, which includes: performing approximate seismic attribute matching, finding the coordinate point position closest to the target well, and extracting the seismic attribute value corresponding to the position approximately as the corresponding value of the target well position Seismic attribute values, and integrate all seismic attribute values ​​into an attribute set; carry out approximate matching of lithological data, through the start and end time range of the time window, and use time-depth conversion to convert the time range to the depth range corresponding to the target well, and then Calculate the lithology ratio within the depth range corresponding to the target well sample; match the extracted seismic attribute set with the lithology type to obtain a seismic attribute set with category labels. This method realizes the approximation of the target well position to the nearest grid position in the adjacent distance and the extraction of the seismic data of the target well. The numerical category labels and seismic attribute values ​​can provide sample point support for the training of the machine learning classification model.

The invention provides a data-driven wind farm energy storage capacity planning method, which relates to the technical field of new energy power generation planning. First, collect relevant data such as wind power, energy storage devices, wind curtailment upper limit, transmission line capacity, etc., and then establish a wind farm operation optimization model with energy storage and a wind farm energy storage capacity optimization model based on distribution robust optimization. The energy storage capacity optimization model is converted into the form of mixed integer linear programming, and finally solved by a mathematical programming solver. The wind farm energy storage capacity planning method based on distribution robust optimization provided by the invention can make full use of the historical data of wind power, consider the error of the approximate probability distribution of the historical data, take into account the economy and conservatism, and is easy to program to find the optimal solution.

Optimizing data approximation analysis using low power circuitry including receiving a plurality of data bits each corresponding to a binary indication of a test result; placing each of the plurality of data bits on an approximation circuit, wherein each of the data bits is placed on the approximation circuit by applying, to a first capacitor during a set time period, a voltage corresponding to the data bit, and wherein placing each of the plurality of data bits on the approximation circuit results in a resulting voltage stored on the first capacitor; and determining a potential correlation of the test results by comparing the resulting voltage to a voltage threshold.