18 results about "Time average" patented technology

The invention discloses a distributed acoustic sensing earthquake monitoring data stream processing method and system, and belongs to the technical field of earthquake monitoring and data processing. The method comprises the following steps: after preprocessing original seismic monitoring data, slicing the original seismic monitoring data by adopting a sliding processing time window to obtain data fragments suitable for real-time detection; designing a self-adaptive short-time average / long-time average detection algorithm, detecting data segments, and dynamically adjusting self-adaptive parameters in the algorithm according to data characteristics; and finally, multi-channel fusion detection is performed on the initial candidate list of the seismic events, so that a final detection list of the seismic events is generated. The method is based on a distributed streaming data processing architecture, combines the innovation advantages of a self-adaptive earthquake detection algorithm, can improve the earthquake detection precision, guarantees the real-time performance of a detection result, and can provide efficient and reliable technical support for a large-scale earthquake monitoring task.

The invention discloses a lightweight load prediction method and system for a distribution transformer, relates to the technical field of power systems, and solves the problem that efficient and accurate lightweight prediction cannot be carried out on the load of the distribution transformer, and the method comprises the steps: analyzing the historical load of the distribution transformer in different dates in the past; binding the historical average temperature of the power utilization area in different dates in the past with the corresponding historical load; analyzing the load condition of the distribution transformer according to the date type of the power utilization area in the current date and the real-time average temperature, and analyzing to obtain a reference load interval or a reference load of the distribution transformer in the current date; predicting the load of the distribution transformer at the next time node according to the reference load interval to obtain a predicted load interval of the distribution transformer at the next time node; and analyzing the load condition of the distribution transformer at the next time node according to the predicted load interval. According to the invention, efficient lightweight prediction of the load of the distribution transformer is realized.

The application discloses a steady-state detection method based on two-fluid six-equation transient calculation, which comprises the following steps: before a detection time point, data required for local convergence judgment and TASS judgment are calculated and arranged; time local convergence of a system is judged according to enthalpy change of the system; after the convergence judgment is completed, TASS judgment is started on a historical state of the system, so that the system is ensured to completely enter a final stable state. The application improves the reliability under a low-energy and small-step working condition through a mixed relative convergence-time average judgment method, and meanwhile, the original steady-state detection efficiency is maintained.

The application provides a frequency standard measurement method, device, computer equipment and storage medium, the method comprises: frequency source output measurement signal is carried out frequency division processing, obtains low frequency pulse signal; using high-precision time interval counter to low frequency pulse signal is carried out delay measurement and time interval counting, and is output in the form of time stamp; by setting a sliding window, using sliding average algorithm to time stamp is carried out sliding average filtering processing, all time stamps are carried out sliding difference to obtain time difference, time difference is grouped according to order and is taken average in group to obtain average time difference; by increasing the length of the sliding window, the number of samples is increased to reduce the statistical error; using average time difference, calculate frequency measurement value, relative frequency deviation and allan variance. The method of the application increases the sliding window, and the frequency measurement result obtained by the algorithm of grouping and averaging the time difference has higher measurement precision and stability.

The application relates to a method and device for determining income, a computer device, a computer readable storage medium and a computer program product. The method comprises: obtaining response indexes of a plurality of building objects, the response indexes representing response capabilities of the building objects to grid instructions, and the response indexes comprising at least one of the following: a response timeliness index, a response effectiveness index, a historical response average time index, and a historical response average effectiveness index; determining comprehensive scores of the building objects according to the response indexes of the building objects; and determining target incomes of the building objects according to the comprehensive scores of the building objects. The method can more accurately distinguish the response performances of different building objects, and can more fairly, accurately and incentively allocate incomes to the building objects according to the response performances of the different building objects.

The invention discloses a modal decomposition and fractal dimension fused coal mine micro-seismic arrival time pickup method. The method comprises the following steps: 1, acquiring an original micro-seismic signal by adopting a micro-seismic monitoring system; 2, obtaining a denoised micro-seismic signal; thirdly, in the sliding process of the long-time window and the short-time window, the fractal dimension of each window is obtained through a box dimension method, and a short-time fractal dimension derivative, a short-long time fractal dimension difference and a short-long time fractal dimension derivative difference corresponding to each window moment are obtained; 4, in the sliding process of the long-time window and the short-time window, the energy ratio corresponding to each window moment is obtained based on the short-time average energy / long-time average energy of each window; 5, constructing a weighted scoring function; and 6, acquiring the microseismic arrival time. The method is reasonable in design, not only can self-adaptive decomposition and denoising be realized, but also joint analysis based on fractal dimension and STA / LTA energy ratio can be realized, so that more stable and accurate microseismic arrival time pickup can be realized.

The application relates to the technical field of personnel position determination, in particular to a key personnel position determination method, device and equipment, wherein the accuracy of historical personnel position determination, a historical average time attenuation factor and an average spatial correlation degree are used to dynamically and adaptively determine the weight corresponding to the perception data type. Based on the determined weight corresponding to the perception data type, the time attenuation factor can improve the time sensitivity of the personnel position determination, and the address confidence degree is fused to finally accurately determine the comprehensive score of the address, and the key personnel position is determined based on the comprehensive score of the address, so that the working efficiency can be improved, the personnel cost can be reduced, and the response speed can be improved.

The invention discloses a flood early warning information determination method and device of a transformer substation and electronic equipment. The method comprises the steps that rainfall time sequence data of an area where a target transformer substation is located are acquired, and the rainfall time sequence data are used for representing changes of the rainfall capacity and the ponding depth of the area along with time; based on the rainfall time sequence data, a return period is determined, and the return period is used for representing the average time interval of rainfall events with the same rainfall intensity as the rainfall intensity of the area in the historical time period; determining the flood level of the target substation based on the recurrence period; based on the rainfall time sequence data, the occurrence time of the maximum ponding depth of the target transformer substation is determined, and the maximum ponding depth refers to the maximum value in ponding depths corresponding to multiple positions included in the target transformer substation; and determining flood early warning information of the target substation based on the flood level and the occurrence time. According to the method and the device, the technical problem that the flood early warning information determination result of the transformer substation is inaccurate in the prior art is solved.

A method and data processing system for identifying data anomalies in data obtained by a condition monitoring system from a fleet of industrial assets is provided. A time series of data values is obtained for each asset in the fleet and an average time series for the fleet is determined, based on the obtained time series. For a selected asset in the fleet a model of the dependency between the obtained time series and the average time series is generated, and a further time series is generated for the selected asset. Anomalous data values are identified from the further time series.

The application relates to the technical field of brain-like perception and computation, in particular to a motion compensation hardware acceleration method and device, which comprises the following steps: denoising is performed on current events and past preset time window events in an event stream based on FPGA to obtain a denoised event stream; events in the denoised event stream are divided into a plurality of time windows; pixel positions of each event in each time window are superimposed with positions of camera motion based on IMU data to obtain a warped event stream; time window event accumulation is performed on the warped event stream; a CPU saves an obtained event accumulation frame in an off-chip RAM; average time stamps of each pixel of an image are obtained from the event accumulation frame; Gaussian filtering is performed to obtain a motion compensation frame, which is output under the control of the CPU; and the application can improve the efficiency of event camera motion compensation and reduce the delay.

System and methods of this technology can provide a framework using machine learning based message generator. The framework can retrieve elapsed times according to computing devices executing an application. Once the elapsed times are retrieved, the framework can generate a total elapsed time that can indicate an average amount of time captured by the at least one computing devices. The framework can make a determination based on the total elapsed time and a threshold elapsed time. The threshold elapsed time can be generated from data associated with previous months, years, days, among other time periods. Upon determining that the total elapsed time is higher than the threshold elapsed time, the framework can generate instructions to display the metrics associated with the total elapsed time, on another computing device.

The application discloses a kind of distributed acoustic sensing earthquake monitoring data stream processing method and system, belong to earthquake monitoring and data processing technical field.The method of the application includes: after the original earthquake monitoring data is preprocessed, it is sliced using sliding processing time window, and the data segment suitable for real-time detection is obtained;Design adaptive short-time average / long-time average detection algorithm, detect the data segment, and dynamically adjust the adaptive parameter in the algorithm according to the data characteristics;Finally, the initial candidate list of earthquake event is executed multi-channel fusion detection, to generate the final detection list of earthquake event.The application is based on distributed stream data processing architecture, combined with the innovative advantage of adaptive earthquake detection algorithm, can improve the accuracy of earthquake detection while ensuring the real-time of detection result, can provide efficient and reliable technical support for large-scale earthquake monitoring task.

The invention discloses a bus travel time prediction method based on multi-component decomposition and attention fusion. The method comprises the steps of S1, date selection; s2, component coding; s3, feature fusion: performing weighted fusion on the riding features and the waiting features through travel attention, modeling long-range dependence between different road sections and stations by using a self-attention mechanism, and outputting global fusion features; calculating a corresponding time code by using historical average time, and performing dot product operation on the time code and the global fusion feature to generate a final comprehensive feature for prediction; and S4, carrying out loss alignment and prediction. According to the invention, the riding time and the waiting time are respectively modeled; off-line and on-line departure frequency data are fused to enhance waiting time prediction; and a multi-component loss alignment mechanism is constructed, the consistency of the formation level prediction and the overall travel level prediction is ensured, and finally the prediction precision and the scene adaptability are improved.

A method, system, and article of manufacture for modifying a queue assignment for a contact center are provided. At least one computing device determines, by solving for constraints, at least one staffing change for at least one of the first queue or the second queue, using as inputs (a) first time-based service metrics, (b) second time-based service metrics, (c) data describing eligible staffing changes, and (d) at least one predetermined constraint. The at least one staffing change is a modification to the queue assignment of a subset of the computing device instances that is predicted to improve net staffing relating to service targets selected from (a) an average speed of answer (ASA) specifying an average time for one of the computing device instances to initiate handling of a particular task after the particular task has been assigned to the relevant queue and (b) a service level specifying a percentage of tasks for which handling is initiated within a specified time frame after the tasks are assigned to the queue. The at least one staffing change can be implemented by modifying the queue assignment of the subset of the computing device instances.

The application discloses a label machine paper wheel pressure automatic adjusting method and related equipment and storage medium, relates to the label machine control technical field, and the method obtains the zero time sequence of the paper wheel and the paper measuring wheel, calculates the time difference of the average time, and generates a pressure adjusting instruction accordingly, dynamically adjusts the pressure of the paper wheel, and the time difference reaches the preset error threshold value until the dynamic pressure reaches the maximum value. If the condition is still not met, an alarm is triggered. In the adjusting process, various pressure adjusting modes such as a linear motor, a stepping motor or an electromagnetic coil are adopted, and an adaptive learning algorithm is combined to optimize the adjusting parameters. In addition, a material-pressure database is established to realize the rapid adaptation of new consumables. The application also relates to an electronic device and a computer readable storage medium for realizing the above adjusting method. The technology can realize the automatic and accurate adjustment of the paper wheel pressure, and improve the production efficiency and quality of the label machine.

According to an embodiment, an information processing apparatus stores, for each workflow that defines an assignment order of tasks to be executed in sequence by a plurality of operators, a task history in which a type of the task executed by each of the operators and a date and time at which the task has been executed are associated with each other. The information processing apparatus calculates an average time for each type of the task from a time when an order is assigned to the operator to a time when the operator executes the task, on the basis of the stored task history. Further, the information processing apparatus sends a notification to an operator who has not performed the task at a timing based on the average time corresponding to the type of the task.

System and methods of this technology can provide a framework using machine learning based message generator. The framework can retrieve elapsed times according to computing devices executing an application. Once the elapsed times are retrieved, the framework can generate a total elapsed time that can indicate an average amount of time captured by the at least one computing devices. The framework can make a determination based on the total elapsed time and a threshold elapsed time. The threshold elapsed time can be generated from data associated with previous months, years, days, among other time periods. Upon determining that the total elapsed time is higher than the threshold elapsed time, the framework can generate instructions to display the metrics associated with the total elapsed time, on another computing device.

According to the present invention, a terminal device that communicates with a base station device measures a measurement item for a beam and, on the basis of determining that the measurement item satisfies a condition that is that the value of the measurement item is greater than a threshold value, incorporates measurement results that are time averages for a plurality of measurement items for each of one or more beams into a field of a MAC CE and transmits the MAC CE to the base station.