29 results about "Time step" patented technology

This specification describes a simulation system that performs simulations of physical environments using a graph neural network. At each of one or more time steps in a sequence of time steps in a given time interval, the system can process a representation of a current state of the physical environment at the current time step using the graph neural network to generate a prediction of a next state of the physical environment at the next time step. Generally, the environment has discontinuous dynamics at one or more time points during the time interval.

The invention provides a time step determination method and device for solving a physical quantity of a transient physical process. The method comprises the following steps: acquiring first time step iteration information corresponding to a historical moment in the transient physical process; the first time step iteration information is used for representing the condition of iteratively updating the time step in the process of solving the convergence solution corresponding to the target physical quantity and the historical moment; the target physical quantity is a to-be-solved physical quantity in the transient physical process; determining a first predicted time step corresponding to the current moment according to the first time step iteration information corresponding to the historical moment and the first predicted time step corresponding to the previous moment; and iteratively updating the first prediction time step corresponding to the current moment to obtain a target time step enabling the target physical quantity to converge with a solution corresponding to the current moment. According to the method, the time step length enabling the physical quantity to converge in the transient physical process can be quickly determined.

The application discloses a soft measurement modeling method based on a residual time attention time convolution network and belongs to the field of soft measurement modeling. First, the time attention module is combined with the time convolution network, and the mutual influence between previous time steps and the current time step is integrated into the current time. Then, the residual connection is added on the basis of the time attention. Finally, the quality variable is predicted. The application can better extract the nonlinearity between data to improve the prediction performance and more accurately extract the relevant features between data.

The application provides an entity linking method and system based on dynamic time steps, and relates to the technical field of natural language processing. The method comprises the following steps: obtaining a plurality of entity mentions of a related topic in a document to be analyzed; obtaining candidate entities of each entity mention from a knowledge base; constructing a mapping entity association graph by using a dynamic time step method, and extracting global topic consistency features from the mapping entity association graph; obtaining target entities of each entity mention from the candidate entities according to the global topic consistency features, and associating each entity mention with the corresponding target entity. In this way, by using the dynamic time step method to construct the mapping entity association graph, in each time step, the candidate entities related to the topic are selected as the mapping entities of the mapping entity association graph, so that the correct global topic consistency features can be extracted from the mapping entity association graph, thereby improving the accuracy of entity linking.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a prediction characterizing an environment. In one aspect, a method includes obtaining a respective observation characterizing a state of an environment for each time step in a sequence of multiple time steps, comprising, for each time step after a first time step in the sequence of time steps: processing a network input that comprises observations obtained for one or mor preceding time steps to generate a plurality of acquisition decisions; obtaining an observation for the time step, wherein the observation includes data corresponding to modalities that are selected for acquisition at the time step, does not include data corresponding to modalities that are not selected for acquisition at the time step; and processing a model input that includes the observation for each time step in the sequence of time steps to generate the prediction.

The application discloses a logical time management service method and system for joint tests, wherein participants set time control strategies and time limited strategies, and initiate logical time advancing requests and request processing callback requests to middleware according to preset time steps, and register callback functions; a time adjuster calculates a timestamp lower limit to provide data guarantee for time advancing; the middleware receives the logical time advancing requests, checks whether the participants have the right of the time control strategies, updates the current timestamp lower limit, receives the processing callback requests, checks FIFO queues and processes queue messages, checks the time limited strategies of the participants, checks TSO queue states and processes queue messages, checks the relationship between the time requested by the participants and the timestamp lower limit, and calls the callback functions allowed by the time advancing to the participants; the application provides an efficient and accurate logical time management mechanism, and solves the problem that the middleware of the existing joint test platform does not support logical time management.

The embodiment of the invention provides a seismic phase signal pickup method based on time window length transformation, and the method comprises the steps: S1, calculating the theoretical travel time of a seismic phase, and calculating the theoretical arrival time of the seismic phase through a ray tracing method; s2, selecting a time window length, setting a time window at the theoretical arrival time, and determining initial actual arrival time through a time domain long and short window method; and S3, changing the length of the time window, reducing the scale of the time window, setting the time window at the initial actual arrival time, and determining the final actual arrival time through a time domain long and short window method. According to the embodiment of the invention, the pickup precision is high, the seismic phase signals can be extracted more accurately by combining the theoretical travel time and the long and short window method, especially in complex or low-signal-to-noise-ratio seismic data, misrecognition or missed recognition can be reduced, the automation degree is high, automatic extraction of the seismic phase signals can be realized, manual intervention is reduced, and the efficiency is improved. A large amount of time and labor cost are saved, and the working efficiency is greatly improved.

Disclosed in the embodiments of the present disclosure are a non-terrestrial communication method and apparatus. The method comprises: acquiring, at the current time step, the data transmission rate between each terminal among at least one terminal and a network device; inputting state information at the current time step into a first model, so as to obtain a first action executed by the network device in the state of the current time step, wherein the first action is used for indicating the displacement of the network device at the current time step; and on the basis of the first action, determining the position of the network device at a subsequent time step, wherein the first model is used for determining the position of the network device at each time step within a first period, and the total data transmission rate of the at least one terminal is the largest within the first period. Thus, a network device can move rationally even when a terminal is moving, thereby effectively ensuring the throughput of a system, making the system achieve communication with a short delay and a high data rate, and improving the communication efficiency of the system.

To provide a technique capable of integrating history data in the order of occurrence in actual time even when integrating history data in which a plurality of time returns exist.SOLUTION: According to an embodiment, an information processing device includes an interface configured to acquire first history data and second history data in which process data of a device and a time stamp are stored in respective rows, and a processor configured to arrange the first history data and the second history data in order of index numbers assigned to the respective rows, determine whether a time of an n-th row of the first history data is later than a time of an m-th row of the second history data, insert the m-th row between the n-th row and an (n-1) - th row when it is determined that the history data of the n-th row is later than the time of the m-th row, and assign new index numbers to respective rows of third history data generated by inserting the second history data into the first history data in order of arrangement.SELECTED DRAWING: Figure 1

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting agent response times. One of the methods includes continually updating, at each time step of a plurality of time steps, an accumulated measure of surprise for the agent due to the movements of another entity in the traffic environment. A distribution of previously predicted trajectories is obtained at a previous time step for the other entity in the environment. A measure of surprise is computed from the perspective of the agent. An accumulated measure of surprise is updated for the time step using the computed measure of surprise for the agent. If the accumulated measure of surprise crosses a threshold at a particular point in time, a predicted response time for the agent is generated based on the particular point in time that the accumulated measure of surprise crosses the threshold.

The application provides a kind of embedded device system time synchronization method and system based on multiple bus interfaces, comprising: step 1: listening to data packet in various bus interfaces corresponding to each slave device;Step 2: analyzing data packet, extracting command code, obtaining interface identification of corresponding bus interface;Step 3: binding command code and interface identification and storing in list according to listening order;Step 4: traversing list, corresponding response is carried out according to command code type;Step 5: when command code type is time request, the system time of master device obtained is sent to slave device according to interface identification corresponding interface;Step 6: listening to data packet sent by master device;Step 7: analyzing data packet, extracting time for time;Step 8: time for time response is carried out according to time for time;Step 9: after slave device completes time for time, sending time for time completion data packet to master device.The application has high universality and expansibility, and reduces development cost.

Methods and apparatus are proposed for computing a power reduction policy to control radio emissions of a base station over a time window, with the objective to keep the time-averaged radio emissions over the time window below an authorized value set by regulations, with minimum impact on the performance of the overall system. The time window is subdivided into a plurality of time periods starting at a plurality of time steps, and the policy control comprises, at least at a first time step in the time window: generating a predicted average radio emissions over subsequent time periods in the time window, based on radio emissions historical data; finding couples of values of a power reduction factor and an average radio emissions that minimize a cost function for each time step in the time window, based on the predicted average radio emissions.

The invention relates to a nuclear power digital twin multi-model engine time synchronization method and system. The method comprises the following steps: S1, establishing a global time reference, so that all model engines perform state updating and event triggering based on the same time reference; and S2, under the global time reference, setting a fixed time step length for all model engines so as to ensure synchronization and model engine calculation and interaction cycle alignment. Wherein the interaction cycle refers to a complete work cycle which must be completed by the model engine within a time step length. And S3, performing timestamp marking on events and communication data generated by all the model engines, and performing queue management on the events and the communication data according to timestamps. And S4, optimizing loading durations of all model engines based on a parallel loading mode and a resource pre-allocation mechanism. The method is used for dynamic interaction of multiple model engines in a nuclear power digital twin platform, global time logic consistency can be ensured, and model collaboration efficiency and real-time performance are improved.

A method (70) for implementing a surface code measurement circuit (50) on a lattice (46) of qubits (14) of a Margarner four-terminal lattice (66, 68) includes: assigning (70A), in a sequence of time steps, a set of single qubit projection measurement loops on each of three auxiliary qubits (14A) of the lattice; allocating (70B), in a sequence of time steps, a set of dual qubit projection measurement loops on each of the four data qubits (14D) of the lattice together with one of the three auxiliary qubits; allocating (70C), in a sequence of time steps, a set of dual qubit projection measurement loops on two or more pairs of auxiliary qubits selected from the three auxiliary qubits of the lattice; and advancing (70D) to traverse each of the time steps of the sequence, performing the allocated single-qubit projection measurement and dual-qubit projection measurement therein. In the method, a measurement circuit corresponds to a stabilizer of a surface code, and a measurement that generates a stabilizer operator is measured.

Techniques for utilizing adjusted timestamps and updated hardware internal timers to drive sensor data (e.g., camera and / or video frames) are discussed herein. Timestamps can be adjusted to be adjusted timestamps based on simulation times and adjustment times. The adjustment times can include delays associated with frames being driven out of buffers. The adjustment times can further include delays associated with frames propagating through simulation devices. Internal timers can be updated to be updated timers based on numbers of timesteps between signals of primary clocks.

The invention provides a path planning method and device, a program product and a storage medium. In the method, a deep learning model comprises an encoder and a decoder; the encoder is used for generating a node-embedded graph embedding containing each node according to the graph structure; the decoder is used for predicting a prediction node yt of the tth time step at the tth time step so as to obtain a distribution path of the prediction node containing each time step; the method comprises the following steps: after the decoder predicts the prediction node yt, updating the predicted commitment time of the prediction node yt; and updating node embedding of the prediction node yt and updating graph embedding based on the updated predicted commitment time of the prediction node yt, so that the decoder executes prediction of the prediction node yt + 1 at the (t + 1) th time step according to the updated graph embedding and the updated node embedding of the prediction node yt.

This application discloses a method and related apparatus for predicting channel time series at future times. The method includes: firstly, acquiring the channel time series at M times to obtain X(t) m )={x n (t m Let X(t) = |m=1,2,…,M} (n=1,2,…,N), where N is the number of channel time series within a given time moment, and M and N are both positive integers. Next, based on the stated X(t)... m )={x n (t m Construct a mapping Ψ for each m = 1, 2, ..., M (n = 1, 2, ..., N). p , among which, Ψ p (X(t m ))=x n (t m+p‑1 (p=2,3,…,L), where L-1 is the number of time steps to be predicted, and X(t) is used as the time step to be predicted. m (m=1,2,…,M-p+1) as input, with x n (t m+p‑1 Using (m=1,2,…,M-p+1) as the output, we perform a Gaussian process regression (GPR) fitting to obtain Ψ. p (p = 2, 3, ..., L). Finally, X(t) m (m = M - p + 2, M - p + 3, ..., M) respectively input the Ψ p (p = 2, 3, ..., L), we get x n (t m+p‑1 This application generates predicted values ​​for (n = 1, 2, ..., N; m = 1, 2, ..., M; p = 2, 3, ..., L), thus achieving multi-step prediction of channel time series. Compared with existing single-step prediction, this application does not accumulate or amplify errors during the prediction process, resulting in more accurate prediction results.

Embodiments of the present specification provide a diffusion model processing method and device, a picture processing method and device, wherein the diffusion model processing method comprises determining a time step set of a diffusion model and a time step interval corresponding to the time step set; determining a first time step from the time step set and determining a target time step corresponding to the first time step according to the time step interval; inputting a noisy picture corresponding to the first time step and the target time step into the diffusion model to obtain predicted noise corresponding to the noisy picture; and processing the diffusion model according to target noise corresponding to the noisy picture and the predicted noise. The method divides the time step set into time step intervals, and during subsequent diffusion model training, the diffusion model shares time step conditions within a time step interval, i.e., the first time step shares the target time step within the corresponding time step interval, thereby reducing the time step condition, greatly reducing the training burden, and improving the model training performance.

A computer-implemented method for determining a mean and variance of measurement data comprises the following steps performed by a computer hardware component: acquiring measurement data for a current time step using a sensor; updating the plurality of intermediate data for the previous time step based on the measurement data for the current time and based on the forgetting factor to obtain a plurality of intermediate data for the current time step; and determining an average value and a variance for the current time step based on the plurality of intermediate data for the current time step.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting agent response times. One of the methods includes continually updating, at each time step of a plurality of time steps, an accumulated measure of surprise for the agent due to the movements of another entity in the traffic environment. A distribution of previously predicted trajectories is obtained at a previous time step for the other entity in the environment. A measure of surprise is computed from the perspective of the agent. An accumulated measure of surprise is updated for the time step using the computed measure of surprise for the agent. If the accumulated measure of surprise crosses a threshold at a particular point in time, a predicted response time for the agent is generated based on the particular point in time that the accumulated measure of surprise crosses the threshold.

The invention provides a GPU architecture simulation method and device, computer equipment and a medium, and relates to the technical field of hardware simulation, the simulation method comprises the following steps: monitoring operation indexes of a plurality of function modules in a preset time window; calculating a hotspot score of the function module according to the operation index; for each functional module, comparing the hotspot score of the functional module with a preset threshold value, and determining a simulation mode adopted for the functional module based on a comparison result; in response to determining that the fine simulation mode is adopted to simulate the functional module, updating an internal state machine of the functional module cycle by cycle; and in response to determining that the fast forward simulation mode is adopted to simulate the functional module, deriving an equivalent delay of the functional module, and crossing the corresponding simulation time step length based on the equivalent delay to skip updating of the internal state machine of the functional module period by period within the simulation time step length. The simulation overhead is reduced, and the overall simulation speed is increased.

The invention relates to a method, computer program and machine readable storage medium for planning the operation of a technical system in its environment. A computer implemented method for planning the operation of a technical system in its environment. The method comprises the steps of: i) obtaining state information comprising: a current domain, a time step and a current state; ii) determining the cost of reachable states from the current state by a heuristic method; iii) selecting a heuristic method from a predefined set of heuristic methods according to a policy depending on the state information and the cost; iv) selecting a state from the reachable states with the lowest cost returned by the selected heuristic method, and v) determining the operation of the technical system from the set of possible operations that the technical system has to perform to reach said state with the lowest cost returned by the selected heuristic method.

The application provides a dead time adjusting method, an adaptive ZVS control method and a switching power supply, comprising the following steps: 11) obtaining a first time length, collecting a second time length of a current period, and comparing the first time length with the second time length; 12) if the first time length is greater than the second time length, reducing the conduction time of a clamping tube by a preset time length in the next period; if the first time length is less than the second time length, increasing the conduction time of the clamping tube by the preset time length in the next period; if the first time length is equal to the second time length, keeping the conduction time of the clamping tube in the next period; and 13) returning to step 11) to adjust the dead time between the clamping tube and the main switch in each period. The application can accurately realize adaptive control of the dead time between the upper clamping tube and the main switch tube in a full load range, has high safety, small loss of the main switch tube, high system efficiency, and wide application range.

The invention discloses an atomic clock control method, device and equipment, a storage medium and a computer product, and relates to the technical field of atomic clock control, and the method comprises the steps: determining an operation temperature sequence of an atomic clock in a slidable time window and an atomic clock type when the atomic clock is in a holding stage; calling a corresponding punctuality model based on the atomic clock type and the temperature interval in which the operating temperature sequence in the slidable time window is located; inputting the operating temperature sequence in the slidable time window into the timekeeping model to obtain a predictive control word of the atomic clock in the next time step of the last time step in the slidable time window; and performing frequency correction on the atomic clock based on the predictive control word. The timekeeping precision of the atomic clock in the keeping stage is improved.

The invention relates to the technical field of cloud computing, and particularly provides a container migration method and device, equipment, a storage medium and a program product. The method comprises the following steps: under the condition that the current resource utilization rate of at least one dimension resource in a plurality of dimension resources of a to-be-migrated container is greater than or equal to a preset resource utilization rate, acquiring a resource utilization sequence of the plurality of dimension resources in a preset historical time period; determining the coding attention weight of each resource utilization sequence in a plurality of time steps by using the coding attention layer; processing each resource utilization sequence at each time step based on the coding attention weight by using a coder to obtain a coding hiding state of each time step; determining the decoding attention weight of each time step based on the coding hidden state of each time step by using the decoding attention layer; processing the coding hidden state of each resource utilization sequence at each time step by using a decoder based on the decoding attention weight to obtain a predicted resource utilization rate of each time step; and under the condition that the predicted resource utilization rate of the at least one resource utilization sequence in the last time step is greater than the preset resource utilization rate, migrating the to-be-migrated container to a target node in the plurality of nodes. According to the invention, unnecessary migration of the container is reduced, and fine scheduling of resources is realized.

A method executable by one or more processors includes: obtaining a measurement of a first variable at a current time step; using a first model to estimate a second variable at the current time step based on the measurement of the first variable; generating a control decision for a subsequent time step based on the measurement of the first variable and the estimate of the second variable using a reinforcement learning model; using a second model to predict a predicted value of the first variable for a subsequent time step based on the measurement of the first variable at the current time step; adjusting the control decision for the subsequent time steps based on constraints and future values ​​of the first variable; and controlling an actuator based on the control decision.

The application relates to a circuit breaker opening time determination method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: obtaining a control resultant force by using an electromagnetic repulsive force simulation component according to an initial air gap size of an electromagnetic repulsive force simulation model at a current time step, and sending the control resultant force to a circuit breaker operating simulation component; obtaining an air gap size generated by taking the control resultant force as a load force of a circuit breaker operating simulation model at the current time step by using the circuit breaker operating simulation component; in the case that it is detected that a repulsive force disc does not reach a preset position, sending the air gap size to the electromagnetic repulsive force simulation component, updating a next time step to the current time step, and returning to a resultant force updating step until the repulsive force disc reaches the preset position; and taking the current time step when the repulsive force disc reaches the preset position as the opening time. The method can accurately determine the circuit breaker opening time.

The embodiment of the invention provides a robot motion control method and device and a storage medium, and belongs to the technical field of robot control. The method comprises the following steps: in response to a received speed adjustment request, determining a speed adjustment coefficient at a preset target position; according to the speed adjustment coefficient, determining an interpolation duration step pitch of a current instruction issuing period to be planned; and according to the interpolation duration step pitch and a preset initial planning track, determining motion control parameters of the instruction issuing period to be planned, and after the motion control parameters of all the planned instruction issuing periods are issued to the target robot, sending the instruction issuing period to the target robot. The actual speed of the target robot is the speed adjustment coefficient times of the planned speed at the same position on the initial planned trajectory. According to the embodiment of the invention, speed adjustment can be performed based on the original trajectory of the robot.

A result of a qubit reading operation is determined by obtaining a photon detection count for a time step of the qubit reading operation performed on a qubit; based at least in part on the photon detection count for the time step, determining whether a bright threshold criteria is satisfied and / or determining whether a dark threshold criteria is satisfied. Responsive to determining that the bright threshold criteria is satisfied, and indication that the qubit is in a bright state is stored. Responsive to determining that the dark threshold criteria is satisfied, an indication that the qubit is in a dark state is stored. Responsive to determining that neither the bright threshold criteria nor the dark threshold criteria is satisfied, it is determined that a state of the qubit is undetermined.