50 results about "Time estimation" patented technology

The invention discloses a foundation pit support deformation real-time monitoring method based on edge calculation, and aims to solve the problems of multi-node time synchronization and clock drift compensation caused by unavailability or poor quality of satellite navigation and precise time protocols in an underground or shielded environment. According to the method, through event dictionary learning, partition time slot scheduling and safety coding micro excitation time synchronization, matched filtering decoding, multi-scale arrival time estimation, paired time difference robust fusion, frequency priority and phase speed limit correction and network disconnection time holding, the time synchronization efficiency is improved; the technical effects that multi-source data alignment, deformation field reconstruction and graded early warning are completed on the unified virtual reference time scale, and high-precision synchronization and online drift compensation are obtained without depending on the external time service condition are achieved.

The invention discloses an SLAM-oriented multi-sensor space-time synchronization and online calibration method, and relates to the technical field of computer vision and robot perception. Comprising the steps that S100, initialization is carried out, and an initial pose and an external parameter transformation matrix initial value are obtained through coarse alignment; s200, data acquisition and preprocessing: acquiring IMU data, LiDAR data and Odom data in real time, and performing data filtering, distortion removal, time sequence correction and point cloud downsampling processing on the acquired data; and S300, performing time synchronization processing, estimating the time offset of the LiDAR and Odom data in real time, and performing unified correction to generate a unified timestamp. According to the method, an online time offset estimation and compensation mechanism with an IMU as a main clock is established, accurate synchronization of sensor data of different frequencies is achieved, and the problem of data alignment caused by sampling frequency difference and clock drift is effectively solved; and meanwhile, tight coupling fusion is realized by using an IMU pre-integration factor, a LiDAR residual factor and an Odom constraint factor, so that the space-time consistency of multi-sensor data is remarkably improved.

The present invention relates to a sitting time estimation system, a sitting time estimation program, and a sitting time estimation method that can estimate sitting time according to the user's lifestyle. [Solution] The sedentary time estimation system according to the present invention is a sedentary time estimation system that estimates the time a user spends sitting, and comprises a lifestyle information acquisition unit, a sedentary time calculation unit, and a sedentary time presentation unit. The lifestyle information acquisition unit acquires the user's lifestyle schedule and the activity intensity for each lifestyle scene in the lifestyle schedule. The sedentary time calculation unit calculates the user's sedentary time based on the activity intensity for each lifestyle scene. The sedentary time presentation unit presents the user's sedentary time to the user.

By a communication device, a line delay time estimation method, a non-transitory computer-readable storage medium storing a line delay time estimation program, a communication packet is accumulated, a data amount of the communication packet is monitored, and a residence time, which is a duration and for which the communication packet remains in a transmission buffer, is estimated as an upstream buffer delay time from the communication device to a counterpart device.

The invention belongs to the technical field of power distribution network energy efficiency analysis, and provides a real-time estimation method and system for additional loss of a distribution transformer based on quantile envelope and dynamic characteristics. According to the method, real-time electrical data and rated electrical data of a transformer are fused, a reference loss envelope model is accurately fitted in a strong noise environment by adopting a low-quantile envelope regression technology, and an optimal nonlinear mapping relation of a self-adaptive learning load rate of a mechanism is constructed in combination with dynamic adjustable index features; and continuously tracking the state change of the distribution transformer based on a sliding window retraining trigger mechanism, and finally realizing real-time stripping and quantification of an additional loss component, namely dynamically calculating instantaneous non-negative additional loss and time cumulant thereof. And a high-precision, self-adaptive and landing quantitative decision basis is provided for harmonic pollution treatment and energy-saving optimization of core energy consumption equipment.

The application discloses a time delay control method and system based on an error compensation type extended state observer, which comprises the following steps: a time delay controller acquires input signals and each output state of a tracking differentiator, and outputs a first control signal; an estimation error model of a displacement is constructed for an extended state observer; based on the first control signal, a total disturbance signal and an estimation error of the extended state observer, a controlled object is converted into an integrator series type form, and a displacement signal is output based on the controlled object; the displacement signal is input into the tracking differentiator to obtain real-time estimation values of each state of a nano-positioning stage; and the real-time estimation values of each state are fed back to the time delay controller. By introducing the extended state observer, the application solves the problem that the stability of a control system is easily affected by the uncertainty of a control input matrix; by introducing the tracking differentiator, the application solves the difficult problem that high-order system states and their derivatives required by time delay control are not easy to obtain.

The present application belongs to the technical field of water rescue, and particularly relates to an air-water collaborative full-autonomous anti-drowning rescue method, system and readable storage medium. The air-water collaborative full-autonomous anti-drowning rescue method plans the paths of the water surface and the flying life buoy at the same time, compares the time consumption, and selects the fastest rescue mode, thereby solving the poor collaboration and low efficiency of the traditional single rescue mode and maximizing the rescue time. The intelligent path planning can adapt to complex environments by using sensing information as the basis for path planning, thereby improving the accuracy of time estimation and the efficiency of time estimation and further shortening the rescue time.

The invention relates to the technical field of vehicles, in particular to a charging remaining time estimation method and device, a vehicle, a storage medium and a program. The method comprises the steps that battery characteristic parameters and charging pile characteristic parameters of a vehicle are obtained, and the battery characteristic parameters comprise the current battery temperature and the current state of charge; on the basis of a preset optimal charging temperature interval, the charging heat management duration of the vehicle is calculated according to the current battery temperature, and the battery characteristic parameters and the charging pile characteristic parameters are input into a pre-established charging time prediction model to obtain estimated charging duration; and according to the charging heat management duration and the estimated charging duration, obtaining the final residual charging duration of the vehicle. Therefore, the problems that in the prior art, estimation deviation is large, user experience and credibility are damaged, complex application scenes are difficult to deal with, and user anxiety is aggravated are solved.

The invention provides a CNN reasoning task time slice segmentation method and system based on a divisible tuple, and relates to the technical field of data processing. The CNN reasoning task is decomposed into sequentially executed BMO sequences, and continuous BMO is combined into tuples based on data dependence; based on the time estimation model of the tuple, segmenting the tuple according to the length of the target time slice to generate sub-tuples; wherein the segmentation is divided according to data dimensions and is rounded down to a minimum divisible unit; tuples or sub-tuples are selected from the tuple list to be combined into the time slice, the total execution time does not exceed the length of the target time slice, memory allocation is managed in a unified mode before the time slice is executed, and the memory is released in a unified mode after the time slice is executed. Performance modeling and time prediction are carried out according to CNN model operation characteristics, the task is divided into time slices to support time division multiplexing scheduling, and the real-time performance, the resource utilization rate and the hardware universality are improved.

The present application belongs to the technical field of power distribution network energy efficiency analysis, and provides a real-time estimation method and system for distribution transformer additional loss based on quantile envelope and dynamic characteristics. The present application fuses real-time electrical and rated electrical data of the transformer, adopts low quantile point envelope regression technology to accurately fit the benchmark loss envelope model in a strong noise environment, combines a dynamic adjustable exponential characteristic construction mechanism to adaptively learn the optimal nonlinear mapping relationship of the load rate, and continuously tracks the state change of the distribution transformer based on a sliding window retraining trigger mechanism, finally realizes real-time stripping and quantification of the additional loss component, that is, through dynamic calculation of the instantaneous non-negative additional loss and its time cumulative amount, provides high-precision, adaptive and implementable quantitative decision basis for harmonic pollution control and energy saving optimization of core energy-consuming equipment.

A front end unit (13) generates, from a functional description indicating one or more functions of software written in a natural language, a code generation prompt instructing the generation of source code that implements the one or more functions, and enters the prompt into a code generation model (11), which is a learning model. An execution time estimation unit (12) estimates the execution time of the source code generated by the code generation model (11) in response to the prompt entered by the front end unit (13).

The invention relates to a method for improving the dustpan filling rate of a bucket elevator. The method comprises the steps that dustpan filling images and equipment data are obtained in real time through a sensor network; transmitting the data to an edge AI calculation unit, performing millisecond-level reasoning by using a lightweight convolutional neural network model, estimating a filling rate in real time and identifying a material type; based on a reasoning result, dynamically and cooperatively adjusting operation parameters, including changing the geometric volume of the deformable intelligent winnowing pan through a micro driving mechanism, adjusting the speed of the elevator and controlling a feeding auxiliary device, and continuously optimizing decision logic of the system by a digital twin model, according to the model, an optimization strategy set is generated in advance through discrete element simulation and a Bayesian optimization algorithm, and the system has a maintenance function of predicting performance degradation by analyzing current and vibration data and can cooperate with upstream and downstream equipment to realize global energy efficiency optimization; according to the scheme, the problem that the filling rate of a traditional elevator is unstable due to variable materials and fixed bucket types is solved, and self-adaptive precise control is achieved.

The application relates to the technical field of artificial intelligence, and discloses a character setting following method and system for a role-playing intelligent agent in a decoding stage. The method comprises the following steps: for an input prompt word of a large language model, which comprises a context situation, a character setting attribute set and a user query, evaluating an importance score of each character setting attribute in the character setting attribute set under the context situation; based on the importance score, constructing a reward function for guiding the large language model to respond to a target character setting; and in the decoding reasoning stage of the large language model, using the reward function to dynamically adjust the probability distribution of the large language model in generating a word element at each time step, so that the generated response conforms to the target character setting under the context situation. Through real-time estimation of the importance of the character attribute and dynamic adjustment of the generation distribution in the reasoning process, the application can adaptively adjust the role performance according to different contexts and tasks, so as to generate an output that is more in line with the target character setting.

The invention discloses a temperature adjustment time estimation method based on adaptive learning, and the method comprises the steps: obtaining basic parameters of a liquid to be subjected to temperature adjustment, and calculating the total heat based on the basic parameters; acquiring a preset heat conductivity coefficient, and calculating initial estimated time according to the preset heat conductivity coefficient and the total heat; the current water temperature is detected again after a preset time interval so as to update the basic parameters, residual heat is calculated based on the updated basic parameters, and the preset heat conductivity coefficient is updated so as to obtain a target heat dissipation coefficient; and calculating target estimated time according to the residual heat and the target heat dissipation coefficient. The heating time and the refrigerating time can be estimated, and the use experience of a user is improved.

An input to schedule a future conference is received. The input identifies a list of topics and a total time scheduled for the future conference. Time allotments for the list of topics are determined based on historical conference data. The time allotments are scaled based on a total time weight indicative of the total time to generate scaled time allotments within that total time. A schedule item for the future conference is then updated to include the scaled time allotments for the list of topics

The invention discloses a task assignment method and system based on a task graph, and relates to the technical field of sparse linear equation set solver, and the method comprises the steps: calculating task processing time based on a time estimation model during task assignment; the number of completed tasks is initialized to be zero, the number of initial idle threads is initialized to be the number of total threads, and the tasks with the initial task state being in task waiting are put into a to-be-dispatched task sequence; executing a task assignment main cycle; when the initial idle thread number is greater than zero and the to-be-dispatched task sequence is not empty, distributing a thread number for the task; when the initial idle thread count is zero, determining the fastest thread based on the task processing time; when the to-be-dispatched task sequence is empty, traversing the task chain depending on the current task to obtain the dependent task of the current task, putting the dependent task into the to-be-dispatched task sequence, and executing the task dispatching main cycle, so that the problem that the task processing time cannot be accurately predicted and the thread resources cannot be uniformly distributed in the prior art can be solved.

Systems, methods, apparatuses, and computer program products for Rx-Tx RTT estimation are provided. One method may include transmitting, by a network element, the reference signal to another network element and recording a time stamp (t0) of a time of transmission of the reference signal, and receiving an estimated Rx-Tx measurement from said another network element and recording a time stamp (t3) of a time of receipt of the estimated Rx-Tx measurement. The method may also include calculating a Rx-Tx measurement at the network element based on a difference between the time stamp (t0) of the time of transmission of the reference signal and the time stamp (t3) of the receipt of the estimated Rx-Tx measurement, and determining a propagation delay based on a difference between the received estimated Rx-Tx measurement and the calculated Rx-Tx measurement.

The invention discloses a semiconductor equipment available time estimation method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring product demand data of the semiconductor equipment; based on the obtained product demand data, determining an available time estimation model corresponding to the semiconductor device; inputting the obtained product demand data into an available time estimation model corresponding to the semiconductor equipment, and estimating the available time of the semiconductor equipment; wherein the available time estimation model is obtained by training an initial available time model by utilizing historical maintenance related data and historical downtime related data of the semiconductor equipment under the condition that the product demand data has the same product combination with the product demand data. By adopting the scheme, the available time of the semiconductor equipment can be accurately estimated.

The application relates to a target frequency hopping period estimation method based on a rotation phase factor, and belongs to the technical field of signal processing. The method solves the problems of high operation complexity and frequency hopping period estimation error caused by error of a heap in the prior art. The method comprises the following steps: obtaining a frequency hopping signal, obtaining a signal relative time sequence according to an appearance time of the frequency hopping signal; establishing a full zero sequence according to a time duration of the frequency hopping signal and time estimation accuracy, and obtaining a unit pulse sequence according to the signal relative time sequence; taking out a shift value in a frequency hopping shift value range, obtaining a detection threshold according to the time duration of the frequency hopping signal; shifting the unit pulse sequence according to the shift value to obtain a unit pulse delay sequence, obtaining a detection result based on a rotation phase factor; if the detection result is greater than the detection threshold, the shift value is taken as a target frequency hopping period estimation value; and finally, the frequency hopping period estimation value of one or more targets in the frequency hopping signal is obtained. The method realizes fast period estimation of the frequency hopping signal.

The application discloses a high-performance file hash calculation method based on double-engine adaptive switching, relates to the technical field of data security, and aims to solve the problems that the existing scheme is mostly heuristic scheduling based on static threshold values or empirical rules, lacks residual time estimation and interval control based on online statistical learning, and lacks real-time detection of residual drift and adaptive scheduling based on evidence; the method comprises the following steps: constructing a high-dimensional vector by mapping observation characteristics, adopting joint modeling of recursive least squares with ridge regularization and quantile regression, providing point estimation and upper and lower bounds of single fragmentation and residual time consumption; fusing the extreme values of residual variance and quantile interval to obtain a robust interval, and using Page-Hinkley / CUSUM for mutation detection to trigger adaptive adjustment of fragmentation size, concurrency and engine type; and before engine switching, serializing internal working vectors, processed bytes and intermediate summaries and performing mirror checking to ensure consistency of cross-engine results.

The invention discloses a passing time estimation method, system and device combined with a large model and a medium, and the method comprises the steps: carrying out the embedding processing of the current latitude and longitude, the current pose, the front real-time image and the current precise time of a vehicle, and obtaining first embedded data; inputting the first embedded data into a cross attention encoder for processing to obtain optimized feature data; performing embedding processing on the current longitude and latitude, the current pose, the front real-time picture and the current accurate time through a hard cue word method to obtain second embedded data; splicing the second embedded data and the optimized feature data, and inputting the spliced feature data into a large language model to obtain a passage time predicted value; an interpretable cause of the transit time predicted value is generated through a large language model based on the front real-time picture and the transit time predicted value. According to the method, the problems that a traditional mode depends on static information and lacks multi-modal fusion and interpretability can be solved, and the passing time estimation precision and the result credibility are improved.

The invention relates to the technical field of electronic sphygmomanometer service life recording, in particular to an electronic sphygmomanometer service life automatic recording method which is achieved by executing stored software instructions through a built-in processor of equipment and comprises the steps that a current count value is initialized and read; defining and capturing a complete measurement action as a counting trigger condition; executing safe counting increasing and verification operation; synchronously correlating and recording temperature, humidity and voltage environment data; based on the number of times of use and the environment trend, the health degree is calculated through a life model, and early warning is generated; encrypting the synchronous data to the cloud; providing an administrator query and reset interface; and system self-inspection is executed regularly. According to the invention, each time of use is accurately recorded and analysis is carried out in combination with multi-dimensional environmental factors, so that the inaccuracy of traditional single time estimation is overcome, intelligent life prediction and maintenance reminding are realized, the reliability, safety and user experience of equipment are effectively improved, and meanwhile, the method has the advantages of low cost and easiness in popularization.

The invention provides a pharyngeal time estimation method based on a swallowing contrast video. According to the method, a fuzzy theory and a space-time modeling thought are combined, continuous modeling is carried out on a swallowing process by constructing a membership function of a pharyngeal period starting frame and a pharyngeal period ending frame, and fuzziness of a pharyngeal period boundary and continuity of time sequence changes are explicitly embodied. According to the model, a three-dimensional convolutional neural network (3D-CNN) is adopted to extract space and time features of a video, and a space-time attention mechanism is introduced to guide the model to pay attention to dynamic changes of a contrast agent in a swallowing process, so that correlation of feature representation is enhanced. Finally, the model outputs the membership degree value of the pharyngeal period starting frame and the pharyngeal period ending frame of each frame, a continuous time curve is formed, and accurate estimation of the pharyngeal period starting and ending moments and the duration time is achieved.

The application provides an etching time estimation device and method for a swing plate flat bridge, which comprises a fixing assembly, a thrust loading unit, a first pressure collecting unit and a data processing unit; the fixing assembly comprises a base and a first fixing seat for fixing a swing plate and a second fixing seat for fixing the thrust loading unit, which are arranged on the base respectively; the thrust loading unit comprises an open shell and a slider and a servo motor arranged in the shell; the servo motor is used to push the slider to slide from a first preset position to a second preset position; the first end of the first pressure collecting unit is connected with the second end of the slider, and the second end is in contact with the center swing of the swing plate; the first pressure collecting unit is used to collect a pressure value when the slider is in the second preset position; and the data processing unit is used to obtain the etching time of the swing plate flat bridge according to the pressure value. The application can solve the technical problems of long time consumption and poor measurement accuracy of the swing plate flat bridge etching method in the prior art.

The objective is to provide a sensor system, a transmitting terminal, and a transmitting method that can suppress the decrease in time estimation accuracy. [Solution] The sensor system of the embodiment comprises one or more sensors, one or more transmitting terminals, and a data collection device. The one or more transmitting terminals comprises a first communication unit and a second communication unit. The first communication unit wirelessly transmits first transmission data, which includes time information used for time estimation, to the data collection device. The second communication unit wirelessly transmits second transmission data, which includes information obtained based on the physical quantities detected by one or more sensors, to the data collection device at a frequency different from the frequency used by the first communication unit. The data collection device comprises a reception time determination unit and a time information processing unit. The reception time determination unit determines the reception time of a plurality of the first transmission data transmitted from the first communication unit. The time information processing unit performs time estimation based on the plurality of the first transmission data and the plurality of reception times.

The invention particularly relates to a field-of-view-limited intersection time and angle constraint-considered three-dimensional guidance law design method, which comprises the following steps of: constructing a mapping relation between a speed angle and a sight angle, and deducing a corresponding relation between a front angle and a measurable angle; designing a rendezvous time and angle constraint guidance model without remaining time estimation, and converting a field angle constraint into a state constraint; and based on the guidance model, designing a three-dimensional guidance law considering the view field-limited intersection time and angle constraint. According to the method, sliding mode control is adopted, the guidance robustness can be improved, remaining time estimation is not needed in the guidance law, the time constraint precision is improved, field angle constraint is achieved through state constraint, and the guidance singularity phenomenon is effectively avoided.

The invention discloses a real-time estimation method and system for pump performance, and the method comprises the following steps: an offline parameter identification stage: obtaining sparse test data (including flow, lift and power) of a pump unit under different frequencies, and building a performance curve equation under a reference frequency; through a generalized similarity law, a parameterized scaling factor function k (r) is constructed by a normalized frequency ratio r, and an analysis form and a coefficient of the parameterized scaling factor function k (r) are optimized and identified. In the online stage, the operation frequency and an operation parameter (lift or power) are obtained in real time, rfield is calculated and substituted into k (r), and a scaling factor is obtained; and generating a current accurate performance curve in real time by combining the reference curve, and substituting the measured value to analyze and solve other target parameters. According to the method, the constitutive property of a physical model and the flexibility of data driving are fused, the unification of high precision, zero storage, low delay and strong robustness is realized, and an important breakthrough of a pump unit virtual sensing technology is represented.

The invention relates to the technical field of task control, and discloses a task control system for high-speed printing, and the system comprises a state monitoring unit which is used for collecting a job queue load capacity and a task completion time estimated value, and calculating a backpressure hysteresis state index based on the mapping distribution of the two values in a historical window; the parameter adjusting unit is used for converting the backpressure hysteresis state index into a system compensation gain coefficient; and the cooperative control unit is used for responding to the system compensation gain coefficient, synchronously adjusting the scoring weight of task scheduling sorting, the rasterization processing parallelism degree and the cache resource quota, and generating an updated task completion time estimated value in combination with the real-time transmission rate of a data channel and a data flow supply continuity index. According to the method, the backpressure hysteresis effect of the system under multi-task concurrence can be quantified and compensated, and while stable supply of data streams is ensured, the precision of job completion time estimation and the adaptability of a scheduling strategy are improved.

According to an embodiment, a computer-implemented method for managing voice call initiation comprises: performing at least one voice call according to a preconfigured script, wherein the preconfigured script comprises a plurality of steps; obtaining, during the at least one voice call, a time estimate for performing at least one step of the plurality of steps of the preconfigured script; computing, during the at least one voice call, a remaining time estimate for each voice call in the at least one voice call based on the time estimate for performing the at least one step of the plurality of steps of the preconfigured script; and determining whether to initiate a new voice call during the at least one voice call according to the remaining time estimate of each voice call in the at least one voice call.

The invention provides a method and a device for estimating in-station transfer time of a vehicle. The method comprises the following steps of: acquiring time-space information of arriving and departing vehicles on the basis of a transfer time estimation request from a user side; and obtaining the latest arrival position, arrival time, departure position and departure time of the vehicle by querying the scheduling time table, and determining an optimal transfer path through a preset path planning algorithm in combination with the operation state of the infrastructure in the transfer station and the transfer path topology model. And calculating a people flow density coefficient and a channel sensitivity coefficient by dynamically collecting people flow density and channel width data, and correcting the basic passing time to obtain the estimated passing time. And accumulating the pre-estimated passing time and the fixed flow time consumption of each infrastructure, calculating the pre-estimated transfer time, comparing the pre-estimated transfer time with the actual available transfer time, and judging the feasibility of transfer. According to the method, the problem of insufficient timeliness of static data estimation in the prior art is effectively solved, and the accuracy and the real-time performance of transfer time estimation are remarkably improved.