98 results about "Time estimation" patented technology

A system for multi-stage planning of construction processes and resource allocation, consisting of: a central planning engine configured to receive input data, including architectural design models, structural constraints, procurement schedules, and historical performance indicators; a task decomposition processor that is operationally connected to the central planning engine and configured to generate a hierarchical construction task graph by decomposing macro-level construction milestones into mid-level and micro-level subtasks, with each subtask having time estimates, location identifiers, resource requirements, and mutual dependencies; a hybrid planning processing unit configured to resolve time and resource constraints across the entire task diagram; a resource coordination controller that is operationally connected to the central planning engine, wherein the resource coordination controller includes a real-time database of work units, machines and material stocks, each resource being tagged with attributes such as availability, usage history, operating status and spatial location; a multitude of distributed execution units distributed across the construction zones, each distributed execution unit comprising an embedded controller, sensor interfaces, task status processing logic, and communication circuitry, each distributed execution unit being configured to receive planning instructions from the central planning machine, execute localized control logic for task confirmation and resource activation, and transmit task execution data back to the central planning machine; an adaptive conflict resolution processing unit that is operationally connected to the central planning engine and configured to detect conflicts in task execution or resource conflicts, simulate alternative task-resource allocation scenarios using a real-time multi-agent model, and autonomously update the task graph with revised task sequences and resource allocations; and A dashboard for the construction process, configured to visualize task progress, deviations from the planned schedule, and resource efficiency metrics, with the dashboard also being able to receive manual override inputs or approve automated conflict resolution proposals generated by the adaptive conflict resolution module.

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 relates to the technical field of power generation, and discloses a wind turbine generator fault early warning method and system based on multi-model combination, and the early warning method comprises the steps: 1, data collection; step 2, establishing an early warning model; 3, real-time monitoring and early warning are carried out; step 4, analyzing a fault source; step 5, estimating fault existence time; and step 6, fault subsequent condition prediction. According to a fault source analysis result, historical fault data and current operation data are combined through the system, the fault existence time is estimated, the prediction model is utilized, the system can not only predict the fault expansion speed, but also predict the influence degree of the fault on the unit performance, and therefore a more effective coping strategy is formulated, and the unit performance is improved. The beneficial effects of early warning the fault of the wind turbine generator and analyzing the fault source 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 embodiment of the invention discloses a printing time estimation method and device for additive manufacturing, equipment and a medium. The printing time estimation method for additive manufacturing can comprise the steps that reference printing time based on a reference piece is decomposed into reference energy output time and reference additive time; determining target energy output time according to the reference energy output time, the geometric attribute ratio of the reference piece to the target piece and the quantity ratio of the energy input devices; determining the target additive time of the target piece according to the reference additive time and the physical structure size ratio of the reference piece to the target piece; and the target printing time of the target piece is determined according to the target material increasing time and the target energy output time.

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.

A computing device having a host system coupled to a memory sub-system. The host system runs a garbage collection manager and a plurality of storage space tenants. The garbage collection manager can: write, to the memory sub-system according to a protocol of flexible direct placement (FDP), data of the plurality of storage space tenants to a reclaim unit in the memory sub-system; identify, after a first portion of the data stored in the reclaim unit is invalidated, first storage space tenants having a second portion of the data remaining valid in the reclaim unit; communicate with the first storage space tenants to identify estimates of expiration time of the second portion; and select, based on the estimates, the reclaim unit for acceleration of invalidation of the second portion of the data.

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 invention discloses an unmanned aerial vehicle positioning method and device, a medium and a product, and relates to the field of unmanned aerial vehicle positioning. An electromagnetic wave signal emitted by the unmanned aerial vehicle is received at each reconnaissance site, and an IQ signal with a timestamp is obtained through digital signal processing; then estimating the absolute time of signal arrival at each reconnaissance site by using a time estimation method based on a Zadoff-Chu sequence; and finally, the absolute time estimated by each reconnaissance site is uploaded to an upper computer system, and the position of the unmanned aerial vehicle is calculated in the upper computer system by using a TDOA method. According to the method, the Zadoff-Chu sequence contained in the unmanned aerial vehicle signal frame is used for positioning, and the method is simple and efficient; and meanwhile, the specific CP sequence characteristic of the OFDM signal segment is utilized, so that the time delay estimation precision is improved, and the positioning precision of the unmanned aerial vehicle is further improved.

The invention discloses an ammunition automatic filling robust control method based on singular system IL disturbance estimation, and aims to solve the problems of flexible transmission, parameter uncertainty, periodic external disturbance, residual vibration and the like in an automatic filling system. According to the method, a fast-slow dual-time-scale cooperative control architecture is constructed, a slow subsystem adopts a disturbance self-adaptive PD controller, low-frequency periodic disturbance is estimated and compensated online in combination with an iterative learning mechanism, and the trajectory tracking precision is improved; the fast subsystem carries out real-time estimation and feedforward suppression on high-frequency elastic vibration based on an extended state observer (ESO); and filtering and amplitude limiting are further carried out on slow and fast control inputs, a self-adaptive scheduling strategy based on tracking errors is designed, and the slow and fast control inputs are dynamically fused to generate a final control instruction. According to the method, only motor end position / speed measurement is needed, a load end sensor is not needed, high precision, high robustness and excellent vibration suppression capability are achieved, and the dynamic performance and complex condition adaptability of automatic ammunition filling are remarkably improved.

This processing time estimation method includes: allocating a plurality of tasks in an automated warehouse to each of a plurality of transport devices; generating a plurality of divided travel routes for each transport device by dividing, at a predetermined first time interval, an entire travel route during processing of the tasks for each transport device into N sections; and, for each of the N sections, executing input, to a trained model capable of outputting an estimated travel time for a divided travel route in a predetermined section for each transport device, of a divided travel route in an n-th section for each transport device, a map, and the first time interval.

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 audio loading, and discloses a USB media file loading method and system, a storage medium and equipment, and the method comprises the steps: detecting equipment connection and initializing a pre-scanning process when USB storage equipment is inserted into the system; the method comprises the following steps: quickly pre-scanning a USB storage device, acquiring basic information of media files through a lightweight file system traversal algorithm, and counting the number and types of the media files; based on a pre-scanning result and historical loading data, establishing a time prediction model to estimate loading time, and formulating a loading priority strategy; in the loading process, multi-level progress information including the overall progress, the classification progress and the real-time state is displayed to the user, and dynamically updated remaining time estimation is provided; according to the method, the loading of the media file is executed according to the loading priority strategy, and result verification and cache management are performed after loading is completed, so that intelligent pre-scanning and optimized loading of the USB media file are realized, and the practicability and user satisfaction of the system are improved.

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.

The invention belongs to the field of TOA tracking, and discloses a 5G signal arrival time robust tracking method and system based on a challenge environment, and the method comprises the steps: carrying out the synchronization and pilot frequency information extraction of a 5G downlink broadcast channel (PBCH); cSI measurement and denoising are carried out; and estimating the time of arrival. According to the invention, based on a dual noise reduction mechanism of CSI, time domain smoothing and frequency domain processing are combined, so that the quality of low-signal-to-noise-ratio signals is remarkably improved. An SAGE algorithm and delay phase-locked loop collaborative architecture is introduced, accurate separation of multipath components and dynamic phase-locked optimization are achieved, complex environment interference is effectively inhibited, and TOA tracking precision is improved by more than 30%. According to the invention, a reliable solution is provided for high-precision positioning in a complex environment.

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 embodiment of the present application provides a kind of electric vehicle charging residual time estimation method, system and storage medium, belong to electric vehicle technical field.The estimation method includes: obtaining the current SOC of battery module, each sampling point temperature and current actual charging current;Determine whether the current SOC is less than the first SOC threshold value;In the case where it is judged that the current SOC is less than the first SOC threshold value, judge whether it is the first time to obtain, current SOC or each sampling point temperature changes;In the case where it is judged that it is the first time to obtain, current SOC and / or each sampling point temperature changes, calculate single cumulative time;Calculate the state value of battery module to reach the next charging current change point, update state;In the case where it is judged that the current SOC is greater than or equal to the first SOC threshold value, obtain terminal charging time;According to each single cumulative time and the terminal charging time, calculate the residual charging time.The estimation method is more accurate in estimation result.

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.

If the reception time of a previous packet is within a designated period before the reception time of a packet of interest, a target extraction unit (S210 to S230) extracts, as a target packet, a forward path packet that has been transferred last using the same path as a path of interest before the reception time of the packet of interest. A calculation unit (S240) calculates the time from the transmission time of the target packet to the reception time of the packet of interest as an estimated value of the round trip time of the path of interest. The previous packet is a return path packet that has been transferred last before the packet of interest. The path of interest is a path used for transfer of a return path packet indicated by a confirmation number of the previous packet.

The invention discloses a performance time estimation method and device, a storage medium and computer equipment. The method comprises the steps of obtaining multi-source feature data of a target order, wherein the multi-source feature data comprises order basic information, historical same-period statistical information, real-time statistical information, real-time weather information and forecast weather information; when the target order is in the abnormal weather scene, inputting the multi-source feature data into a pre-trained abnormal weather time estimation model; converting the multi-source feature data into embedded features through an abnormal weather time estimation model, carrying out explicit feature cross calculation on the embedded features to obtain cross features, and carrying out multiple times of aggregation and projection processing on the embedded features in parallel to obtain multiple reinforced features; and carrying out splicing and fusion on the cross features and the plurality of reinforced features, and carrying out performance time estimation based on the spliced and fused feature vectors to obtain a performance time estimation result. According to the method, the accuracy of performance time estimation in abnormal weather can be improved.

A computing device having a host system coupled to a memory sub-system. The host system runs a garbage collection manager and a plurality of storage space tenants. The garbage collection manager can: write, to the memory sub-system according to a protocol of flexible direct placement (FDP), data of the plurality of storage space tenants to a reclaim unit in the memory sub-system; identify, after a first portion of the data stored in the reclaim unit is invalidated, first storage space tenants having a second portion of the data remaining valid in the reclaim unit; communicate with the first storage space tenants to identify estimates of expiration time of the second portion; and select, based on the estimates, the reclaim unit for acceleration of invalidation of the second portion of the data.

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.