23 results about "Time efficiency" patented technology

The invention relates to the technical field of scheduling management, in particular to a dynamic production scheduling management system based on artificial intelligence, which comprises a task compression coefficient generation module, a task priority remapping module, a resource conflict index extraction module, a path broken link node identification module and an alternative task sequence construction module. According to the method, quantitative evaluation is performed on the task timeliness urgency degree through the time buffer region constructed by the latest starting time and the predicted execution duration of the task, the key task influencing the delivery node can be dynamically identified, so that the task priority relationship is not statically solidified any more, and potential link breaking points in the technological process are screened in combination with the path structure dependency relationship; a prediction trigger condition is constructed through a judgment node with the minimum structural sensitivity, a task replacement path is predicted by matching a process parameter group with a convolutional neural network model, a node with the minimum interference degree is screened to form a repair scheme path, and the plan failure risk caused by abnormal nodes is reduced.

The utility model relates to an on-line grinding machine, which solves the problems of poor grinding precision, long grinding time efficiency, low grinding efficiency, high grinding work intensity and the like in the prior art, and adopts the technical scheme that the on-line grinding machine comprises a first motor and a grinding wheel arranged at the output end of the first motor, and is characterized by further comprising a base and a three-dimensional adjusting mechanism arranged on the base, the first motor is arranged on the three-dimensional adjusting mechanism, the three-dimensional adjusting mechanism is used for adjusting the three-dimensional position of the first motor to adjust the grinding surface of the grinding wheel, the three-dimensional adjusting mechanism comprises an X-direction adjusting mechanism, a Y-direction adjusting mechanism and a Z-direction adjusting mechanism, and the grinding surface of the grinding wheel can be adjusted by adjusting at least one of the X-direction adjusting mechanism, the Y-direction adjusting mechanism and the Z-direction adjusting mechanism. The position of the grinding surface of the grinding wheel is adjusted. The grinding machine has the advantages that the position of the grinding face of the grinding wheel is accurate through the three-dimensional adjusting mechanism, the purpose of accurate grinding is achieved, the three-dimensional adjusting mechanism is high in adjusting precision and convenient to adjust, the grinding efficiency can be greatly improved, and the grinding strength is reduced.

Provided is a printer that improves the time efficiency of printing. A heating device 110 of a printer 10 comprises a heating device body 111, a heater 120, and a media guide 130. The media guide 130 is disposed so as to face a recording medium 5 transported by a medium transport device 50. The media guide 130 is a plate-like member that guides the recording medium 5 toward a heating chamber 113. A plurality of holes 131 are formed in the media guide 130 so as to pass through the thickness direction thereof.

The invention discloses an equipment lease process automatic management system and method, and belongs to the technical field of equipment lease, and the method comprises the steps: dividing the expected use time into minimum time units, and forming a refined time credibility scoring matrix through combining an equipment return behavior fluctuation index and a regional time efficiency compression index; meanwhile, a buffer time period is automatically inserted after a task is finished, a sliding time window is used for detecting a low-credibility time block and marking a conflict risk, recommendation equipment is further screened through a logic judgment mechanism, a replacement scheduling scheme is provided when necessary, and finally scheduling suggestions are output in a graphical mode. High-precision prediction, high-reliability recommendation and high-visual interaction of equipment scheduling in a multi-lease, cross-time-zone and high-density scene are realized, and the scheduling safety and the system intelligence level are effectively improved.

The embodiment of the invention provides a task scheduling method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining a target task type corresponding to a target task indicated by a task scheduling request in response to the task scheduling request, and determining a target compiling resource based on a resource determination mode corresponding to the target task type; determining a target node from the at least two to-be-scheduled nodes based on the resource use conditions corresponding to the at least two to-be-scheduled nodes and the acquisition channel of the target compiling resource; and scheduling the target compiling resource to the target node. According to the method, target compiling resources are determined through a resource determination mode corresponding to a target task type, and in a task scheduling link, a target node is intelligently determined from a plurality of to-be-scheduled nodes based on resource use conditions corresponding to at least two to-be-scheduled nodes and an acquisition channel of the target compiling resources; the reasonability of task scheduling and the time efficiency of task execution are improved, and a powerful guarantee is provided for stable operation and efficient execution of the system.

A non-volatile memory improves read time efficiency by combining hard and soft reads into a single effective soft read sequence using two senses per state level. Instead of a standard hard read, which performs two soft reads offset above and below the hard read value, the hard reads are shifted so that they reliably sense one state but less reliably sense the other, and soft data is determined only for the less reliably sensed state. This reduces the amount of soft data. The effective soft-sensing sequence can be used as the default read mode, providing soft-sensing information for ECC correction without triggering read error handling. Combining soft and hard sensing into a single sequence avoids the additional overhead for read sequence operations.

A system for increasing the speed and reducing the time to obtain a required amount of data, from a secondary storage device, for a digital computer, based upon measures to improve the time efficiency of I / O request processing by improving the timing and sequence of transfers to improve the efficiency of mass storage devices.

To improve time efficiency and user-friendliness in connection with the setting of parameters used in a three-dimensional manufacturing device.A three-dimensional fused deposition modeling (FDM) manufacturing device comprises: a parameter setting unit that sets the type of user-replaceable part and the value of a manufacturing parameter of an object; a manufacturing data generation unit that creates manufacturing data for producing a three-dimensional manufactured object based on the value of the manufacturing parameter; a storage unit that stores allowable range reference data specifying a allowable range of the manufacturing parameter value according to each type of replacement part; and a guidance unit that guides the manufacturing parameter value to fall within the allowable range based on the type of replacement part, the value of the manufacturing parameter, and the allowable range reference data stored in the storage unit.

The present invention aims to provide a rotating body article visual inspection device and a rotating body article visual inspection method that can improve inspection accuracy and shorten cycle time to increase the time efficiency of inspection. [Solution] The O-ring appearance inspection device 1 of the present invention is an appearance inspection device for inspecting the appearance of an O-ring K, comprising: a plurality of line sensor cameras 20 whose positions and orientations are set in advance and which image the O-ring K; and a holding device 10 which holds the O-ring K and has a head portion 14 that is rotatable around an axis C1, wherein the holding device 10 sequentially moves the O-ring K to a plurality of imaging positions P corresponding to each of the plurality of line sensor cameras 20, and rotates the head portion 14 around the axis C1 at the imaging positions P to rotate the O-ring K in the circumferential direction.

The invention discloses a portable intelligent power first-aid repair metering method, system, equipment and medium, and belongs to the technical field of power distribution network maintenance, and the method comprises the steps: receiving and integrating the position and type information of a fault point and the real-time state data of each first-aid repair device, dynamically predicting the first-aid repair time of each device based on the historical efficiency and the real-time efficiency, and calculating the first-aid repair time of each device; the total scheduling time is calculated in combination with the path distance and the distribution speed; and through intelligent comparison, predicting a matching relationship between the first-aid repair time and the total scheduling time, selecting a device with the optimal comprehensive scheduling time efficiency from the devices meeting the time efficiency conditions as a supply source, generating a distribution instruction and issuing the distribution instruction to distribution personnel. According to the method, the historical efficiency data, the real-time working condition information and the multi-device synergistic effect are integrated, the first-aid repair time is predicted, and the optimal device is dynamically selected, so that the timeliness of first-aid repair response and the scientificity of resource scheduling are improved, and the whole-process intelligence from first-aid repair operation to equipment maintenance is realized while the continuous and reliable operation of first-aid repair equipment is ensured.

The invention relates to the technical field of integrated circuit chip design and artificial intelligence, aims to solve the problems of poor acceleration calculation timeliness and high cost performance of an LSTM (Long Short Term Memory) time sequence algorithm in the existing long short-term memory network calculation chip, and provides a long short-term memory network calculation chip and method for MIMO (Multiple Input Multiple Output) time sequence signals. The long and short time memory network computing chip for the MIMO time sequence signals comprises a Sigmoid function computing module, wherein the Sigmoid function computing module computes output data and transmits the output data to a multiply-accumulate computing module; the data flow control module is used for providing an input data signal sequence and parameter data for the Sigmoid function calculation module, outputting data obtained by Sigmoid function calculation to the multiply-accumulate calculation module, and transmitting an output result to the output data module; the assembly line control module is used for controlling assembly line calculation of the long-short term memory network. The LSTM calculation efficiency can be improved, and the calculation cost can be reduced.

The present application relates to the technical field of intelligent manufacturing and production scheduling, in particular to a multi-variety variable-batch flexible job shop intelligent scheduling method based on enhanced genetic algorithm and dynamic time window, comprising the following steps: step S1: obtaining a production order list to be scheduled, workshop resource information and a current material inventory state, splitting the order into a work order set with process constraints according to the process route of the order product, and performing a material completeness pre-check on the split work order; step S2: constructing a machine idle time period management model based on a dynamic time window, and maintaining available time segments of each production device in real time through a multi-value mapping data structure; step S3: taking the minimization of the maximum completion time, the maximization of the weighted average device utilization rate and the maximization of the material completeness just-in-time start rate as optimization objectives; the present application realizes accurate maintenance of the device idle time period by introducing a dynamic time window management mechanism, and significantly improves the time efficiency in the decoding process of the genetic algorithm.

The invention provides a method for optimizing a vacuum system in a magnesium reduction process, which comprises the following steps of: S4, judging whether a starting condition of a jet vacuum pump is met or not according to a stable medium temperature value, and calculating a cooperative operation time point of a mechanical vacuum pump and the jet vacuum pump as a pump group linkage moment through a time sequence arrangement mechanism; s6, according to the smooth vacuum degree transition curve, whether the process stability reaches the expectation after the system is started or not is judged, and optimized operation parameters are stored through a data recording module to serve as an optimization template; s7, according to the optimization template, obtaining improvement data of the vacuumizing efficiency in the magnesium reduction process, and determining a final vacuum system operation scheme as a standardized operation protocol by comparing historical operation records with real-time efficiency indexes; and S8, according to the final vacuum system operation scheme, the operation states of the mechanical vacuum pump and the jet vacuum pump are monitored in real time through a continuous monitoring mechanism, and long-term stable process parameters are obtained to serve as lasting and reliable indexes.

A system for increasing the speed and reducing the time to obtain a required amount of data, from a secondary storage device, for a digital computer, based upon measures to improve the time efficiency of I / O request processing by improving the timing and sequence of transfers to improve the efficiency of mass storage devices.

The present application relates to the technical field of aero-engine fault data isolation processing, and in particular to an aero-engine fault data processing method and system which can achieve a good balance between time efficiency and generation quality and has good versatility. First, the original data is preprocessed through the MAW workflow, and then the fine semantic segmentation of the text and the efficient vectorization index construction are completed through the domain adaptive large language model and the dynamic code execution mechanism. Second, the two-stage progressive retrieval enhancement generation architecture TSP-RAG is proposed. At the same time, the adaptive HNSW retrieval module dynamically adjusts the search breadth according to the obtained ef weight, performs vector retrieval, and removes the results at the content level. Finally, the nodes retrieved by the FIL-knowledge graph and the HNSW retrieval results are semantically fused and reordered, and are input into the large language model together with the reasoning tree to generate answers. Compared with the prior art, the present application has the advantages of high time efficiency, high generation quality, and good versatility.

A method and system for quickly emptying a plurality of substantially identical target items from a transport structure with a picking tool for placement into a transport container are provided. The method includes the step of providing a plurality of equivalence classes which partition all possible sequences of legal picks. Each equivalence class containing a subset of items from a ranked configuration. The method also includes ranking the equivalence classes in order of expected time efficiency and selecting the best ranked equivalence class for picking.

The invention discloses a material guarantee task scheduling system based on a double-population genetic algorithm. The system comprises a node model, a task demand and capability model, a material guarantee task scheduling model, constraint conditions of the model and a model solution guarantee task scheduling algorithm based on double-population heredity. The node model comprises a demand node, a guarantee node, various material reserves capable of being provided by the guarantee node and guarantee equipment of the guarantee node; the task demand and capability model comprises the demand quantity of a certain material guarantee task of the demand node, the expected completion time of the demand task and the quantity of materials needed by the guarantee task. According to the system, the limitation that a traditional single population optimization algorithm is easy to fall into a local optimal solution in material guarantee task scheduling and is difficult to consider multi-target conflicts is effectively overcome, and the time efficiency, the resource utilization rate and the overall feasibility of a scheduling scheme of the material guarantee task are remarkably improved.

The present invention relates to the field of transportation technology, and discloses a method and system for optimizing the operation strategy of heavy-load trains based on group control technology, so as to rationally plan the operation strategy, reduce the time efficiency of heavy-load train cargo transportation, and improve the line transportation capacity. The method comprises: step S1, determining a heavy-load railway line to be optimized with the characteristic of "directly departing from a technical station"; step S2, constructing a target optimization model that minimizes the weighted sum of economic cost and total in-transit transportation time of goods based on the supply and demand relationship, arrival time constraint, skylight time, number of locomotives, and the comprehensive importance of transportation demand; step S3, solving the group train operation strategy corresponding to the Pareto optimality in the target optimization model based on the simulated annealing algorithm; wherein the number of trains in each group is the same and greater than or equal to 2.

The application discloses a time series prediction method and device, electronic equipment and medium, and relates to the technical field of big data. The method comprises the following steps: acquiring historical time series data; constructing a prediction model based on a Transformer network, wherein the prediction model comprises an attention layer, and the attention layer comprises a linear mapping autocorrelation attention module, which is used for acquiring autocorrelation features of input data of the prediction model; inputting the historical time series data into the prediction model as the input data, obtaining autocorrelation features of the historical time series data based on the linear mapping autocorrelation attention module of the prediction model, and obtaining a prediction sequence in a preset time period after a current time based on the autocorrelation features of the historical time series data. The method can capture context correlation information of the historical time series data, is more accurate in prediction, reduces spatial and temporal complexity, and improves memory efficiency and time efficiency.

Embodiments of the present application provide a kind of based on distributed cluster partition method.The method comprises: based on the initial sampling period of current round, the operating parameter of each node in power system is collected, and initial operating parameter is obtained;According to initial operating parameter, determine failure index;Wherein, failure index represents the time efficiency adaptation degree of cluster partition according to initial operating parameter;If it is determined that the period adjustment condition is satisfied according to failure index, then determine the actual sampling period according to failure index and initial sampling period;Based on actual sampling period, the actual operating parameter of each node in current round is collected, and each node is divided into multiple distributed clusters according to the actual operating parameter of current round.The method is used to improve the timeliness and accuracy of distributed cluster partition, to improve the stability and resource utilization efficiency of power system.

An embodiment of the present invention provides a method, apparatus, communication device, and storage medium for obtaining interrupt time, including: when an error is detected during OS runtime, triggering an SMI, a timing module obtains the total SMI time and the IPMI information sending time through a timing register, wherein the IPMI information sending time is the time it takes for the timing module to obtain an error record from a register storing error records and send the error record to the BMC through IPMI; a BMC time analysis module obtains the IPMI information sending time and the total SMI time from shared memory by cyclically reading and updating a flag bit. Obtaining the interrupt time through the BMC time analysis module, i.e., obtaining the total SMI time out-of-band, does not require additional OS login permissions, and the process of obtaining the total SMI time is relatively simple, solving the problem of low efficiency in obtaining the time spent from error-triggered SMI to SMI termination.

The application provides a weapon target allocation method based on a neural network, and mainly solves the problem that the prior art cannot be applied to the continuous combat scene of unmanned aerial vehicle group attacking ground targets which has extremely high time efficiency requirement.The scheme is as follows: threat evaluation is carried out on the discovered targets, the targets are sorted according to the threat degree, and the targets are allocated with weapons one by one; the damage probability estimation is used to obtain the attack suitability of each weapon on the current target to be allocated, the commander adjusts part of the suitability according to the actual combat experience, and a training data set and a test data set are formed; the full connection network model is trained through the training set, the best full connection network model is selected through the test data set, and the selected best full connection network model is used to allocate the weapon target for each target one by one.The application not only can utilize the historical combat information and the combat experience of the commander, but also can reduce the allocation time, and can be applied to the continuous combat scene of unmanned aerial vehicle group attacking ground targets which has extremely high time efficiency requirement.

A simulation coordination device (100) executes simulation in parallel even for three or more inter-coordinated simulations, thus enhancing time efficiency, and also ensures accuracy in the simulations as a whole. A prior processing indication unit (110) executes a mock run by including predicted values among processing results of a plurality of simulations that are coordinated with one another and each have individual cycles, and calculates a first provisional processing result (62). A current processing indication unit (120) uses all of the processing results of the plurality of simulations as past processing results to execute a mock run, and calculates a second provisional processing result (63). A conformity determination unit (130) calculates the difference between the first provisional processing result (62) and the second provisional processing result (63), and determines whether the difference has exceeded a threshold value (64). A synchronization control unit (140) adjusts the cycles and executes a mock re-run if the difference is determined to have exceeded the threshold value (64).