40 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 invention provides a sub-season heat wave prediction method, which comprises the following steps of: determining all optimal prediction factors associated with any air temperature main mode time coefficient under preset prediction time efficiency according to a pre-obtained air temperature main mode of a target area and an air temperature main mode time coefficient-prediction time efficiency-optimal prediction factor relation table; and acquiring data of all the optimal forecasting factors through real-time non-band-pass filtering, inputting a pre-trained sub-season air temperature forecasting model, and acquiring a predicted air temperature abnormal field in the target area under preset time efficiency. And predicting the sub-season heat wave event in the target area according to the predicted air temperature abnormal field. According to the method, the interaction between multiple scales and multiple variables is considered by using the strong data mining capability of the convolutional neural network, the influence of the interannual scale signal on the large-scale sub-seasonal variation rate is fully considered, and the potential correlation between the early-stage multi-scale signal and the future air temperature is mined.

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.

The invention belongs to the field of software testing, and discloses a software test case testing method and system, and the method comprises the steps: S1, obtaining a set U of test cases for testing, and S11, calculating a risk value of a module based on a change record of a code of a module of software; s12, calculating a risk coverage weight of the test case based on the risk value; s13, calculating a defect prediction weight and a space-time efficiency weight of the test case based on the historical test record; s14, calculating a screening value of the test case based on the risk coverage weight, the defect prediction weight and the space-time efficiency weight; s15, acquiring a set U of test cases based on the screening values; and S2, using the test case in the set U to test a module needing to be tested, and obtaining a test record. According to the invention, the test priority of the high-risk module can be ensured, and a more effective test result can be obtained.

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 present invention discloses a multi-objective dynamic task scheduling method and system based on an improved ant colony algorithm, the method comprising: splitting a task into a plurality of subtasks, and sorting the subtasks of each task in ascending order according to the priority of each task, to obtain a sequence of tasks to be scheduled; assigning the tasks to be scheduled to each computing node in a sequential scheduling manner, to obtain an initial task-computing node allocation scheme, and to calculate the task execution time and computing cluster load factor; and obtaining an optimal allocation scheme based on an improved ant colony algorithm. The present invention comprehensively considers factors such as the system computing node load capacity, task execution time, and task priority, optimizes the pheromone update strategy and heuristic information in the basic ant colony algorithm to avoid local optimality and achieve rapid convergence, improves the timeliness of task allocation and the utilization rate of computing resources, reduces the cloud computing task scheduling overhead, and realizes global multi-objective task optimization scheduling.

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.

The invention discloses a method for quantitatively evaluating the completion degree of a task, which comprises the following steps of: D1, acquiring the planned completion time Tp of the task, the actual completion time Ta of the task, the planned continuity resource usage amount Rp of the task, the actual continuity resource usage amount Ra of the task and the planned one-time resource usage amount Sp of the task, the actual one-time resource usage amount Sa of the task, the subtask number n of the task, the total number m of the indexes, and the expert-evaluated initial value xij of the ith subtask on the jth index are calculated; d2, calculating the time efficiency of the task according to the planned completion time of the task and the actual completion time of the task; d3, calculating the resource utilization rate of the task according to the planned resource usage amount of the task and the actual resource usage amount of the task; d4, calculating the completion quality of the task according to the number of the subtasks of the task; and D5, calculating the completion degree of the task according to the time efficiency of the task, the resource utilization rate of the task and the completion quality of the task.

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.

To provide an electric wire fixture, crimp determination device, and crimp determination method capable of determining a crimp state of electric wires with excellent time efficiency.SOLUTION: An electric wire fixture is arranged on a stage when performing X-ray CT photography and enables a wire harness being a photographing object to be arranged at a predetermined position on the stage. The electric wire fixture includes: a base part for supporting the plurality of wire harnesses and transmitting an X-ray; and grooves arranged on a surface of the base part and having a width larger than a diameter of the wire harness. The groove penetrates at least a set of opposing surfaces of the base part.SELECTED DRAWING: Figure 1

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 discloses a method for calculating the reachability probability of an uncertain graph based on landmark nodes, including: (1) modeling the network in the real world into an uncertain graph; (2) constructing landmark nodes corresponding to each node by offline sampling; (3) calculating the reachability probability of each node to its landmark node; (4) calculating the reachability probability between a given pair of nodes through the landmark nodes. While ensuring that the calculation accuracy of the reachability probability between any two nodes in the uncertain graph is close to that of the mainstream method, the present invention improves the time efficiency.

Computer-implemented methods and systems for operating a plurality of Hardware Random Number Generators (HRNGs), (e.g., physical roulette wheels). An example method includes sequentially launching each of the plurality of HRNGs such that none of the plurality of HRNGs have a starting point occurring at the same moment in time. Methods for selecting one HRNG out of the plurality of sequentially launched HRNGs based on a timing of a placed and confirmed bet such that the selected HRNG is the HRNG of the plurality of HRNGs having the lowest time until reaching the resolution while fulfilling a predefined criteria are also included. Thereby advantages in terms of time efficiency, increased game cycle rates, and improved human-machine interaction are readily achievable.

A method for an electric vehicle trip simulator is described. The method includes determining parameters for an upcoming trip of an electric vehicle, including at least a start location and a destination location. The method also includes analyzing data associated with a plurality of points of interest between the start location and the destination location. The method further includes selecting a set of locations from the plurality of points of interest for the upcoming trip of the electric vehicle, according to the analyzing of the data. The method also includes displaying a travel order recommendation associated with the set of locations selected for the upcoming trip of the electric vehicle, including at least one charging station location according to a current charge capacity of the electric vehicle.

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.

Techniques for performing efficient automatic test-pattern generation (ATPG) are disclosed. ATPG may be performed by ATPG workers whose fault states are synchronized by an ATPG manager. In some embodiments, test-pattern generation by a ATPG worker may be performed multiple times with minimal idle time between generation and fault simulation intervals. Synchronization schemes may be synchronous or asynchronous. In asynchronous schemes, an ATPG worker may determine staleness of its fault state. If the fault state is stale, the ATPG worker may poll the ATPG manager to update the fault state to the current fault state of the ATPG manager which includes information on faults detected (including duplicate faults) by other ATPG workers. In synchronous schemes, fault states may be synchronized without polling by the ATPG worker. The synchronization of fault states via communication between manager and workers may reduce duplication and idle time, hence improving the time efficiency of ATPG workers.

The invention relates to the technical field of education, and particularly discloses a time management planning method based on time efficiency maximization, which comprises the steps of arranging timing tools and methods; filling in a time log, and making a work and rest time table; comparing with a work and rest time table; listing a list of events to be completed in the next day, classifying the events, and arranging time in blocks; performing four-quadrant method sorting, sorting events and tasks according to a four-quadrant time management method, and dividing the events and tasks into important emergency, important non-emergency, emergency non-important and unimportant non-emergency classes; performing time arrangement and labor division on the team; making a long-time period time management table; making a career planning table; and carrying out processes and achievements of conclusion, review, tracking and reflection time management training. According to the training of the invention, children can not only improve the time management ability in a short period of time, but also form a good time management habit in a long period of time, thereby generating far-reaching influences on the aspects of improving the learning efficiency, improving the life quality, enhancing the confidence and responsibility and the like.

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 compiler variable address random compilation method and system, collects industrial automation control data required for use in a program to be run, and counts the number of variables to be assigned addresses; obtains random seeds A and random seeds B, and generates random number sequences S respectively. A With S B And cross randomly generate variable index random number sequence b a And the address number random number sequence a b ; Group the variables to be compiled and number the bytes of the memory address, then use a hash table to store the bytes of each memory address and its corresponding number; select the groups in order of grouping, randomly select the variables to be compiled in the selected groups, calculate the number of aligned bytes and the length of the variables, and allocate the memory addresses in parallel until all the variables in the groups are allocated to the available memory space memory addresses or all the available memory space memory addresses are used up. The present invention effectively increases the difficulty of predicting memory address allocation, makes the cracking cost higher, and successfully takes into account time efficiency.

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.

The aluminum alloy tank welding system and method are used for solving the problems that manual welding is low in accuracy, low in time efficiency and poor in stability. An aluminum alloy tank body welding system is characterized by comprising a robot (101), an electric control cabinet (102), a robot control cabinet (103), a welding machine (104), a positioner (106) and a robot ground rail (107), a target workpiece is an aluminum alloy tank body (105), the welding machine (104) is in communication connection with the robot (101), the robot (101) is in communication connection with the robot control cabinet (103), the positioner (106) is used for fixing and adjusting the pose of the aluminum alloy tank body (105), and the robot ground rail (107) is connected with the robot control cabinet (103). The robot ground rail (107) is connected with a mechanical arm of the robot (101) so that the mechanical arm can move in the preset direction, and the electric control cabinet (102) is electrically connected with the robot control cabinet (103), the positioner (106) and the robot ground rail (107).

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 present invention provides a task allocation method, device, equipment and product, which relates to the field of task processing technology. The method comprises the following steps: obtaining evaluation parameters of personnel to be assigned; inputting the evaluation parameters into a task allocation model to obtain evaluation parameters output by the task allocation model; wherein the evaluation parameters include a comprehensive evaluation value of the personnel to be assigned, a first time-consuming evaluation value and a first number evaluation value, the first time-consuming evaluation value is the time-consuming evaluation value of the task completed at that time, the first number evaluation value is the number evaluation value of the task completed at that time, the timeliness value is inversely proportional to the actual operation time, and the accuracy value is inversely proportional to the number of cycles; based on the evaluation parameters, tasks are allocated. The present invention can allocate tasks to business personnel with high completion quality and fast completion speed, avoiding the backlog of tasks and the task processing quality not meeting the requirements.

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.