37 results about "Work scheduling" patented technology

The invention relates to a monitoring system and method for a new energy station, a medium and equipment, and the system comprises a data monitoring module which is used for collecting the current health state information of a target operation and maintenance worker in the new energy station in real time, and the current environment information of an area where the target operation and maintenance worker is located; the monitoring platform is used for determining a target operation type corresponding to a target operation task currently executed by the target operation and maintenance personnel, determining an environment matching degree according to the target operation type and the current environment information, determining a health state matching degree according to the target operation type and the current health state information, and sending the health state matching degree to the target operation and maintenance personnel; if it is determined that the work scheduling information of the target operation and maintenance personnel needs to be adjusted according to the environment matching degree and the health state matching degree, prompt information is sent to terminal equipment used by the target operation and maintenance personnel; and the terminal equipment is used for receiving and outputting the prompt information. According to the technical scheme, the operation scheduling can be optimized, the operation safety of operation and maintenance personnel is improved, and the operation risk is reduced.

The invention discloses an active power distribution network risk assessment method and system, and the method comprises the steps: taking a day as a calculation time period, combining a constructed fault influence scale, and carrying out the calculation of an annual equipment maintenance work schedule model considering the minimum power failure loss and element strengthening plan offset, and obtaining an annual equipment maintenance work plan; combining the novel source side / load side response model to construct a system unit commitment optimization scheduling model with minimum load shedding and optimal economical efficiency as objective functions; and inputting the obtained annual equipment maintenance work scheduling plan result, carrying out state sampling on the system by adopting a sequential Monte Carlo simulation method, and carrying out system state estimation by applying a system unit combination optimization scheduling model to obtain system operation state data so as to realize reliability evaluation and risk analysis of the power distribution network.

To enable smooth job recruitment.SOLUTION: A job offer management system includes a publication unit configured to collectively publish job offers, for work hours to which no staff member has been assigned, to job seekers belonging to a predetermined segment on the basis of work schedule information indicating work schedules.SELECTED DRAWING: Figure 1

The invention relates to a charging pile control method and system, a terminal and a storage medium, and relates to the technical field of charging piles, and the method comprises the steps: collecting the working state information of a charging pile; acquiring position information, destination information and charging demand parameters of a target vehicle; predicting the arrival time of the target vehicle according to the position information and the destination information; based on the charging demand parameters, the arrival time and the working state information, whether a target charging pile meeting the charging demand parameters exists or not is judged; if not, determining a candidate charging pile combination according to the charging demand parameter; determining a target charging pile combination according to the candidate charging pile combination and generating a work scheduling instruction and a vehicle scheduling instruction corresponding to the target charging pile combination; sending a vehicle scheduling instruction to the target vehicle; and in response to the charging starting operation, controlling the target charging pile combination to cooperatively supply power according to the work scheduling instruction. The method has the effects of improving the charging efficiency, guaranteeing the power supply reliability and realizing efficient cooperative distribution of power resources.

The invention discloses a base station power distribution system which comprises at least one of a PV / DC photovoltaic power module and a DC / DC bidirectional stacked storage power module, a stacked storage battery, a system centralized monitoring module, a load primary power-off port, a load secondary power-off port and a load power-off and data acquisition control module. The system can be flexibly configured as a pure light system, a stack storage system or a light storage integrated system, facilitates the subsequent increase, decrease and change of the configuration according to the needs, is high in expansibility, and enables the resource utilization rate to be maximized. The integrated design is integrated to complete system operation and work scheduling required by functions, high reliability and stability are achieved, meanwhile, system operation state information is integrated to be in butt joint with a data platform, and remote inspection operation and maintenance are facilitated.

A method for performing project management that comprises: generating, by a processor, a draft proposal of a project; sending, by the processor, the draft proposal to a client device to be reviewed by a client; receiving, by the processor, a client input on the draft proposal from the client device; for the client input indicating client approval of the draft proposal, initiating, by the processor, work scheduling with the client.

Technologies for enhancing work scheduling of a big data framework. The technologies can include generating, in a database, configurable namespaces to be used by a work scheduling enhancement application to group together tasks of one or more big data clusters. The namespaces can be hierarchical. The technologies can also include linking in the database, by the application, related tasks with respective namespaces to categorize and group together the related tasks. The technologies can also include configuring, by the application, a display scheme for displaying error handling and root cause analysis of tasks of the one or more big data clusters. The technologies can also include generating or rendering, by the application, a GUI having a navigable hierarchal view for displaying the namespaces. The generation or rendering of the GUI can be based partially on the display scheme.

The processing system (100) includes a scheduling mechanism for generating data for fine-grained reordering of workgroups of kernels to generate data blocks, such as for communication across devices to enable overlap of AllReduce communication and producer computations over a network. This scheduling mechanism enables a first parallel processor (702) to schedule and execute a set of workgroups of producer operations to generate data for transmission to a second parallel processor (704) in a desired traffic pattern. Concurrently, the second parallel processor schedules and executes a different set of workgroups of producer operations to generate data for transmission in a desired traffic pattern to a third parallel processor (706) or back to the first parallel processor.

A computer system and computer implemented method. The method includes identifying a plurality of operational readiness data and a plurality of policy data for a workforce; filtering the plurality of operational readiness data and the plurality of policy data to define a ready workforce; providing a first user interface to a manager; providing a second user interface to a worker; and detecting a selection of a date range for scheduling the ready workforce. Further, the method optionally includes receiving at least one priority constraint from the manager; receiving at least one scheduling preferences from a worker. The method includes calculating, by applying an iterative computer model, a work schedule for the ready workforce during the date range and publishing the work schedule.

A method for hierarchical work scheduling includes consuming a work item at a first scheduling domain having a local scheduler circuit and one or more workgroup processing elements. Consuming the work item produces a set of new work items. Subsequently, the local scheduler circuit distributes at least one new work item of the set of new work items to be executed locally at the first scheduling domain. If the local scheduler circuit of the first scheduling domain determines that the set of new work items includes one or more work items that would overload the first scheduling domain with work if scheduled for local execution, those work items are distributed to the next higher-level scheduler circuit in a scheduling domain hierarchy for redistribution to one or more other scheduling domains.

The invention provides a battery energy station work schedule management method and system based on a processor utilization rate. The method comprises the following steps: firstly, charging a plurality of batteries by using a battery energy station, and providing the batteries for exchange operation; a time schedule corresponding to at least one work of the battery energy station is provided, and a remote server is utilized to execute the work according to the time schedule. A processing unit of the remote server detects a processor usage rate of the corresponding processing unit and determines whether the processor usage rate exceeds a preset threshold value. When the processor usage rate exceeds a preset threshold value, the remote server is used to adjust the time schedule of the corresponding work, and the work is executed according to the adjusted time schedule.

This application discloses a conflict detection method, system, and storage medium for planned work scheduling of nuclear power equipment. The conflict detection method includes: acquiring configuration files pre-established for each master device, the configuration files including availability dependency information and redundancy information. The availability dependency information includes: the identifiers of upstream devices on which the availability of the master device depends, and the dependency logic relationship between the availability of the master device and the upstream devices. The upstream devices include at least one other master device and / or at least one end device; acquiring an isolation instruction table from the SAP system; determining the status of each master device according to the isolation instruction table and the availability dependency information corresponding to each master device; and identifying master devices that do not meet the corresponding redundancy requirements according to the status of each master device and the redundancy information corresponding to each master device. Implementing the technical solution of this application improves the efficiency of conflict detection in planned work scheduling and reduces the probability of human error.

To facilitate job recruitment.SOLUTION: A job management system includes: a detection unit for detecting a work schedule of short-term part-time employment; and a processing unit for performing processing on the basis of short-term part-time job information regarding the short-term part-time employment for the detected work schedule.SELECTED DRAWING: Figure 1

The invention is suitable for the technical field of intelligent monitoring, and provides a fault prediction method and system based on elevator parts, and the method comprises the steps: obtaining the real-time operation data set information of a plurality of elevator parts based on a plurality of sensors, and then generating operation evaluation information based on the real-time operation data set information, and finally, sending the operation evaluation information to a specified display terminal. According to the method and the device, an owner party can carry out work scheduling of shutdown maintenance on the elevator to be maintained in advance, the occurrence probability of sudden failures is avoided, the use safety of the elevator is improved, an elevator maintenance company can purchase and prepare targeted key parts, the inventory number of the key parts is effectively reduced, and the maintenance cost is reduced. According to the method and the system, key parts of corresponding brands and models can be more accurately provided for a user for maintenance, meanwhile, an owner can follow real-time data of a mechanical vibration analysis curve for comparison, the operation state of the key parts can be clearly mastered in real time, and maintenance work is effectively supervised.

The invention discloses a grassroots governance collaborative decision support system based on intelligence and big data, and relates to the technical field of big data processing in grassroots governance, comprising the following steps: step 1, work task statistics, step 2, task information arrangement, step 3, priority calculation of to-be-handled tasks, step 4, sorting of to-be-handled tasks, step 5, scheduling of the to-be-handled tasks, step 6, scheduling of the to-be-handled tasks, and step 7, scheduling of the to-be-handled tasks. The method comprises the following steps: step 1, marking to-be-handled tasks as in-progress tasks, step 6, uniformly managing and displaying the tasks, and step 7, jointly and cooperatively deciding, in the method, the to-be-handled tasks are counted according to the urgency of the to-be-handled tasks, the importance of the to-be-handled tasks and the difficulty of the to-be-handled tasks, and the to-be-handled tasks are sorted and distributed through priority calculation; and step 3, marking the to-do tasks as in-progress tasks, repeating task information arrangement in the step 2 and priority calculation in the step 3, and putting the in-progress tasks into the to-do task set for unified management, so that the distributed tasks are redistributed, and the work arrangement efficiency can be improved.

The present invention discloses a pipeline-oriented network processing workflow scheduling method, device, and medium, wherein the method includes: generating a DAG and generating a global resource usage document; serializing the network processing workflow; training a network work scheduling model; and forming a network workflow scheduling strategy. The pipeline-oriented network processing workflow scheduling method proposed by the present invention can handle network processing workflows of variable length and network processing resources of variable scale, and utilizes a reinforcement learning model to simultaneously implement intelligent network processing resource planning and intelligent work scheduling for network processing workflows, thereby improving the overall utilization of network processing resources and reducing the waste of network processing resources. The present invention can be widely applied to fields such as reinforcement learning, parallel computing, and work scheduling.

The application belongs to the field of distributed production scheduling in manufacturing industry, and particularly relates to a distributed blocked flow shop scheduling optimization system based on reinforcement learning, which comprises a scheduling sequence diversification initialization module, an improved module based on Q-learning and a local search module based on neighborhood reconstruction; the scheduling sequence diversification initialization module designs a diversified initial population generation strategy, the improved module based on Q-learning designs a global search mechanism based on a reinforcement learning mechanism, and a search operator is adaptively selected according to a search state and historical experience of the operator; and the local search module based on neighborhood reconstruction comprises a deep local search strategy based on neighborhood reconstruction and an improved strategy based on path reconnection. The application has simple logic, is easy to implement and easy to expand, and can expand the optimizer to most scheduling problems in the current intelligent manufacturing production field.

This invention discloses an intelligent scheduling method and system for medical waste robots based on the Internet of Things (IoT), relating to the field of IoT technology. The method includes: installing an IoT sensing device group on the medical waste robot; starting the robot and processing data to obtain a multi-dimensional data stream of standard medical waste; obtaining medical waste production prediction information and simultaneously collecting the robot's working status information; determining a robot work scheduling scheme; controlling the robot to perform medical waste processing and full-process recording, obtaining a processing data chain, and tracing and managing the process through the data chain. This invention solves the technical problems of low efficiency, exposure risks, and difficulty in rationally scheduling waste processing tasks based on actual conditions in existing medical waste processing processes. It achieves intelligent and automated medical waste processing, improves processing efficiency, reduces occupational exposure risks for processing personnel, and enables rational scheduling based on actual waste conditions, achieving the technical effect of refined management throughout the entire process.

The invention discloses a maintenance plan arrangement method and system considering equipment importance evaluation, and belongs to the technical field of electrics. Weibull distribution is utilized to fit an equipment aging failure process in a maintenance period, and a change curve of an equipment failure rate in the aging failure process is obtained; power distribution system equipment importance degree sorting is realized by using an equipment importance degree evaluation method; screening to obtain key elements of the system; obtaining a final to-be-overhauled equipment set in combination with overhauled equipment information reported by the system; judging a simultaneous stop mutual exclusion relation between the final to-be-overhauled equipment; by considering factors of distributed power supply output and system interconnection switch action, a maintenance plan arrangement model considering equipment importance evaluation is constructed and solved, and a power distribution system maintenance work schedule condition in a maintenance work period and an operation mode of a power distribution system in a corresponding maintenance construction period are obtained; the maintenance plan adjustment amount, the maintenance plan uniformity and the power failure loss of the system in the maintenance work development period are calculated. And rapid compilation of a power distribution system maintenance plan is realized.

An example of a method of creating preferred work assignments for nursing workers includes receiving a first set of attributes for a first nurse including one or more attributes that describe the first nurse, receiving a plurality of shift constraints for a plurality of shift variables, generating a preferred work assignment, and outputting an indication of the preferred work assignment. The preferred work assignment is generated by optimizing, using an optimization algorithm, shift variables for the first nurse using a computer-implemented machine learning model, the first set of nurse attributes, and the plurality of shift constraints. The first preferred work assignment is predicted by the optimization algorithm to reduce a first resignation probability of the first nurse according to outputs from the computer-implemented machine learning model and the computer-implemented machine learning model is configured to relate resignation likelihood to shift variables and nurse attributes.

To provide a system for supporting a sub-business optimal to an individual user.SOLUTION: A system, comprising: inputting means for a user to create an account and input information on skills, hobbies, work experience, and lifestyle; receiving and storing the information inputted by the user in a database; generating a sub-business idea using a AI engine based on the information stored in the database; presenting the sub-business idea to the user; generating a schedule of sub-business work based on schedule information of the user; evaluating marketability of the sub-business idea and the schedule and providing feedback; and providing specific procedures and resources for starting the sub-business.SELECTED DRAWING: Figure 1

A method for hierarchical work scheduling includes consuming work items at a first scheduling domain having a local scheduler circuit and one or more work group processing elements. Consumption of the work item produces a set of new work items. The local scheduler circuit then allocates at least one new work item of the set of new work items to be executed locally at the first scheduling domain. If the local scheduler circuit of the first scheduling domain determines that the set of new work items includes one or more work items that, if scheduled for local execution, would cause the first scheduling domain to work overloaded, then the work items are assigned to a next higher-level scheduler circuit in a scheduling domain hierarchy, to redistribute to one or more other scheduling domains.

The invention discloses a multi-team collaborative operation scheduling method and system based on an improved whale optimization algorithm, and the method comprises the steps: taking the minimization of the maximum completion time and the minimization of the maximum team task load as a dual-objective function for the condition that a plurality of teams need to cooperatively process the same workpiece; a scheduling model oriented to multi-team continuous collaborative operation is constructed, a whale optimization algorithm including task sequence and team collaborative double-layer discrete coding is adopted for solving, and improved operators such as multi-strategy whale group initialization, multi-strategy whale search, multi-strategy whale predation and multi-dimensional similarity calculation are designed for multi-team continuous processing features. According to the method, the shift continuity and the rest time constraint are directly mapped through a task and team double-layer coding mechanism, the target function is constructed based on the shift index, the optimization efficiency of multi-team collaborative scheduling is remarkably improved, and the method is widely applied to long-period multi-team collaborative manufacturing scenes of large spacecraft cabin structural members, high-speed rail carriages, ships, heavy machinery and the like.

We provide the system. [Solution] A device and means for acquiring and recording construction condition information, A device and means for evaluating information on multiple contractors based on acquired construction condition information and selecting an appropriate contractor, A device that automatically places construction orders with selected contractors, A device that recognizes the worker's operational status in real time and presents the optimal work schedule, A device and means for collecting construction progress data and updating the contractor's capability database, A device and means that provides an interface for displaying the construction progress status on a smartphone and remotely monitoring the project's progress, A system that includes this.

The invention discloses an urban elevator cluster power-saving monitoring system based on AI learning, relates to the field of elevator control and energy saving, and aims to solve the problems that in a traditional system, a single elevator runs disorderly, a power-saving strategy is not iterated and is very fixed, AI application is not wide, and monitoring is not completely covered. The system comprises a centralized control management unit, a transmission layer and a field control unit. The centralized control management unit comprises a monitoring platform and a sensing layer AI learning module, the monitoring platform can realize data visualization, abnormity alarm and remote intervention, and the sensing layer AI learning module is responsible for data preprocessing, strategy model training and iterative optimization. The field control unit can collect elevator energy consumption, people flow and running state data and can also execute start-stop control, speed adjustment, standby dormancy and other power-saving actions. According to the invention, elevator cluster co-work scheduling and continuous electricity-saving efficiency are realized, the operation and maintenance cost of the elevator is reduced, and the elevator waiting time of the user is shortened.

The invention discloses an intelligent scheduling method and system for a medical waste robot based on the Internet of Things, and relates to the technical field of the Internet of Things, and the method comprises the steps: installing an Internet of Things sensing equipment group on the medical waste robot; the robot is started, and standard medical waste multi-dimensional data flow is obtained through data processing; medical waste production prediction information is obtained, and meanwhile working state information of the robot is collected and obtained; determining a robot work scheduling scheme; and the robot is controlled to execute medical waste treatment and whole-process recording, a treatment data chain is obtained, and control is traced through the data chain. The technical problems that in the existing medical waste treatment process, manual operation efficiency is low, exposure risks exist, and waste treatment tasks are difficult to reasonably arrange according to actual conditions are solved, intelligent and automatic medical waste treatment is achieved, the treatment efficiency is improved, the occupational exposure risks of treatment personnel are reduced, and the medical waste treatment efficiency is improved. And reasonable scheduling can be realized according to the actual condition of the garbage, and the technical effect of whole-process fine management is realized.

The invention provides an automatic mobile robot work scheduling method, system and device and a medium. The number of automatic mobile robots completing a current task is determined by combining the actual utilization rate of the automatic mobile robots, the starting number of the devices is dynamically adjusted, unnecessary device operation time is shortened, energy waste is reduced, and reasonable utilization of device resources is ensured. In addition, the automatic mobile robot is monitored in real time, whether the scheduling task is added or not is determined according to the state of the automatic mobile robot, and the situation that the automatic mobile robot completing the task is added into the scheduling task and task completion is delayed is avoided.

In some examples, a system receives a first work unit to be scheduled in the system, the system includes a plurality of processing unit sets for executing the work unit, wherein each respective processing unit set in the plurality of processing unit sets is associated with a corresponding scheduling queue. The system selects a candidate set from the plurality of processing unit sets for the first work unit according to a first criterion; and enqueues the first work unit in a scheduling queue associated with the selected processing unit set selected from the candidate set according to the selection criterion.

The application discloses a multi-end cooperative intelligent scheduling platform and method for flexible labor management, and particularly relates to the technical field of labor management, and comprises the following steps: a preset scheduling rule algorithm performs work scheduling according to flexible labor requirements, and generates a scheduling arrangement form each time; in each scheduling period, a feature set affecting scheduling is extracted, the fairness and rationality of work arrangement are evaluated, and an evaluation report is generated; according to the evaluation report, a feedback signal is generated to determine whether to optimize the scheduling rule algorithm. In the optimization process, an optimization scheme is designed through the feedback signal, the scheduling algorithm is iteratively trained, the scheduling algorithm is better adapted to the labor requirements, the work distribution is ensured to be more fair and reasonable, and the optimized algorithm is applied to scheduling in the next period; the application can scientifically evaluate whether the task distribution is fair and reasonable, can perform targeted optimization training on unreasonable parts in the task distribution, and gradually realizes that the task distribution in the labor environment is more scientific and efficient.

The application provides a work order allocation method and related device, electronic equipment, medium and program product. The method comprises the following steps: obtaining a production task, determining a production performance priority according to the production task; determining a target production process from the multiple production processes according to the production performance priority; obtaining historical production data of each production personnel in a production personnel to which a to-be-allocated work order belongs; determining a target production personnel according to the target production process and the historical production data of each production personnel; determining a target work order associated with the target production process; and allocating the target work order to the target production personnel. By implementing the application, suitable production personnel can be arranged at suitable work posts to realize reasonable work arrangement and facilitate reasonable allocation of production resources under the condition of meeting the demand of the production task.