18 results about "Group cooperation" patented technology

The invention provides a die cutting equipment error optimization method and system based on group collaboration, and relates to the technical field of die cutting machines, and the method comprises the steps: carrying out the spectrum analysis of a frequency characteristic curve of each piece of die cutting equipment, so as to divide an initial interference group; establishing a virtual spring damping network in the initial interference group, regarding each die cutting device in the initial interference group as a mass point, and determining a spring stiffness coefficient and a damping coefficient according to an actual distance between adjacent mass points; determining vibration mode characteristics of each die cutting device according to the spring stiffness coefficient and the damping coefficient, and converting a control signal generated according to the vibration mode characteristics into a parameter adjusting variable by using a preset control algorithm; and determining a vibration coupling relationship according to the collected vibration energy data of the initial interference group after the initial processing parameters are adjusted according to the parameter adjusting quantity, and determining an optimal production takt and a parameter compensation value according to the vibration coupling relationship. The technical problem that in the prior art, due to vibration coupling of a die cutting equipment group, the machining error cooperative control difficulty is large is solved.

The invention discloses an agent-based instant messaging group cooperation method and device, a medium and a program product, and is applied to a client, and the method comprises the steps: sending a super group creation request to an instant messaging server, and triggering the instant messaging server to automatically bind a default digital intelligent employee for a super group as a super group assistant; when a dialogue message is generated in the group, pushing the dialogue message to the instant messaging server, and triggering the instant messaging server to send message data to the intelligent server; triggering the intelligent server to carry out real-time intention analysis, and assembling service message data when a service intention is recognized; the service message data from the intelligent server is received through the instant messaging server, replied in a super group assistant identity and displayed in a service message card form, and a corresponding service process can be triggered through clicking. According to the invention, the AI intelligent agent and the instant messaging group are deeply combined, the communication-service-intelligence fused cooperation is realized by using group communication, and the enterprise cooperation efficiency and the service processing capability are improved.

The application discloses a kind of multi-agent cooperation decision-making method and device based on behavior characteristic quantification modeling and weak connection mechanism.The method quantitatively evaluates the impulsivity level of each agent, and establishes a weak connection interaction influence mechanism based on this to adjust the information interaction weight between agents, thereby effectively weakening the negative interference of impulsive individuals on group cooperation strategy. This method can be flexibly embedded in mainstream multi-agent reinforcement learning framework, improving the robustness and overall performance of multi-agent system containing behaviorally unstable individuals in cooperative tasks.

The invention discloses a task scheduling method, system and device, a medium and a product, and the method comprises the steps: screening a management node from available computing nodes in response to a project task set, so as to enable the management node to cooperate with the remaining available computing nodes to form a computing resource group; receiving a group cooperation efficiency improvement coefficient of the computing resource group uploaded by the management node, and obtaining the efficiency workload of the computing resource group according to the group cooperation efficiency improvement coefficient; according to the efficiency workload, assembling the project task set into batch task groups, and issuing the batch task groups to the management node, so that the management node assigns and executes the batch task groups; and in response to an assignment completion notification of the management node, updating the available computing nodes. By adopting the embodiment of the invention, the project task can be autonomously dispatched and executed in combination with the collaboration capability of the computing node, and the task processing efficiency is effectively improved.

The present application relates to the technical field of group recommendation, in particular to a personalized group recommendation method fusing student behavior information, which comprises the following steps: 1) data preprocessing; 2) student multi-behavior modeling; 3) student preference and item structure acquisition; 4) group consensus modeling; 5) model prediction and optimization. The present application utilizes the behavior information of students and designs a group consensus strategy to provide effective learning resources for group cooperative learning.

The invention relates to a micro-grid group scheduling method based on an improved MASAC algorithm, and belongs to the technical field of micro-grid group scheduling. The method comprises the steps of designing a cooperation mechanism fitting a real scene by considering conflicts between individual interests and collective interests among different micro-grids; and a micro-grid group coupling model is built by taking economic benefits and safety as targets. Due to the fact that the model has high non-linear features and the cooperative relation is complex, an attention mechanism is introduced to enhance feature learning and agent interaction modeling capacity, an improved AM-MASAC method (AM-MASAC) is used for achieving real-time scheduling, and new energy uncertainty is effectively dealt with; simulation verification and comparative analysis are designed to verify the effectiveness of the model and the method. The method is used for solving the problem of multi-microgrid cooperation real-time optimization. A dual incentive mechanism based on historical contribution and instant transaction is established, the problem of micro-grid group cooperation in a real-time market is solved, and a complete multi-micro-grid cooperation optimization framework is established.

The application discloses a kind of fast road interweaving area intelligent network connection vehicle dynamic grouping method, belong to intelligent transportation and vehicle networking collaborative control technical field, comprising:A. based on the dynamic grouping rule of longitudinal position;B. based on the dynamic grouping update period adjustment of communication link quality;C. group cooperation control strategy;D. group cooperation control strategy;E. real world fast road interweaving area grouping method calibration, the advantages of the application are: by real-time dynamic grouping, the global cooperative control problem of complex intelligent network connection vehicle in fast road interweaving area is decomposed into multiple local sub-problems, simplify the complex vehicle interweaving problem, thereby reduce the complexity of problem solving.For target vehicle with lane-changing demand, suitable gap is created, and smooth and efficient merging and exiting of vehicles is realized.Time and space resources are fully utilized, and the collaboration capability of CAV is exerted, thereby improving the safety and traffic efficiency of fast road interweaving area.

This invention discloses a method and system for collaborative management and dynamic adjustment of sewing machine group production line balance. The method includes: merging all tasks to be processed belonging to the same process category into a central task pool and randomly and dynamically assigning the tasks to sewing machines in the sewing machine group; collecting real-time operating data and constructing a dynamic device state vector for each sewing machine in the group through an IoT sensor module installed on each sewing machine; inputting the dynamic device state vector of each sewing machine and the remaining task sequence into a dynamic task allocation model based on multi-objective optimization to obtain the subsequent dynamic task allocation scheme for each sewing machine; periodically evaluating the balance index of the sewing machine group production line and initiating a dynamic rebalancing mechanism to adjust the production line task flow in real time. This ensures the adaptability of the assigned tasks to each sewing machine, guarantees dynamic response, and ensures the utilization rate of each sewing machine.

To provide an image forming system and the like that can easily change a group to process a print job in a connection destination group cooperation function related to print release.SOLUTION: An image forming system has a plurality of groups to which one or more image forming apparatuses operating as master units and one or more image forming apparatuses operating as slave units belong, and causes the image forming apparatuses belonging to the set group to perform image formation. The image forming system comprises a display unit that displays a basic screen that receives an operation instruction to the image forming apparatus, and a control unit that controls screen display of the basic screen. The control unit displays, on the basic screen, a changeover key that receives a changeover instruction to the group designated by a user, and outputs, from the slave units, a print image based on a print job registered in the master units belonging to the group that has been changed.SELECTED DRAWING: Figure 1

The invention relates to the technical field of group control optimization, in particular to a wind turbine group control strategy optimization system based on artificial intelligence, which comprises a state feature extraction module, a cooperative relationship modeling module, a group control strategy optimization module, a control instruction generation module and an execution feedback module. According to the method, through introduction of fusion calculation of unit operation characteristics and a spatial topological relation, multi-source state data is utilized to mine group cooperation characteristics, the energy coupling strength between units can be dynamically identified, and the cooperation influence weight can be quantified, so that self-adaptive optimization of power distribution is realized. A distribution mechanism based on priority regulation logic enables power gap response to have more real-time performance and pertinence, a pitch angle regulation instruction generated through fuzzy control is combined, output of multiple units is accurately matched with the overall load, coordinated operation can still be kept under the multi-wind-speed disturbance and complex operation scene, and the wind power generation efficiency is improved. And the coordination of power distribution, the energy utilization efficiency of the system and the overall operation stability are improved.

Methods, systems, and devices for wireless communication are described. A UE can cooperate with a group of one or more other UEs, where each UE can operate as a panel in a wireless communication system. To ensure that updated information based on the UE's cooperation status is provided to the network, the UE can receive one or more capability request messages from a base station. The UE can determine a group cooperation capability of the UE based on a current group cooperation status of the UE. The group cooperation status can be based on the UE operating in cooperation with a group of UEs to communicate with the base station. The UE can then transmit one or more messages to the base station indicating the group cooperation capability of the UE.

The invention discloses a cooperative control method and system for a low-altitude aircraft, and relates to the technical field of aircraft cooperative control, and the method comprises the steps: obtaining group state information corresponding to a plurality of control nodes based on a dispatching center; dividing based on the group state information to obtain a plurality of task areas; generating an optimal control scheme based on the task area and the group state information to control the corresponding group to work; monitoring emergency situations in the working process of the group in real time based on the dispatching center, generating a first fly-around scheme, and controlling execution of the group; the control node generates a coordination instruction based on the state space data and controls the aircrafts in the group to cooperatively work; the aircraft obtains obstacle information in the working process in real time and automatically avoids obstacles when communication is interrupted. And the dynamic environment adaptability, the group cooperation efficiency and the safety redundancy capability of cooperative control of the low-altitude aircraft are improved.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle wing anti-collision structure which comprises an environment sensing module, a decision control module, a group cooperation module and an execution mechanism module. Compared with the prior art that obstacle detection mainly depends on a single sensor, missing detection or misjudgment is often caused by environmental interference, and a decision-making algorithm has high delay, the scheme of the invention has the advantages that a multi-modal environmental perception fusion architecture and a bionic eagle eye real-time decision-making mechanism are adopted; the advantages of millimeter wave penetrability, infrared heat source capture, terahertz wave imaging and polarized light filtering are creatively integrated, optical flow field analysis and biological heuristic path planning are combined, obstacle recognition precision and collision avoidance response timeliness under complex meteorological conditions are remarkably improved, and full-link efficiency leap from sensing to execution is achieved.

Methods, systems, and devices for wireless communications are described. A UE may cooperate with a group of one or more other UEs, where the UEs may each operate as a panel in a wireless communications system. To ensure updated information based on the cooperation status of the UE is provided to a network, the UE may receive one or more capability request messages from a base station. The UE may determine a group cooperation capability of the UE, based on a current group cooperation status of the UE. The group cooperation status may be based on the UE operating in cooperation with a group of UEs for communicating with the base station. The UE may then transmit, to the base station, one or more messages indicating the group cooperation capability of the UE.

The invention provides a multi-energy complementary power station output prediction method based on dynamic group cooperative optimization, and aims to solve the problems of accuracy and reliability of multi-energy complementary power station output prediction. Different energy power generation units in the multi-energy complementary power station are reasonably grouped through a dynamic group division strategy according to correlation and complementarity of energy power generation and uncertainty of influence of environmental factors and the like on power generation of each energy, so that a dynamically changing group node is formed; according to the technical scheme, the output change trend of the multi-energy complementary power station is more accurately captured, prediction errors are effectively reduced, a more reliable output prediction basis is provided for operation scheduling, power market transaction and the like of the multi-energy complementary power station, and the operation management level and economic benefits of the multi-energy complementary power station are improved.

The invention discloses a fluid pipe network AI intelligent agent based on a group cooperation mechanism. The fluid pipe network AI intelligent agent comprises an energy self-supply module, a multi-dimensional sensing module, an execution regulation and control module, a dual-mode communication module and an AI collaborative decision module. The multi-dimensional sensing module is used for collecting pipe network operation parameters, fault characteristic signals and environment state data; the dual-mode communication module comprises a long-distance transmission unit and a short-distance instant transmission unit; and the AI collaborative decision-making module is used for carrying out analysis processing on the sensing data, constructing group collaborative logic, generating a regulation and control decision, dynamically optimizing regulation and control parameters and simulating a self-organization behavior of a biological group. According to the invention, by realizing unconscious synchronous regulation and control of multiple nodes, quick response to sudden faults can be completed without intervention of a central platform, the fault processing time is greatly shortened, the loss caused by the faults is reduced, the fault-tolerant capability and the operation reliability of the system are improved, accurate guidance is provided for maintenance work, and the maintenance time is shortened.

The invention relates to the technical field of emergency location uploading, and provides a distributed location information aggregation reporting method and system based on group collaboration. The method comprises the following steps: when a trigger device detects a preset emergency event, generating a cooperative discovery beacon frame, and sending first position information and event session information corresponding to the preset emergency event to response devices in an effective cooperative area; the response device generates response data information containing second position information based on the first position information and the event session information, and sends the response data information to the trigger device; and the trigger device generates aggregation position information based on the first position information and the second position information, and sends the aggregation position information and the event session information to a server. According to the method, the problems that position information reporting of single equipment is limited and position information reporting of a fixed group is lack of flexibility are solved.

The invention belongs to the technical field of individual innovation ability evaluation, and provides a multi-modal data-based multi-user interaction innovation ability evaluation system for solving the technical problems that a traditional evaluation method is insufficient in ecological validity in a real interaction scene and the group cooperation ability is difficult to quantify. The system constructs a standardized creative task situation through a real online conference platform, synchronously collects language texts, voice features and facial expression data of participants, and performs hierarchical feature extraction and fusion modeling on multi-modal data in combination with natural language processing, voice signal processing and emotion recognition technologies, so as to obtain a standardized creative task. The technical scheme comprises the whole process of scene deployment, data acquisition, feature fusion and automatic evaluation, and accurate quantification of the innovation ability of individuals in group interaction is realized. The method is suitable for student ability development evaluation in an education scene and high potential talent selection in an enterprise scene, and has the technical advantages of high efficiency, expandability and adaptation to a real interaction situation.