50 results about "Planning process" patented technology

The invention relates to a resource allocation and process planning optimization method under complex constraint conditions, which comprises the following steps of: representing various constraint conditions of a process planning process by utilizing a double-layer directed acyclic graph, and generating and constructing an initial feasible solution set meeting all the constraint conditions; initializing a state space, wherein the state space comprises state variables of a process number, an average process length, reward value fluctuation and fitness; noise is collected and coupled to a Q network, action selection is carried out, and low-level heuristic algorithm options are output; generating a new taboo sequence by using the selected low-level heuristic algorithm, and optimizing the current feasible solution; switching a low-level heuristic algorithm according to the improvement amplitude and the execution duration; and outputting an optimal processing feature sequence and process division combination after multiple times of training. Compared with the prior art, the method has the advantages that multiple process decisions can be optimized at the same time, sub-optimal results caused by separate optimization processes are avoided, processing time and resource consumption are remarkably reduced, and production efficiency and scheme adaptability are improved.

The embodiment of the invention provides an enterprise information architecture (4A)-based AI Agent planning enhancement system, a control device and equipment, and the system comprises a Prompt construction module which is used for analyzing an unstructured demand to obtain a structured demand, and cooperating with other modules to generate a standardized Prompt comprising a business process, a data entity and a tool strategy; the knowledge matching module is used for matching related knowledge based on a knowledge graph employment number fusion knowledge base and sorting the related knowledge into a knowledge list containing business processes, practical experience, a data list and a tool list; and the context reasoning module is used for generating a reasoning result based on the historical data and the knowledge list and feeding back the reasoning result to the Prompt construction module so as to assist in generating the normalized Prompt. According to the system, the integration capability of the AI Agent on business logic and data resources in the task planning process is remarkably improved, so that the AI Agent can more accurately understand enterprise-level business scenes, and standardized and intelligent planning support is provided for practical application of the AI technology in enterprise digital transformation.

The invention relates to the technical field of computers, and discloses a model training method, electronic equipment, a readable storage medium and a program product, which can realize the planning of an autonomous generation task of a task model and improve the performance and generalization ability of the model. The method comprises the steps of obtaining task demand information of a first task model; and according to the task demand information, controlling an intelligent agent represented by the task model to execute a plan corresponding to the user interaction task, and generating a process reward and a result reward of each planning process in the plan. And then, according to the process reward and the result reward, obtaining a plurality of adjusted planning processes. And furthermore, according to the task demand information, the first task model is controlled to execute the adjusted planning processes, and a plurality of new process rewards and new result rewards are generated. Then, according to the new process reward and the result reward, it is judged that the multiple adjusted planning processes take effect; and training the first task model according to the adjusted planning processes.

The invention discloses a multi-AGV task allocation method in an intelligent picking warehouse based on a Hungary algorithm. The method is fused with path planning framework rolling time domain conflict resolution (RHCR) for use. According to one method, a dynamic allocation mechanism is adopted, and the one-to-one correspondence relationship between the AGV and the task is not fixed before the AGV actually arrives at a pickup point; and 2, constructing a periodic redistribution strategy, and calling a Hungary algorithm to carry out redistribution after each RHCR planning cycle is ended. According to the method, a task allocation process is decomposed into a multi-round assignment problem, information brought by a planning process is fully utilized for allocation through a Hungary algorithm, an AGV task execution sequence is dynamically adjusted according to a staged allocation result, and deep collaboration of task allocation and path planning is realized. Compared with a traditional allocation method in which task allocation is regarded as an independent process, the method provided by the invention effectively improves the operation efficiency of the AGV system on the premise of ensuring that the calculation complexity is only the sum of multiple independent Hungary algorithms.

The invention relates to an aviation typical structure assembly sequence planning method and system and a storage medium, and the method comprises the steps: carrying out the feature recognition of a product three-dimensional mathematical model of an aviation typical structure, and obtaining a recognition result of the assembly features of the aviation typical structure; analyzing the recognition result into structured data, and constructing an assembly structure diagram model based on the structured data; and performing assembly sequence planning on the aviation typical structure by using the assembly structure diagram model to generate a final assembly sequence. The problems that the assembly sequence planning process depends on artificial experience and judgment, the design time is long, and the efficiency is low can be solved, and the efficiency and quality of assembly sequence planning are improved.

The present invention relates to the technical field of energy planning, and specifically discloses a source-storage-transmission joint planning method considering carbon emission responsibility sharing. The method includes: establishing a two-layer carbon emission responsibility sharing strategy; based on the two-layer carbon emission responsibility sharing strategy, establishing a source-storage-transmission joint planning model considering carbon emission responsibility sharing; solving the source-storage-transmission joint planning model considering carbon responsibility sharing to obtain an optimal joint planning scheme for the system's source-storage-network. According to the principle of "who causes, who bears, who governs, and who benefits", this method scientifically shares carbon emission responsibilities, effectively considers the role of carbon emission responsibilities in the planning process, adds energy storage systems, improves system flexibility, and promotes the consumption of renewable energy.

The invention discloses a planning process generation method based on a block chain. Comprising the following steps of full-link marketing data collection and block chain evidence storage, planning process template creation, planning demand and multi-source data chaining, intelligent planning scheme generation, task decomposition and intelligent contract driving, planning process full-link tracing, on-chain data intelligent analysis and feedback and automatic settlement and optimization iteration. The invention discloses a planning process generation system based on a block chain. The system comprises a data acquisition and evidence storage module, a template management module, a demand and data processing module, an intelligent planning engine module, a task execution and cooperation module, a full-link data acquisition module, a data analysis and feedback module and a tracing and redisk module. The invention belongs to the technical field of planning process management, and particularly provides a block chain-based planning process generation method and system of an intelligent marketing ecosystem, which integrate intelligent planning, block chain credible cooperation and full-link data credible analysis.

The application relates to the technical field of hydrology and water resources simulation, and discloses a SWAT watershed hydrology model task planning system, method and product, which comprises a knowledge graph construction module, an embedded index construction module, a query coding and two-stage retrieval module, a context construction module and a large language model task planning module. Through the complete planning process of knowledge graph modeling, vector index construction, two-stage retrieval, context generation and structured task output, the whole-process intelligentization from a user's natural language demand to SWAT watershed hydrology model executable task planning is realized, the SWAT file / parameter structure can be accurately matched, the professionalism, accuracy and executability of task planning are improved, and the problems of high operation threshold, large artificial workload, unstable and unexecutable output of a general large model of a traditional SWAT watershed hydrology model are solved.

The application provides a man-machine cooperative cognitive decision space construction and on-the-spot decision method, that is, in the action planning process, on the basis of the main line action plan designed based on the static task purpose, a person estimates possible variables in action execution in advance, refines situation cognitive characteristics of key decision points, and proposes countermeasures, the system explores diversified possible action processes, analyzes and excavates key variables which have greater influence on action results, explores the best action options under the guidance of countermeasures and trains a dynamic planning intelligent agent, finally, the cognitive characteristics and countermeasure options, the planning intelligent agent are added to the main line action plan, and a cognitive-decision space is constructed; in the action execution process, the cognitive-decision space is used to guide the real-time monitoring of the change of situation characteristics and the dynamic triggering of key decision points, the online optimization of the best countermeasure and the dynamic generation of subsequent action planning.

The invention provides a land space planning scheme processing method, device and system and electronic equipment, and the method comprises the steps: responding to a received planning scheme, calling a space analysis tool and / or a planning knowledge base by at least two agents, and obtaining a sensing result; generating a judgment result according to the perception result and predetermined target preference information; calling a pre-configured structured expression template, and generating negotiation messages respectively corresponding to the at least two agents; information interaction is carried out between the at least two agents based on an agent interaction protocol A2A; evaluating the planning scheme and the like to obtain correction suggestion information; and processing the correction suggestion information proposed by the plurality of second intelligent agents, selecting one instruction as a processing result and issuing the processing result to the corresponding second intelligent agent, ending negotiation if the current state meets the convergence condition, and starting the next round if the current state does not meet the convergence condition. The method can improve the information interaction efficiency in the land planning process.

The invention discloses an unmanned ship integrated path planning method based on space-time state search and optimization. The method comprises the following steps: constructing a unified space-time state space and dynamic model; performing forward search based on the space-time state space to generate a preliminary feasible trajectory; performing continuous space-time optimization on the preliminary trajectory to generate a smooth executable trajectory; performing online rolling execution and local re-planning; according to the method, a search space is lifted from a traditional two-dimensional geometric position to a four-dimensional space-time state space containing speed, course and time, and geometric accessibility, dynamic feasibility and space-time collision-free performance are synchronously considered in a unified framework. Different from an existing separated architecture that the path is planned first and then the speed is adjusted, an integrated track containing position, course, speed and time information is directly generated in the planning process, the problem that planning and execution are disjointed is fundamentally solved, and it is ensured that the planning result can be directly executed.

The invention provides an on-orbit spacecraft sensitive shortcut operation control planning mode design method and system. The on-orbit spacecraft sensitive shortcut operation control planning mode design method comprises the following steps: determining a spacecraft operation control planning process design strategy; designing an operation and control planning process; establishing an information interaction model between operation and control planning implementation systems; and determining an implementation method of the operation and control planning process. According to the technical scheme, the operation and control planning process adopts a design strategy of'two-layer planning and staged iteration ', a step-by-step progressive information interaction model is established, and efficient and agile implementation of the operation and control planning process is ensured.

The application provides a new line railway transmission and data network port intelligent planning method and system, relates to the railway communication technical field, and solves the technical problems of low efficiency, easy error and difficulty in meeting complex design specifications caused by the dependence of the existing railway communication port planning on manual experience. The method comprises the following steps: obtaining a business requirement list and a device resource list; constructing a constraint optimization model based on a preset port planning rule library; based on the business requirement list and the device resource list, the constraint optimization model is optimized and solved by a constraint optimization algorithm to obtain a port allocation result; based on the port location in the port allocation result and the physical distance between the device cabinet and the ODF frame, the tail fiber length is calculated; the port allocation result and the tail fiber length are structured and coded and integrated to obtain a port configuration account. The application is used in the new line railway transmission and data network port planning process.

The application discloses a master-slave satellite task allocation method based on a double-layer backtracking mechanism, constructs a master-slave satellite cooperative task planning model with a target function of maximizing the efficiency generated by the master-slave satellite in executing tasks according to obtained master-slave satellite task planning requirements and constraint conditions, performs task planning conversion based on a Markov decision process (MDP), defines a state space, an action space and a reward function, solves the master-slave satellite cooperative task planning model by using a deep reinforcement learning (DQN) algorithm, performs task planning optimization through a double-layer backtracking mechanism, and obtains a task allocation strategy of the master-slave satellite based on the solved master-slave satellite cooperative task planning model. The double-layer backtracking mechanism is designed, a high-cost and low-yield planning decision is dynamically adjusted in a task planning process in a manner of combining global backtracking with local backtracking, resource waste and task conflicts are avoided, and the rationality and robustness of task allocation are improved.

The invention discloses an engineering task dynamic re-planning method, which relates to the technical field of engineering task dynamic re-planning, and comprises the following steps: collecting equipment space coordinates, operation surface point cloud data and task completion amount in real time through multiple sensors, and calculating a progress deviation value; generating a progress thermodynamic diagram covering the construction area based on a preset engineering task digital twinborn body; performing grading response judgment according to the progress deviation value, and triggering an early warning process or a re-planning process according to a response grade; and calling the multi-objective optimization model and solving to generate a re-planning scheme when the re-planning process is triggered, performing deduction simulation based on the real-time state data of the equipment in the digital twin sand table, and outputting the predicted construction period completion degree, the cost change rate and the risk triggering probability after the re-planning scheme is executed. According to the invention, differential response of early warning and re-planning is realized by adopting a hierarchical trigger mechanism; and the precision and timeliness of construction progress monitoring and the scientificity and feasibility of scheduling decisions are improved.

This disclosure relates to a multi-objective, two-layer optimization method and apparatus for a multi-regional integrated energy system. The method includes: establishing an upper-layer multi-objective programming model and a lower-layer optimization scheduling model; using the unit capacity of various types of energy supply units as initial values, generating velocity and position expressions for upper-layer particles based on a particle swarm optimization algorithm; solving the expression using a Gurobi solver to generate the daily power output state of various types of energy supply units in the multi-regional integrated energy system; updating the velocity and position expressions of the upper-layer particles based on the upper-layer multi-objective programming model and iteratively calculating; stopping the iteration when preset conditions are met, and calculating and generating a capacity configuration scheme for the multi-regional integrated energy system based on the velocity and position expressions of the upper-layer particles. This disclosure's two-layer optimization strategy incorporates the system's operational characteristics into the planning process, improving the feasibility of the planning scheme; regional energy mutual assistance can optimize the system's operation mode and improve overall efficiency.

The present invention relates to the technical field of aircraft manufacturing, and more specifically, to a fuselage skin AO planning method, system, device, and medium based on typical features. The method first obtains fuselage skin data based on acquired three-dimensional model data and constructs a fuselage skin library. Secondly, based on the aircraft three-dimensional model, a fuselage skin typical planning feature library is extracted and constructed. Then, the fuselage skin typical planning feature library is analyzed, and combined with knowledge graph technology, the relationship between the features and the skin is clarified, the fuselage skin AO is inferred, and a full-aircraft fuselage skin assembly content set is formed. Finally, a graph traversal algorithm is called to check the completeness of the full-aircraft fuselage skin assembly content set. This improves the structured expression of the fuselage skin AO planning process and effectively enhances the planning efficiency and accuracy.

The present invention relates to systems and methods for intelligently optimizing supply chain is provided. In particular, the systems and methods provide the capability to configure supply chain systems so as to: balance between cost and service is optimised and profitability maximised; configure system parameters to respond to both current and future risks; ensure that variability is built into plans enabling maximised efficiency; and human error and bias are eliminated from the planning process such that pro-active rather than reactive behaviour becomes the norm.

The invention provides a new line railway transmission and data network port intelligent planning method and system, relates to the technical field of railway communication, and solves the technical problems that the efficiency is low, errors are easy to occur and complex design specifications are difficult to meet due to the fact that existing railway communication port planning depends on artificial experience. The method comprises the following steps: acquiring a business demand list and an equipment resource list; constructing a constraint optimization model based on a preset port planning rule base; based on the business demand list and the equipment resource list, performing optimization solution on the constraint optimization model through a constraint optimization algorithm to obtain a port allocation result; calculating the length of the tail fiber based on the port position in the port distribution result and the physical distance between the equipment cabinet and the ODF frame; and carrying out structured coding and integration on the port allocation result and the tail fiber length to obtain a port configuration ledger. The method and the device are used in a new line railway transmission and data network port planning process.

The application relates to a contact type machining robot motion planning method based on deep reinforcement learning, which comprises the following steps: firstly, based on DH parameters and homogeneous transformation matrix, a position level forward and inverse kinematics model between a six-degree-of-freedom mechanical arm end state vector and a base and joint motion vector is established; secondly, considering constraints such as a machining task, a feeding speed, a feeding angle and the like, a multi-stage reward function is designed for operation parameter planning; then, a network structure is designed based on a double-delay deep deterministic policy gradient, and three-level optimization is carried out on the algorithm; finally, according to the network structure, a planning process is designed, and the application is applied to a planning task of an intelligent contact type machining mechanical arm system taking grinding and polishing machining as an example. The application can realize real-time optimization and control of various machining parameters of the contact type machining process through autonomous learning, and can be used for intelligent and safe planning under the condition of contact type machining process dynamics coupling.

The invention discloses a spatial layout planning method for a cascade silt arrester group. According to the method, the debris flow energy regulation and control intensity F of the ladder dam group is decomposed into three indexes including the dynamic energy dissipation rate, the potential energy storage rate and the total energy net loss ratio, a mathematical model among the three indexes including the dam group relative height difference Z and the F value is established, and the problem of overall layout around the blocking function level in dam group planning is solved. According to the optimization method, spatial elevation parameters are introduced, and the problem of collaborative measurement and calculation of the number, the dam height, the dam spacing and the Z value of the silt arrester is solved; and different collaborative measurement and calculation methods are provided for construction projects of different prevention and treatment targets. According to the method, overall planning is conducted on space and structure parameters of an elevator dam group by adopting a systematic perspective, and multi-level design parameters are coordinated in series model expressions of indexes of energy regulation and control intensity by utilizing a function model, so that the planning process can always reflect systematicness of the elevator dam group and collaborative development of internal units of a dam group system. The method can also be used for guiding transformation planning of an in-service ladder dam group.

The invention provides a travel planning method, device and equipment, a storage medium and a program product, relates to the technical field of aviation travel services, and aims to provide a coherent one-stop travel route planning service, simplify the planning process and improve the planning efficiency. The method comprises the following steps: acquiring travel demand information of a user; based on the travel demand information of the user, performing keyword search and matching on the data in the database to obtain at least one travel planning scheme meeting the travel demand; the database comprises data matched with the travel demand information of the user; and sorting the at least one travel planning scheme to obtain an optimal travel planning scheme.

The application discloses a path planning method and device, equipment, storage medium and program product. The method comprises the following steps: acquiring a to-be-planned region corresponding to a to-be-planned path, and determining a starting point and a target point of the to-be-planned path; generating a skeleton graph of the to-be-planned region; the skeleton graph is formed by connecting a plurality of skeleton lines, the skeleton lines are generated along a region between two adjacent obstacles and a region between an obstacle and an edge of the to-be-planned region; determining a sampling point in the range of the skeleton line, sampling in a preset step range along the skeleton line based on the sampling point to determine an expandable point; updating the expandable point to the sampling point until the expandable point determined based on the updated sampling point meets a planning end condition, and then generating a planning path based on the starting point, at least one sampling point, at least one expandable point and the target point. By using the method, the calculation amount in the path planning process is effectively reduced while ensuring the sampling integrity.

The application relates to the technical field of computers, and discloses a model training method, an electronic device, a readable storage medium, and a program product, which can realize autonomous generation of task planning of a task model, and improve model performance and generalization capability. The method can obtain task requirement information of a first task model; according to the task requirement information, control an agent represented by the task model to execute planning corresponding to a user interaction task, and generate process rewards and result rewards of each planning process in the planning. Then, according to the process rewards and the result rewards, adjusted multiple planning processes are obtained. Further, according to the task requirement information, the first task model is controlled to execute the adjusted multiple planning processes, and multiple new process rewards and new result rewards are generated. Subsequently, according to the new process rewards and the result rewards, it is judged that the adjusted multiple planning processes take effect; and then the first task model is trained according to the adjusted multiple planning processes.

This invention discloses a method for spatial layout planning of a cascade dam group. The method modulates the energy regulation intensity of the dam group on debris flows. F The relative elevation differences of the dam group are determined by three indicators: kinetic energy dissipation rate, potential energy storage rate, and total net energy loss ratio. Z and F A mathematical model among the three indicators is used to address the overall layout problem in dam group planning centered on the level of retaining function. The optimization method incorporates spatial elevation parameters to address the relationship between the number of silt-trapping dams, dam height, dam spacing, and... Z This invention addresses the issue of collaborative calculation among different values ​​and provides different collaborative calculation methods for construction projects with varying prevention and control objectives. The method adopts a systematic perspective for the overall planning of the spatial and structural parameters of cascade dam groups. It utilizes functional models to coordinate multi-level design parameters within a series of model expressions for energy regulation intensity indicators, ensuring that the planning process consistently reflects the systematic nature of the cascade dam group and the synergistic operation of its internal units. The method can also guide the retrofitting planning of cascade dam groups currently in service.

The application relates to the technical field of aircraft manufacturing, and discloses an aircraft component assembly detailed process design method, system and medium, which comprises the following steps: establishing a process procedure template corresponding to an assembly scene according to an assembly process flow and a standard process procedure library; planning process procedure nodes and process procedure materials from the two dimensions of an assembly scene space and time; establishing a process parameter library according to process knowledge and process rules; and finally automatically preparing process procedure documents, so that the aircraft component assembly detailed process is efficiently and accurately designed, and the technical problems of the existing aircraft assembly process design and process procedure preparation, such as the failure to combine the process procedure preparation with the assembly process flow, the low process procedure preparation efficiency and the low process procedure preparation accuracy are solved.

The application discloses a kind of high renewable energy penetration rate power system planning method considering the influence of extreme weather, belong to power system planning field. Including obtaining target planning area annual operation data;Typical operation scene is constructed based on the data obtained;Wherein typical scene includes conventional scene and extreme weather scene;Power system planning model is constructed based on typical scene;The model aims at minimizing annual cost while relieving the power system energy imbalance problem caused by extreme weather;Solving the planning model obtains final planning scheme.The present application can solve the problem that power system planning model is difficult to include the influence of extreme weather event into planning process, resulting in the problem that planning result is difficult to cope with energy supply under extreme weather event.

The invention relates to a planning method for planning a configuration structure and a procedure for a production unit for implementing a production process on a product in the production unit, wherein in a definition step 100 the product with the associated production information is defined, wherein in a selection step 200 a selection of selection substructures is made, wherein the selection substructures are suitable for use in the production process, and wherein the selection substructures form a set of selection substructures; wherein in a configuration step 300 a planning configuration structure of the production unit is generated from a plurality of target substructures, wherein the target substructures are formed from a subset of the selection substructures of the set of selection structures;wherein in a procedure generation step 400 a planning procedure with procedure steps for implementing the production process is formed with the planning configuration structure of the production unit; wherein in a coordination step 500 the planning procedure and the planning configuration structure are coordinated with each other in order to obtain the configuration structure and the procedure for the production unit for implementing the production process.

The invention relates to the technical field of process engine control, and discloses a training planning process control method and system based on an Activity process engine. The method comprises the following steps: extracting an instance state snapshot from a process engine, analyzing to construct a time trajectory map of process evolution, marking a key path and a branch point, and generating a process evolution mode template library; and the current evolution stage is accurately determined by matching the real-time process with the template. And then dynamically loading a corresponding control strategy, analyzing the rule to generate a node-level operation instruction, and converting the node-level operation instruction into a model adjustment command which can be identified by an engine. Synchronously monitoring the synchronization state of the resource consumption and the flow track, and automatically calculating a resource quota adjustment scheme when deviation occurs. And finally, cooperatively scheduling a model adjustment command and a resource scheme, forming a control instruction set, and distributing the control instruction set to an engine and a resource manager to realize efficient and adaptive evolution of a flow according to an expected path. According to the invention, the intelligent level of process management and the resource utilization efficiency are improved.

The invention discloses a near-earth orbit spacecraft implementation layer task planning method and equipment, and belongs to the technical field of spaceflight. The method comprises a core planning process, a constraint processing process, a cooperative work process and a staged iteration process. The core planning process comprises demand submission, event layer planning, instruction layer planning and result confirmation; the constraint processing flow comprises constraint carding, initial arrangement, conflict detection, conflict resolution and planning result implementation; the cooperative workflow comprises resource constraint release, demand submission, plan generation, feedback adjustment, countersigning confirmation and operation control implementation; the staged iteration process comprises pre-planning, monthly planning, weekly planning and real-time re-planning. According to the method, a two-layer planning, multi-party cooperation and staged iteration mode is adopted, complex tasks are adapted, resource configuration is optimized, and cooperation efficiency and real-time response capability are improved.