25 results about "Planning process" patented technology

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 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 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.

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 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 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 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 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.

The invention relates to the technical field of path planning and intelligent scheduling, and provides a path optimization method and device for multi-region goods taking and delivering tasks. According to the method, multi-subarea modeling is carried out on a taking and sending task environment, and a task graph model containing taking and sending task nodes and cross-area connection nodes is constructed so as to describe the structural characteristics of high connectivity in subareas and sparse connectivity between the subareas. In the path planning process, intra-region structural features of task nodes in the sub-regions and cross-region communication features among different sub-regions are extracted respectively, and the features are fused according to the current path state. On the basis, a candidate target node set is generated through a planning stage, taking and sending task nodes which are actually accessed are determined in an execution stage, and the path state is updated step by step until path planning is completed. The method takes a structured decision process as a core, and is suitable for a path optimization scene of a multi-subarea taking and sending task.

The invention discloses a method for generating a ship position arrangement diagram in a dock, particularly relates to the technical field of ship construction, and solves the technical problems that in the prior art, a ship position arrangement diagram is generally manually drawn by planners, and multiple constraint conditions such as dock scale, ship size, shipping date and object quantity are comprehensively considered in the planning process; the technical problem that objective and effective evaluation and optimization means are lacked due to the fact that the method depends on experience and judgment ability of planners is solved. According to the technical scheme, a project operator and a space search algorithm are introduced, under the constraint condition, multiple sets of initial arrangement schemes with time and space diversity are automatically generated, and space feasibility verification is efficiently completed through recursion backtracking and two-dimensional gridding means; optimizing and screening the arrangement scheme by using a multi-objective fitness function with the dock utilization rate and the production load balance degree as the core; according to the method, the dependence on artificial experience can be effectively reduced, the arrangement efficiency and scientificity are improved, and reasonable configuration of dock resources and balanced promotion of the construction rhythm are realized.

The invention discloses a task planning method and system, and the method comprises the steps: distributing a first processor for a to-be-planned target task from a first processor resource pool, so as to execute a task planning process for the target task, the task planning process comprises a task decomposition sub-process for decomposing the target task to obtain a sub-task and a calling tool sub-process for calling a tool to execute the sub-task; allocating a second processor for the sub-task from a second processor resource pool, so as to judge whether the sub-tasks in the task decomposition sub-process and the tool calling sub-process conform to expectation or not according to a result output by the task planning process, and updating the number of retry times corresponding to the task planning process according to a judgment result; and according to the updated number of retry times, re-executing the task planning process on the target task based on the allocated first processor so as to obtain a sub-task conforming to expectation.

The invention provides a flight path planning system, which comprises a planning management module, and the planning management module is in communication connection with a flight control system and a task system through the Ethernet. The planning management module is configured to receive planning input data of the task system, the planning input data comprises design constraints of a starting point, an end point, a threat area and an aircraft, and the design constraints comprise a maximum turning angle and a maximum climbing angle; based on design constraints, a search area is constrained in the path planning process, a horizontal search area is limited based on the maximum turning angle, and a vertical search area is limited based on the maximum climbing angle; in the searching process, the threat degree is calculated for the threat area, extension nodes are selected based on evaluation functions, and the evaluation functions comprise the node distance, the turning angle, the climbing angle and the threat degree; and generating a track from the starting point to the ending point and sending the track to a flight control system. According to the method, the safe and feasible flight path is quickly generated through constraint search areas and comprehensive evaluation.

The application discloses a UAV cluster system cooperative pursuit target path planning method and system, relates to the technical field of path planning, respectively takes the observation vector of each UAV in the UAV cluster system at the current time as input, determines the first action constant and the second action constant corresponding to each UAV by using a deep reinforcement learning network, and further obtains the observation vector of each UAV at the next time by calculating the heading angle of each UAV at the next time by using an artificial potential field method, and the above steps are cycled until the iteration termination condition is reached, so that the path planning of each UAV in the cooperative pursuit target process is completed. In the path planning process of the application, each UAV solves its own path separately, realizes effective decentralization, and considers the influence of surrounding obstacles in the path planning process, so that the decentralized path planning in a complex environment is realized.

The invention provides a port and wharf capacity planning method and system based on full-link intelligent scheduling, and the method and system construct a full-link collaborative double-layer planning model, and achieve the purpose of combining simulation modeling with intelligent decision. The model adopts a double-layer structure, and the upper layer adopts a multi-target intelligent optimization algorithm and is used for calculating investment cost, throughput and resource utilization rate. And the lower layer generates an optimal scheduling scheme based on dynamic constraint planning. And global decision optimization is realized through bidirectional data interaction between the upper layer and the lower layer. The method has the advantages that simulation modeling and intelligent decision making are combined, and the scientific preciseness, the economic efficiency and the adaptability of the planning process are remarkably improved. According to the method, the challenges of demand uncertainty, large peak-valley demand difference, strong resource relevance and system complexity faced by a traditional planning method are solved. The method can effectively deal with the operation characteristic of coexistence of the wharf operation peak value and normal operation of the oil logistics support base in the middle sea.

This invention provides a method for dynamic urban renewal based on deep reinforcement learning, relating to the field of urban renewal. The method includes: step S1, data acquisition; step S2, state prediction; step S3, hierarchical decision-making; step S4, execution feedback; and step S5, iterative optimization. Hierarchical decision-making, based on the urban state data in step S1 and the predicted state in step S2, implements hierarchical update schemes for macro-level, meso-level, and micro-level intelligent agents. This method transforms urban renewal from a one-time static planning process to dynamic adaptive decision-making that evolves with the urban system, thereby achieving dynamic adaptation of infrastructure and public services and avoiding negative impacts such as environmental damage, facility idleness, resource waste, and increased costs caused by mismatch.

The application belongs to the technical field of heavy load AGV, and discloses a heavy load AGV path planning method, which comprises the following steps: a simulation environment map of a heavy load AGV driving environment is constructed; in the simulation environment map, the AGV path planning process is sequentially divided into a first stage and a second stage based on an A* algorithm, and different comprehensive cost cost functions are used for path planning in the first stage and the second stage respectively. The heavy load AGV path planning method provided by the application improves the search speed of the planning result by improving the comprehensive cost cost function of the A* algorithm in stages, under the premise of ensuring the shortest path.

This invention belongs to the field of embodied intelligence and relates to an embodied task planning method and apparatus based on capability decomposition. The method includes: implementing a scheduler and multiple capabilities using a visual language model; the scheduler receiving task instructions and, based on these instructions, invoking multiple capabilities to perform embodied task planning, generating an atomic action sequence; and completing the task by executing the atomic action sequence and interacting with the environment. The multiple capabilities include exploration guidance capabilities, object localization capabilities, scene description capabilities, action decoding capabilities, and experience summarization capabilities. This invention effectively utilizes the basic capabilities of the visual language model to simplify the overall planning process, resulting in a more controllable and transparent reasoning process. This invention employs a multi-stage training strategy to fine-tune the visual language model, gradually improving the model's performance on various tasks and its generalization ability to new scenes.