161 results about "Optimal route" patented technology

The invention discloses a satellite-based routing decision making method and device and a storage medium. The method comprises the following steps: determining a plurality of reference curves in each first sampling period; determining a first distribution curve in the current time period, and broadcasting the reference curve of the current time period, the first distribution curve and the channel capacity of each area in the current time period to each satellite; determining a reference curve of the next time period, calculating a deformation relation between the reference curve of the second sampling time period and the reference curve of the third sampling time period, and performing deformation processing on the first distribution curve to obtain a plurality of second distribution curves of the next time period; predicting the satellite congestion degree of each region in the next time period according to the channel capacity of each region in the current time period on the basis of the plurality of second distribution curves; and based on each region, constructing a plurality of corresponding routing paths, and determining an optimal routing path in the plurality of routing paths by using a genetic algorithm. Therefore, the technical effect of reliably transmitting data is achieved.

The invention relates to an edge computing network-oriented micro-service and distributed database collaborative deployment system. The system comprises a database copy number dynamic optimization unit which obtains a dynamic optimization strategy of the copy number of a database based on a queuing gradient projection elastic scaling algorithm; a deployment strategy dynamic adjustment unit calculates end-to-end time delay based on the micro-service routing path and the database routing path; calculating a data inconsistency measurement index based on the number of each copy of the database; dynamically adjusting the deployment strategy based on the resource constraint between the end-to-end time delay and the data inconsistency measurement index and the dynamic optimization strategy of the number of copies of the database; the deployment strategy comprises micro-service instance deployment, database copy deployment and optimal routing path selection; according to the MEC scene-oriented distributed database design and fine-grained collaborative deployment optimization method, a message queue, a queuing theory and a Canal database incremental updating mechanism are integrated, and the micro-service application performance and the data query efficiency / reliability are improved.

The invention relates to the field of modern intelligent manufacturing and automation, and discloses a method for planning a path of an intelligent robot with a body based on visual inspection, which comprises the following steps: acquiring real-time image data, preprocessing and extracting position coordinates of an obstacle, and generating an obstacle distribution diagram; an A star algorithm is adopted to generate a preliminary optimal route sequence, and map information is updated; uncertain interference in the path is judged, and a path alternative set is generated through coordinate calibration; a time-varying parameter and a security constraint optimization path strategy are integrated through adaptive path optimization; key node coordinates are extracted and are fused with obstacle boundary identification to obtain a path execution sequence; real-time performance is checked, if calculation is overtime, a rollback mechanism is triggered, and an initial path is loaded and fused with real-time obstacle information to generate a final feasible route; a control instruction sequence is generated according to the final route and transmitted to the robot for execution. According to the method, efficient and adaptive path planning in a dynamic environment can be realized, and the real-time response capability and task execution reliability of the robot are improved.

The invention discloses a multi-constraint emergency material vehicle path optimization method and system, and belongs to the technical field of vehicle path planning. Comprising the following steps: acquiring input data from a data source, and constructing a multi-objective optimization model containing an objective function and constraint conditions based on the input data; based on the input data and the constructed multi-objective optimization model, generating an initial path scheme meeting all constraint conditions by adopting a heuristic algorithm combining nearest distance distribution and an earliest time window priority rule; and constructing a hierarchical collaborative optimization architecture consisting of an ALNS execution layer and a PPO decision layer, carrying out iterative optimization by taking the initial path scheme as a starting point, terminating the iterative optimization when a preset termination condition is met, and finally outputting an optimal path scheme. Compared with the prior art, the method has the beneficial effects that the key indexes are collaboratively optimized through the multi-objective optimization function, and the global solution quality and the scheduling precision are remarkably improved.

The invention discloses a large transport intelligent line selection implementation method fusing a graph neural network and a large language model, and the method comprises the following steps: S1, constructing multi-source features to a unified high-dimensional vector space according to large transport historical data and real-time environment data; s2, constructing a structured prompt template through multi-modal input; s3, based on the structured prompt template, generating a candidate route set in combination with a large language model; s4, dynamically optimizing the candidate route set through a reinforcement learning framework, and outputting an optimal route. Compared with the prior art, the method has the advantages that intelligent generation and dynamic decision making of a large transportation route are realized through multi-modal feature fusion, graph structure semantic compression and large model reasoning optimization, and the transportation reliability, safety and economical efficiency can be remarkably improved; traffic accidents can be responded in real time to realize route adjustment, routes are dynamically optimized to reduce passage cost, planning quality is continuously improved through historical case learning, and safe and punctual delivery of overrun goods is guaranteed.

In large domes and stadiums, this system integrates advanced information systems, user interfaces, and real-time data to ensure that visitors are properly guided to their destinations (seats, restaurants, shops, etc.), can understand congestion levels, receive information on products and events tailored to their individual needs, and, in the face of the increasing adoption of unmanned stores, enable efficient inventory management and payment processing. [Solution] A system including a digital display device and means for the user to input a desired destination; a central control unit and means for receiving destination information from the digital display device and calculating the optimal route; means for providing the user with optimal route guidance using a geographic information system including real-time congestion information; and means for communication with the central control unit.

This invention discloses an elevator bearing safety early warning method, device, and medium based on the Internet of Things (IoT), relating to the field of control testing and monitoring technology. The method includes: acquiring raw analog signals and preprocessing them to generate synchronous data frames; decomposing fault impact sequences from the synchronous data frames and obtaining a bearing safety status index through weighted D-S evidence, while simultaneously matching a pre-diagnostic control logic library to generate a pre-diagnostic confidence identifier; based on the pre-diagnostic confidence identifier and the bearing safety status index, obtaining a dynamic health baseline through sliding retrieval and elastic tracking compensation, and dynamically extrapolating the control envelope through a stochastic control boundary evolution algorithm to generate a dynamic safety threshold; comparing the bearing safety status index with the dynamic safety threshold, evaluating link quality, and selecting a candidate route set; and obtaining the optimal route through a shortest delay tree to form an encrypted alarm stream. This invention achieves accurate generation of the dynamic safety threshold.

The application discloses an AGV optimal path automatic memory storage scheduling method and system, which comprises the following steps: receiving task information; separately threading real-time cyclically reading the task information; selecting an AGV vehicle meeting a current task; matching a path planning from a site where a current vehicle is located to a task destination site in an optimal route cache set, if the path planning exists, directly selecting an optimal planning, if the path planning does not exist, re-planning an optimal path according to a path planning method and storing the optimal path into an optimal cache for next time matching and use; converting the optimal planning into a task execution instruction; and sending the task execution instruction to the AGV through a TCP protocol.

The system according to this embodiment aims to automate and efficiently perform optical communication route design. [Solution] The system according to the embodiment comprises a reception unit, a design unit, an evaluation unit, and a provision unit. The reception unit inputs information between connection points. The design unit designs the optimal route based on the information input by the reception unit. The evaluation unit evaluates the route designed by the design unit. The provision unit provides the route information evaluated by the evaluation unit.

The invention discloses an ESB intelligent message routing optimization method based on reinforcement learning, and the method comprises the steps: deploying a Kafka ESB node, registering node information, and carrying out the heartbeat synchronization maintenance of a node state; the node registers an HTTP service, updates the state change, and synchronizes the service state between cities; summarizing node, service, message and dependency information, and constructing a four-dimensional routing state tensor; receiving a service request, generating a unique identifier, and executing state recombination and dependency recoding; inputting the comprehensive evaluation into a decision maker, and selecting an optimal routing path by utilizing MuZero prediction; and after the service is executed, analyzing the feedback factor, generating a feedback vector, and updating a routing enhancement strategy parameter. According to the method, intelligent optimization and continuous adaptive adjustment of ESB message routing in a cross-city asynchronous environment are realized by constructing a four-dimensional routing state tensor and a reinforcement learning decision-making mechanism based on MuZero.

The application discloses a multi-four-rotor unmanned aerial vehicle gathering type task path planning method based on reinforcement learning, first constructs a multi-four-rotor unmanned aerial vehicle Gym environment based on PyBullet, abstracts a state space and an action space of the four-rotor unmanned aerial vehicle, sets a reward function mechanism, then uses an improved deep reinforcement learning algorithm to make path planning decisions, finally trains the improved deep reinforcement learning network, controls the four-rotor unmanned aerial vehicle through output action information, and makes each four-rotor unmanned aerial vehicle successfully reach a specified target task in the shortest time. The method uses N-step returns in the TD3 algorithm, obtains more accurate return estimates, faster learning speed and better generalization performance, uses priority experience replay to reduce sampling bias, reduces model bias caused by uneven sampling, improves algorithm stability, makes the TD3 algorithm more suitable for continuous multi-dimensional decision problems, and can plan an optimal route in the shortest time under the condition that real-time performance and accuracy are reached.

The present application relates to the technical field of communications, and discloses a method for a device to connect to a network, and a device, a system, and a readable storage medium, which enable a device in a distributed routing system to maintain a high-quality and high-stability network connection. In the present solution, a primary router in the distributed routing system can comprehensively analyze and compare signal indicators of wireless signals received from a device by routing devices, determine an optimal routing device from among the routing devices, and establish a connection between the optimal routing device and the device, so that the device can maintain a connection with the optimal routing device in the distributed routing system, thereby maintaining a high-quality and high-stability network connection.

A system is provided.SOLUTION: A system comprising: means for receiving current location information and destination information of a user; means for instantaneously generating an optimal route from the current location information to the destination information using a generative AI model; and means for transmitting the generated optimal route information to a user device for display on the user device.SELECTED DRAWING: Figure 1

The invention discloses an online obstacle avoidance route planning method based on random scattering, and belongs to the field of unmanned flight route planning, and the method specifically comprises the steps: firstly, obtaining initial position coordinates of a starting point and a target point in a to-be-measured obstacle region, and converting the initial position coordinates into a Mercator plane coordinate system; then, generating a minimum rectangle or square for the obstacle area; and constructing a key point set Sets by adopting a Gaussian bias random point scattering strategy. Thirdly, calculating a comprehensive evaluation function of each key point, and selecting the key point corresponding to the minimum value as an optimal waypoint at the next moment; and judging the feasibility of the minimum value of the comprehensive evaluation, outputting the waypoint to a flight control system when the minimum value of the comprehensive evaluation is feasible, and starting real-time re-planning of the next period as a new starting point. Otherwise, falling into local deadlock or no solution, returning to increase the standard deviation in the Gaussian bias random point scattering strategy, and forcing the search range to diffuse to the region deviating from the target until a feasible solution is found. The task can be completed safely and efficiently.

The invention provides a transmission network route generation method and device, equipment, a medium and a program product, and relates to the technical field of communication engineering, and the method comprises the steps: determining resource objects of a plurality of hierarchies, and distributing a corresponding unique identifier for each resource object; according to the unique identifier, establishing a hierarchical topological association relationship between the hierarchical resource objects to obtain a hierarchical resource model; adding corresponding attribute information to each resource object through a hierarchical resource model; determining a corresponding macroscopic routing direction according to the attribute information and the hierarchical resource model; determining a candidate routing scheme set according to the macroscopic routing direction and the hierarchical topology association relationship; screening the candidate routing scheme set according to the plurality of target dimensions to obtain a screened optimal routing scheme or a sorted candidate scheme list; wherein the target dimension comprises time delay, the number of nodes and routing preference; the method provided by the invention is used for realizing the technical effect of improving the generation efficiency and flexibility of the transmission network route.

Aspects provided herein provide methods, systems, and a non-transitory computer storage medium storing computer instructions for network aware optimal route selection for autonomous user equipment (UE) in a network. The method begins with identifying an initial route based on a mapping mechanism. An example is entering a start and ending point for a delivery using an autonomous UE. After an initial route is identified operator defined geospatial hex bins and base stations along the initial route are identified. Further identifying operations include identifying at least one flow quality of service (QoS) value that comprises a priority of at least one service and identifying at least one geospatial hex bin and associated node with a QoS value greater than an operator defined threshold. Those geospatial hex bins are then marked and excluded from the route of the autonomous UE and a revised route is transmitted to the autonomous UE.

The application discloses a kind of anonymous routing methods of double-layer satellite network for delay-sensitive service, it is applied to VLEO / LEO double-layer satellite network, this network is based on software-defined network SDN architecture implementation, including data plane, control plane and application plane;Data plane includes VLEO layer, VLEO / LEO cross layer and LEO layer;Application plane is deployed with the routing method of the application upper;The method comprises: constructing layered decoupling routing calculation framework, to divide routing decision into including LEO layer inner routing, VLEO / LEO cross layer routing and VLEO layer inner routing multilayer path selection;Using the collaborative computing capability of SDN controller and satellite node, multilayer path selection is reconfigured and weight disturbance in real time, generates optimal routing path.The application can effectively reduce end-to-end delay, balance network load, improve the real-time performance, robustness and security anonymity of double-layer satellite network.

The invention discloses an mrk image three-dimensional visualization and plotting method based on digital twinning, and relates to the technical field of GIS and three-dimensional visualization, by establishing a digital twinning body of an mrk image in a deduction system, the mrk image generated according to a combat scenario in the real world can be conveniently mapped to a virtual space, and the real-time performance of the mrk image is improved. Therefore, deduction simulation, optimal route planning, formation of combat scheme suggestions and conversion into mrk graphs can be carried out by utilizing marine environment information, real-time situation data and underwater sound field calculation, full interaction between virtuality and reality is realized, optimal decision is carried out by utilizing simulation deduction, and the real-time situation data and the underwater sound field calculation can be realized. The method overcomes the defects that an mrk graph is stiff and is difficult to formulate an optimization scheme in combination with complex conditions such as marine environment information and a friend or foe situation, and fully utilizes the capabilities of flexible trend distribution, real-time information access, marine environment information support and efficient dynamic optimization of a deduction system.

The invention discloses an unmanned sanitation vehicle fleet balanced scheduling method based on near-end strategy reinforcement learning, and the method comprises the steps: determining a cleaning task set of unmanned sanitation vehicles, and each task comprises the workload and the spatial position; establishing a mixed distance matrix based on the task point coordinates and the warehouse position, loading the node workload, and constructing a neighbor graph; establishing a path planning model based on the optimization target and the limiting condition; according to the number of the unmanned vehicles and the neighbor graph, generating an initial route combination by using an initialization algorithm, and finding an initial optimal route based on a route planning model; and constructing an intelligent agent based on the graph neural network, iteratively selecting a route and adjusting an operator and parameters by using an optimization algorithm, and iterating to a preset number of times to obtain an optimal path satisfying the path planning model. According to the invention, the path of the unmanned sanitation vehicle can be effectively arranged, so that the working efficiency is improved and the cost is reduced.

A single-point-of-failure search device as in one embodiment of this invention searches for a single point of failure in a network. The single-point-of-failure search device is equipped with a resource management unit, an optimal resource selection unit, and a single point of failure (SPOF) resource calculation unit. The resource management unit manages, for each of the layers of the network, construction properties including at least resource coordination overhead, a design period, a construction period, a lead time, a life cycle cost, and a cost value. In accordance with a search object given by designating a start point and an end point, the optimal resource selection unit optimizes a route between the start point and the end point on the basis of at least the cost value, and outputs an optimal route in the network. The SPOF resource calculation unit gives, to the optimal resource selection unit, a search object with which the cost value of paths constituting the optimal route has been set to a maximum value to search for a bypass route for the optimal route, and calculates a non-bypassable resource as being a single point of failure.

We provide the system. [Solution] A means for obtaining text information entered by the user, Means for obtaining information entered by users, A means for analyzing the acquired information and extracting relevant elements, A means for searching for appropriate guidance from information sources on the network based on the extracted elements, A means for presenting the searched information to the user, A means for analyzing the user's location information and providing optimal route information, A system that includes this.

To provide technology that enables the efficient operation of services such as receiving goods from users by sequentially determining the optimal route for a moving object, taking into account compliance restrictions imposed on the driver. [Solution] A base information acquisition unit 80 acquires base information for each of the multiple bases, including the location of the base and the amount of goods in and out per predetermined unit time; a warehouse information acquisition unit 81 acquires warehouse information for each of the multiple warehouses, including the location of the warehouse and the availability status per predetermined unit time; a driver information acquisition unit 85 acquires driver information, including predetermined compliance restrictions; and a route determination unit 82 determines a route for each of the one or more mobile units to travel, including a resting place for the driver, based on the base information for each of the multiple bases, the warehouse information for each of the multiple warehouses, and the driver information.

The invention provides a multi-rate network intelligent route planning method based on minimum media occupancy time, and belongs to the field of multi-rate networks and route planning. According to the method, firstly, an ant colony algorithm is adopted, the mobility of nodes is introduced, a stable and optimal MPR set is selected, and whole network topology information is obtained; then giving a network link weight based on media occupancy time; and finally, selecting an optimal route based on a simulated annealing algorithm of multi-agent optimization. According to the method, the traditional method of selecting the routing based on the minimum hop count is abandoned, the media occupation time is defined to comprehensively evaluate the network link weight, the time delay of the network is reduced, and the throughput of the network is increased; and secondly, routing is selected by adopting a simulated annealing algorithm based on multi-agent optimization, so that the optimization capacity is improved, the network dynamics is adapted, and the robustness of the network is enhanced.

A node device for forming a multi-hop network is provided. The node device is configured to discover two routing topologies: a normal routing topology for normal data transmission and a preferred topology for prioritized data transmission. The normal route is discovered for all data nodes in an IoT network, and the preferred route is discovered for only the preferred data nodes. The normal data route (D-route) is discovered using a distance-based route discovery protocol (RPL), and the preferred route (P-route) is optimally discovered for only the preferred data nodes to minimize route overlap, route transmission time, and route length. The node device includes a transceiver configured to transmit and receive normal data in a destination-oriented directed acyclic graph (DODAG)-based topology and transmit and receive priority data in the optimal routing topology; a memory configured to store a computer-executable program including a communication mode (CM), a multirate link count (MLC), a route overlap degree (DRO), neighbor node information, route transmission time, and route length; and a processor configured to execute the steps of the computer-executable program. The steps include finding a D route and finding a P route, where finding a P route includes finding a non-circular route, finding a minimum overlap route, finding a minimum transmission time route, and finding a minimum length route.

The invention discloses a ship route optimization method based on particle swarm optimization and geographic information, and particularly relates to the technical field of ship route optimizing.The method comprises the steps that firstly, multi-source geographic information of a target shipping area is collected and preprocessed, a voyage number operation standard data set is obtained, and a double-layer management and control constraint model is constructed; calculating a forward operation cost matrix and a backward operation cost matrix in advance by adopting a path search algorithm, carrying out iterative optimization and verification by introducing a particle swarm algorithm of an operation path traction item, and outputting a global optimal first waypoint sequence; performing smoothing processing on the global optimal first waypoint sequence by adopting a B spline interpolation method, performing secondary verification, and outputting a verified optimal route; according to the method, the targeted search boundary of the particle swarm is delimited by constructing the bidirectional feasible region, the operation path traction item is innovatively introduced into the speed updating formula, geographic information is fused in the whole process, and the problems of premature convergence and local optimum caused by lack of geographic guidance are solved.

The invention provides a graph neural network assisted big data transmission scheduling system. The graph neural network assisted big data transmission scheduling system comprises an online scheduling subsystem and an offline training subsystem, the online scheduling subsystem is configured to collect network state information in real time, and extract a spatial-temporal characteristic matrix including request characteristics, link characteristics and path characteristics; inputting the spatial-temporal characteristic matrix into a graph neural network model, and outputting storage and forwarding scheduling success rates of a plurality of alternative routes; arranging alternative routes in a descending order according to the scheduling success rate, selecting an optimal route in combination with a route quality estimation function, executing data transmission scheduling through a store-and-forward mechanism, and feeding back an actual scheduling result to the offline training subsystem; and the offline training subsystem is in communication connection with the online scheduling subsystem, and is configured to receive an actual scheduling result fed back by the online scheduling subsystem and a corresponding spatial-temporal characteristic matrix, train a graph neural network model based on a historical sample database, and update the graph neural network model regularly.

Embodiments of the present disclosure disclose a system for determining an optimal route. The system obtains an origin-destination (OD) matrix comprising historical traffic values for predefined time slots for each route and generates network graphs based on the OD matrix. Each of the network graphs corresponds to one of the predefined time slots, and each of the network graphs comprise nodes, and edges having corresponding weight values. The system determines desired routes from the one or more routes based on the weight values, determines travel frequency data for each of the desired routes at least in the predefined time slots based on the network graphs; and determines a modal route based on the desired routes and the travel frequency data. Each of the desired routes is associated with one of the network graphs.

Provide a system. 【Solution means】 Analyze the image of an individual's clothes obtained from a terminal, Means for estimating an individual's preference based on the image, Means for automatically generating a travel itinerary based on the preference, Means for reflecting an individual's constraints in the itinerary, Means for visually displaying the generated itinerary, Means for recommending items based on attributes within a commercial facility based on the image of clothes obtained from a terminal, Means for providing an optimal route using the location information within the commercial facility, A system including the above.