104 results about "Transport network" patented technology

The invention discloses a power-traffic network charging load prediction method and system, and a storage medium. The method comprises the following steps: constructing an electric vehicle basic model, a road network basic model, a charging station basic model and a power distribution network basic model; generating dynamic traffic flow data through a generative adversarial network based on the basic model and the historical traffic data; constructing a traffic travel demand matrix based on a start-end point analysis method, and simulating the whole process of charging decision, queuing waiting and charging service of the electric vehicle in the charging station by using a queuing theory algorithm in combination with the dynamic traffic flow data and the basic model; constructing a space-time diagram attention network model, taking charging demand simulation data, a road network basic model and a charging station basic model as input, obtaining a space-time coupling relationship between a traffic network state and a charging demand through a multi-head diagram attention mechanism, and predicting to obtain space-time distribution of an electric vehicle charging load in a certain period of time in the future. And accurate prediction of the time-space part of the charging load of the electric vehicle is realized.

Computer-implemented methods optimising routes in a transport network for a geographical region are disclosed. Methods comprise obtaining an analysis of the geographical region; generating probabilistic predictions, checking whether at least a subset of the generated probabilistic predictions have previously been solved by a trained machine learning model; based on at least a first subset of the generated probabilistic predictions having previously been solved, retrieving the trained machine learning model previously used to solve the at least a first subset of the generated probabilistic predictions and executing the trained machine learning model to determine a first plurality of suggested routes for the transport network; based on at least a second subset of the generated probabilistic predictions not having previously been solved, training a new machine learning model to solve the at least a second subset of generated probabilistic predictions to determine a second plurality of suggested routes for the transport network.

The invention relates to the technical field of composite cables for rail transit, and provides a flexible composite cable for rail transit and a preparation method thereof.The preparation method comprises the steps that a power transmission unit, a signal transmission unit and PBO fiber bundles are constructed into a three-dimensional transmission network framework which is in a hollow tube shape as a whole through three-dimensional weaving; a plurality of upgrading channel pipes are arranged on the inner side of the three-dimensional transmission network framework, and the outer side of the three-dimensional transmission network framework is sequentially coated with a shielding layer and an outer protection layer from inside to outside. According to the flexible composite cable for the rail transit and the preparation method of the flexible composite cable, power transmission and signal transmission can be integrated, meanwhile, the overall anti-pressure capability, flexibility and anti-torsion stability are improved, the integrity of electrical connection and optical paths is effectively protected, the cost and upgrading complexity of the whole life cycle are remarkably reduced, and the service life of the cable is prolonged. And flexibility is provided for long-term technical evolution of a rail transit system, and reliable electromagnetic interference protection capability is maintained.

Handling resets comprises communicating transport packets between a transport network and data processing circuitry, with at least a portion of the data processing circuitry operating in a given reset

A method for configuring a first autonomous system in a transit network is described. The method includes obtaining information according to which the traffic received by an ingress router of the first autonomous system is saturated, and determining a prefix of a destination subnet of a third autonomous system downstream of the first autonomous system. The method also includes extending the path associated with the prefix on at least one target router of the first autonomous system, the prefix and the at least one target router being determined by optimizing an objective function so that the path associated with the prefix must be extended for all the ingress routers of the first autonomous system which are geographically closer to the saturated router than the target router.

Transmitters, receivers, transceivers, transport networks, and methods of use are described herein, including a transmitter comprising a client-side input, transmitter circuitry, and antennas. The client-side input receives baseband signals having client data encoded therein. The transmitter circuitry receives the baseband signals from the client-side input and generates antenna feed signals based on the baseband signals. The antennas receive the antenna feed signals from the transmitter circuitry, generate radiated signals based on the antenna feed signals, and couple the radiated signals into hollow waveguides. The radiated signals are radiated electromagnetic waves configured for coherent detection and having one or more frequencies in a range between 300 Gigahertz (GHz) and 10 Terahertz (THz). The antennas include one of a helical antenna, a waveguide probe antenna, a tapered antenna, a patch antenna, and a slot antenna.

Aspects of the subject disclosure may include, for example, a device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of identifying a public land mobile network (PLMN) identifier associated with a communications network; determining a tracking area code (TAC) range of a plurality of cell sites in a radio access network (RAN) associated with the PLMN identifier; identifying transport network circuits of a transport network connecting the plurality of cell sites with a core network of the communications network; and displaying a user interface comprising a graphical representation of the core network, the transport network and the RAN. Other embodiments are disclosed.

Embodiments of present disclosure disclose internet protocol (IP) assignment and secure traffic for network elements deployed over untrusted transport network. In an embodiment, base station (101) transmits an Open Cloud (O-cloud) available registration request to an operator network system (103) through First Secure Tunnel (FST) (133) established between operator network system (103) and base station (101). The FST is terminated upon receiving network information related to each of plurality of O-cloud entities of O-cloud through FST from operator network system. Thereafter, base station (101) transmits second authentication request to operator network system for establishing Second Secure Tunnel (SST) (135) between operator network system and base station. Finally, base station establishes SST between operator network system and base station when network information is authenticated. The established SST allows bi-directional traffic related to each of plurality of O-cloud entities. The present disclosure helps in handling the traffic at the operator network system.

The application provides an optimization method, system and equipment for a public and railway combined transport delivery network under external set internal matching, and belongs to the technical field of logistics distribution network optimization. The method is aimed at the problem that the traditional optimization algorithm in the prior art is prone to local optimization and difficult to obtain a globally satisfactory solution, and uses a deep learning assisted genetic algorithm to solve a pre-constructed public and railway combined transport network model. The algorithm performs real-time sensing on the population evolution state through a deep Q network, dynamically and intelligently selects a genetic operation strategy, and combines an experience playback mechanism to perform self-training and parameter updating, and finally outputs an optimal two-stage public and railway combined transport hub site selection and network freight flow distribution scheme. The application uses the above optimization method, system and equipment for a public and railway combined transport delivery network under external set internal matching, effectively improves the global search capability and adaptive level of the algorithm, and can obtain a public and railway combined transport network optimization scheme which is lower in cost, better in layout, and stable and reliable.

Provided in the embodiments of the present application are a network anomaly analysis method, a transport network and a related device, which can collaboratively analyze anomaly events of cable layers, optical layers, electrical layers or service layers comprised in transport networks, thereby improving the efficiency of discovery of hidden risks of networks. The method comprises: a network management device receives an anomaly message from a target optical device; the network management device obtains an anomaly event of a first optical layer channel caused by the anomaly message, and the network management device obtains an anomaly event of a first electrical layer channel caused by the anomaly event of the first optical layer channel; and the network management device obtains an anomaly event of a target service caused by the anomaly event of the first electrical layer channel.

The invention relates to a computer-implemented method for managing and optimizing logistics operations using autonomous transport platforms, the method comprising the following steps: - constructing a representation of a transport network comprising paths between strategic points, the strategic points including transfer zones, - constructing a representation of the autonomous transport platforms, - iteratively planning to establish, for each logistics operation, a route and the autonomous transport platform that will execute the route, by carrying out the sub-steps: - assigning a platform, - determining possible routes being the paths between an initial position, transfer zones and a final position, by reducing a discrepancy between the schedules of the possible routes and the time constraints of the logistics operation, - determining, for each possible route, the energy consumed.- Select the route from the possible routes. Figure for the abbreviation: Figure 1,

A process, method, architecture, apparatus, system, apparatus, and computer program product for a network node may be configured to receive configuration information from a second network node, the configuration information indicating a set of rules for allocating differentiated service code point (DSCP) values; obtaining a first protocol data unit (PDU) associated with the first PDU set and a second PDU associated with the second PDU set, wherein the first PDU set and the second PDU set are associated with the same quality of service (QOS) flow; determining a first DSCP value and a second DSCP value, wherein the first DSCP value and the second DSCP value are different; and generating a first packet including the first PDU and the first DSCP value and a second packet including the second PDU and the second DSCP value.

The network system triggers registration of the start of a transport journey in response to a communication of a transport user device and a transport provider device with each other, performs a continuous coordinated proximity monitoring to verify the identity of a transport user and a transport provider vehicle, and triggers registration of the end of the transport journey through communication of the transport user device and the transport provider device with each other.

The application provides a kind of metropolitan area transport network adaptive protection path planning method and device.The method is executed on metropolitan area transport network, and metropolitan area transport network is composed of multiple nodes.Network topology information of metropolitan area transport network is stored as graph data, and the traffic load of each service flow in the next time period is predicted based on the pre-trained traffic prediction model and the obtained historical traffic information, and the residual capacity of each link in the next time period in the metropolitan area transport network, the available time slot type and the corresponding number are estimated.The traffic prediction model uses graph convolution network to perform multi-layer feature extraction on the structure of network topology graph, constructs load balancing constraint, minimization blocking rate constraint and minimization resource consumption constraint, and generates protection path and protection time slot allocation scheme for each service flow according to the residual capacity of each link in the next time period, the available time slot type and the corresponding number, to realize more efficient fault recovery and protection path selection.

Aspects of the subject disclosure may include, for example, receiving a service request relating to an mIoT application, identifying service delivery and feature requirements, resulting in identified requirements, obtaining first information from an AIC regarding resources in access network(s), second information from a TIC regarding resources in transport network(s), and third information from a CIC regarding resources in core network(s), selecting a first resource in the access network(s), a second resource in the transport network(s), a third resource in the core network(s), and at least one treatment function, generating an SRH that identifies the first, second, and third resources and the at least one treatment function, and causing the SRH to be provided to the AIC to facilitate embedding of the SRH into packets relating to the mIoT application, thereby enabling connectionless E2E service delivery for the mIoT application. Other embodiments are disclosed.

Apparatuses, systems, and techniques including APIs, subscription services, and controllers to enable one or more fifth generation new radio (5G-NR) networks to share information. For example, a processor comprising one or more circuits can perform an API or subscription service to cause a device in a radio access network (RAN) to share its analytic data with a device in a transport network, and said device in said transport network can use said analytic data to adjust its network settings to improve performance.

Provided are an apparatus and a method for computing a path for forwarding user data through the following steps: receiving a state measurement value or a state prediction value corresponding to the state measurement value of a state of a plurality of network resources within a mobile core network and a transport network; and computing the path for forwarding the user data, on the basis of either the state measurement value or the state prediction value, and topology of the mobile core network and topology of the transport network.

The application discloses a kind of building waste tracking methods based on graph neural network, constructs pre-processing building waste transport multi-source data;Building waste transport network weighted heterogeneous graph is constructed based on pre-processing building waste transport multi-source data;Generation and update GraphSAGE node embedding vector;The breakpoint event composed of interrupt position, occurrence time and state element is output;Fixed hop local subgraph is extracted on building waste transport network weighted heterogeneous graph;Get the priority of the set of detour candidate paths, and select the highest score of self-healing tracking path;Form the updated building waste transport path tracking expected path, combine the compliance risk information in GraphSAGE node embedding vector, mark potential illegal dumping risk node, and output building waste path tracking result.The application realizes detour path optimization and exclusion of high-risk path, so that path reconstruction is more in line with urban transportation scheduling and regulatory requirements.

Methods and devices for a mobile communication system are disclosed. According to an embodiment, there is provided a method in a mobile communication system comprising a radio access network, RAN, comprising a first RAN node and a second RAN node connected by a transport network comprising a first transport node and a second transport node, wherein the first RAN node is connected to the first transport node and the second RAN node is connected to the second transport node, the method comprising, by the first transport node: determining a status of the transport network connection between the first transport node and the second transport node; generating a message indicating the status of the transport network connection; and initiating transmission of the message to the first RAN node.

The application relates to a multimodal transport planning method and device, computer equipment, medium and computer program product. The method comprises the following steps: constructing a coal transport network topology graph according to nodes and transport edges in a coal transport network; the number of nodes and transport edges is multiple, and the transport edge is a transport path between nodes; obtaining node parameters of the nodes and transport parameters of the transport edges in the coal transport network; constructing a target optimization model based on the coal transport network topology graph, the node parameters, the transport parameters and a preset optimization target; determining the transport path, the transport mode corresponding to the transport path and the transport quantity of each type of coal based on the target optimization model. The method can plan a transport path, a transport mode corresponding to each transport path and a transport quantity of different types of coal that can meet the actual demand of a user under the premise of meeting the actual transport condition, so that the actual demand of the user can be met, and the overall transport efficiency is improved.

The invention specifically relates to a BIM-based hydraulic engineering design earthwork volume calculation method, and relates to the technical field of hydraulic engineering design, and the method comprises the steps: generating a cross-regional scheduling instruction through a high layer, and carrying out the coevolution process of intra-regional precise optimization and cost feedback iteration through a bottom layer until the overall total cost is converged, and obtaining an optimal cross-regional scheduling and intra-regional deployment scheme. According to the method, qualitative engineering constraints such as soil matching, construction time sequence and transport distance economy are converted into quantifiable transport network graph theory rules such as effective edge filtering, time sequence verification and flow limitation, and it is ensured that the measurement and calculation process strictly conforms to the actual construction logic; the risk that a deployment scheme is not feasible due to the fact that constraint consideration is not comprehensive in a traditional method is avoided from the source, and double improvement of measurement and calculation precision and construction adaptability is achieved.

The invention provides a train control system time series data enhancement method based on semantic guide diffusion. The method comprises the steps of periodically collecting data transmission network performance index data in a train operation process according to operation characteristics of an urban rail train control data transmission system, and constructing a time sequence data set; constructing a semantic guidance diffusion framework SG-DiffTS model, wherein the SG-DiffTS model comprises a semantic guidance network and a time sequence decomposition denoising reconstruction network; using the time sequence data set to train an SG-DiffTS model, and after the training is completed, obtaining a trained SG-DiffTS model; and performing enhancement processing on the real data transmission network performance index data in the actual operation process of the train control system by using the trained SG-DifITS model. According to the method, trend and periodic semantics in a time sequence are extracted and fused in an unsupervised mode by using a conditional denoising diffusion probability model, so that the key problem that the performance of a deep learning model is restricted due to data scarcity in a train control system is solved.

In one embodiment, a method herein comprises: determining, by a service mesh process, whether a problematic metric for an application is based on a transport network to a cloud infrastructure or is within the cloud infrastructure; delineating, in response to the problematic metric being within the cloud infrastructure, cloud infrastructure network contribution versus application microservice architecture contribution to the problematic metric; determining, in response to the application microservice architecture contribution being a primary contributor to the problematic metric as compared to the cloud infrastructure network contribution, whether the problematic metric is due to a software issue or a hardware issue of the cloud infrastructure, a high load issue with application microservices of the cloud infrastructure for the application, or else an issue with the application itself; and exporting a corresponding determination related to whether the problematic metric is due to the transport network, the cloud infrastructure, or the application itself.

The present disclosure relates to a method of a transport network node (13a) performing load balancing in a transport network (10) and a transport network node (13a) performing the method. On the one hand, a method of a transport network node (13a) performing load balancing in a transport network (10) is provided. The method comprises receiving (S101) a data traffic flow to be transmitted through the transport network (10) from a source radio access network (RAN) node (11a) to a destination RAN node (12a) connected with the transport network (10); identifying (S102) a plurality of data traffic sub-flows forming the data traffic flow from the source RAN node (11a) to the destination RAN node (12a); determining (S103) one or more routing paths via which the identified data traffic sub-flows can be transmitted to a next hop node (13b, 13g) in the transport network (10); and if there are multiple possible routing paths, transmitting (S104) the identified data traffic sub-flows in the data traffic flow via the determined different routing paths alternately to implement load balancing in the transport network (10).

Provided in the embodiments of the present application are a method for determining a transport network layer address of a base station, and an apparatus, which are applied to base stations. The method comprises: acquiring transport network layer addresses associated with a target ground area; and when the base station operates in the target ground area, determining a target transport network layer address associated with the target ground area as the transport network layer address of the base station. The present invention solves the problem of large network overheads caused by excessive signaling interaction in non-terrestrial networks.

The invention relates to the field of intelligent management, and discloses a horizontal transportation automatic management system for combined transportation, which comprises a data acquisition module, a knowledge graph construction module, a transportation planning module, a transportation monitoring module, a transportation deviation identification module and a transportation regulation and control module, the railway station position information, the waterway port attribute information, the transportation tool state information and the cargo feature information are gathered into initial data of the railway-iron combined transportation network; constructing a knowledge graph; performing constraint reasoning in the knowledge graph to obtain an initial transportation plan of the transportation demand; state data of the combined transportation network after the initial transportation plan is executed are monitored in real time; evaluating a current transportation state and a plan deviation of the railway-iron combined transportation network, and traversing key influence entities and relationships in the initial transportation plan; dynamically adjusting the initial transportation plan, and automatically scheduling the molten iron combined transportation network; according to the invention, the efficiency of automatic management of horizontal transportation for combined transportation of iron and water can be improved.

A method includes receiving, by a first device in a transport network, a first service requirement parameter and a second service requirement parameter. The first service requirement parameter is a service requirement parameter of a transmit end device. The second service requirement parameter is a service requirement parameter of a receive end device. The method further includes determining, by the first device, a first service transmission requirement between the transmit end device and the receive end device based on the first service requirement parameter and the second service requirement parameter.

The invention discloses a harbor group iron ore transportation network chain construction and toughness planning optimization method and system fused with intelligent decision, and relates to the technical field of harbor planing.The method comprises the steps that all harbors between the starting place and the destination of iron ore transportation are mapped into harbor nodes, channels between the harbor nodes are mapped into edges, and the edges are mapped into the harbor nodes; forming a plurality of transport network chains from the starting place to the destination; each transport network chain is divided into a core transport network chain or a standby transport network chain according to the whole-course transport time efficiency, the network chain disturbance incidence rate and the transport capacity utilization rate of each transport network chain, the toughness value of each standby transport network chain is calculated, and the core transport network chain is preferentially selected for iron ore transport; and when the core transport network chain is disturbed by the network chain, calculating a disturbance comprehensive quantized value of the network chain disturbance, judging whether the standby transport network chain is started or not, and if so, selecting the corresponding standby transport network chain according to the toughness value.

The invention relates to a collaborative scheduling method, system and device for a cross-layer IP and an optical network, and a medium. The method comprises the following steps of: atomizing and analyzing an I P layer resource of a data network and an optical layer resource of a transmission network into a network resource atomic power unit which can be independently scheduled; combining the service priority, the bandwidth utilization rate of the network resources, the average delay and the service type which are monitored in real time to perform multi-layer service model combination to generate a cross-layer collaborative arrangement strategy; and generating a cross-layer optimal service path through a comprehensive cost function in combination with data network path planning data, transmission network optical channel resources and service demand information, thereby realizing collaborative scheduling of end-to-end resources of the data network and the transmission network, and finishing cross-layer resource allocation and service end-to-end automatic opening. By adopting the method, the management barrier between the IP layer and the optical layer can be broken, the utilization efficiency of network resources and the agility of service deployment are effectively improved, and the requirements of high reliability and high efficiency of a modern communication network are met.

The application discloses a kind of transport path optimization method and device considering port cascading failure risk, belong to port logistics and transport network optimization technical field.For the problem that insufficient consideration is given to port systemic risk in existing transport path planning, and chain reaction is easily caused by single point failure, the application proposes a comprehensive evaluation and optimization mechanism, by constructing a weighted directed graph model to represent the port transport network, integrating the port carrying capacity, historical failure probability and multi-dimensional external risk factors, the quantitative calculation of port cascading failure risk is realized.On this basis, a multi-objective optimization function is designed, with the minimum time and cost product as the optimization goal, while constraining the lowest probability of full-path failure risk, and using gradient descent algorithm to solve the optimal transport path.By dynamically adjusting the transport volume distribution, effectively avoiding high-risk nodes, the network robustness and transport reliability are improved.The application method can be widely applied to international sea transport, container scheduling and other scenarios, significantly reducing transport cost and interruption risk, and enhancing the ability to respond to emergencies.