199 results about "Network deployment" patented technology

The invention discloses a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization method and a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization device. The method comprises the following steps: constructing a data-driven random environment model reflecting photovoltaic output, electricity price fluctuation and charging load uncertainty by adopting a mode of combining time sequence clustering and a non-homogeneous Markov chain based on historical operation data; modeling a scheduling and bidding problem of the optical storage and charging integrated station into a multi-stage Markov decision process model which comprises day-ahead decision and joint optimization of multiple intra-day rolling adjustment; a deep reinforcement learning algorithm is utilized to train the network, and a strategy regulation and control network which can adapt to various uncertain scenes and meet equipment physical constraints is obtained; and deploying the trained strategy regulation and control network in an energy management system to realize global coordinated scheduling and bidding of the optical storage and charging integrated station. According to the method, the economic benefit is remarkably improved, the robustness is greatly enhanced, the decision is globally coordinated and optimized, the real-time decision capability is strong, and the expandability and portability are good.

The invention discloses a micro-grid parallel-separation operation switching method, which relates to the technical field of micro-grids and comprises the following steps: S1, collecting real-time state data of a micro-grid, calculating system instability and generating a stability state label; s2, generating an ultra-short-term prediction result, and calculating an energy buffer potential well parameter set and a virtual inertia coefficient in combination with a stability label; s3, triggering a mode switching instruction based on the stability state label, executing the energy buffer potential well parameter set and the virtual inertia coefficient to control the output of the energy storage system, and completing grid-connected and off-grid mode switching; s4, the harmonic content of the power grid is collected, and a protection constant value and reactive power output are dynamically adjusted according to the instability degree of the system; and S5, constructing a system support framework by constructing a hierarchical communication network, deploying a redundancy mechanism and adopting a staged implementation strategy. And through real-time stability evaluation, virtual inertia adjustment and ultra-short-term prediction optimization, the stability, the electric energy quality and the adaptive capacity in the grid-connected and off-grid switching process of the micro-grid are improved, and high reliability and flexibility of the system are ensured.

The invention discloses a dam safety detection method and system based on multi-source detection data, and relates to the technical field of dam safety detection, and the method comprises the steps: cooperatively collecting dam multi-source data through multiple platforms and multiple sensors; the collected multi-source data are preprocessed; constructing a multi-scale teacher network, and performing high-precision feature learning and risk quantification by using labeled multi-source data; teacher network knowledge migration is carried out through a knowledge distillation technology, and a lightweight student network is trained in combination with cross-domain pseudo data; and deploying the trained lightweight student network to an unmanned aerial vehicle or a robot dog, and carrying out dam safety real-time detection. Through integration of multi-source data acquisition, cross-domain mutual training of teachers and students, lightweight model deployment and automatic early warning decision, pain points of single data, difficulty in cross-domain adaptation, insufficient precision, deployment limitation and low efficiency are solved, the system can be directly deployed on an unmanned aerial vehicle or a robot dog, dependence on cloud computing power is not needed, data acquisition and analysis time delay is reduced, and the system can be widely applied to unmanned aerial vehicles or robot dogs. And emergency scenes are quickly responded.

The invention relates to the technical field of network deployment, in particular to a method and system for interactively configuring parameters through an LLM and a router gateway. The method comprises the following steps: arranging corresponding data of a natural language, a router command and a command execution result, and forming Quest / Answer training data required by a large model for providing a semantic mapping basis of a router configuration field for the large model; and training the general model through a large model fine tuning technology, so that the general model translates a router configuration related natural language into a specific router command and translates a command execution result into a natural language. According to the method, corresponding data pairs of a natural language, a router command and an execution result are constructed, and targeted fine adjustment is performed on a large model, so that the model has a bidirectional semantic translation capability in the field of router configuration, and the technical bottleneck that a traditional interaction scheme depends on independent interface development is broken through.

The invention discloses a leakage monitoring method based on an LNG fuel gas system. The leakage monitoring method comprises the steps that a self-adaptive frequency modulation continuous wave active acoustic scanning network is established; blind source separation is carried out on mixed signals in acoustic scanning network abnormal events by adopting self-adaptive kernel independent component analysis; constructing a leakage feature mapping model of the physical information neural network; leakage source accurate positioning and quantification based on acoustic tomography and Bayesian reasoning are carried out; multi-modal decision fusion is carried out based on the multi-dimensional data sources received in parallel, a false alarm suppression mechanism is set, and time continuity verification and space consistency verification are carried out; establishing a reinforcement learning model for autonomously optimizing a monitoring strategy according to environment change and system state, and realizing adaptive optimization; the strategy network after self-adaptive optimization is deployed at the cloud, actions are generated regularly according to the current state, the actions are issued to the regional gateway and the edge node for execution, and iterative updating is carried out, so that the monitoring accuracy in a complex environment is improved, and the false alarm rate is reduced.

The invention relates to the technical field of pulse neural network computing hardware, in particular to a neural network computing circuit of a pulse self-attention mechanism. According to the method, invalid or inefficient pulse events are dynamically screened through the hardware mask module, the operation number is remarkably reduced, and calculation path delay and logic resource occupation are reduced; meanwhile, in order to adapt to novel networks with binary architecture such as QKFormer, calculation and storage of a V matrix are eliminated, and storage resources and calculation resources are further reduced; in addition, the event coding module only generates active neuron events, and input sparsity is achieved. A configurable IF neuron model is adopted, exponential operation is avoided, hardware implementation is facilitated, and the method is suitable for binary network deployment. The modular architecture can support function extension, assembly line and parallel work; and the parallelism degree of the design can be determined according to the actual data pulse distribution rate. Event driving and mask pruning are combined, so that the overall computing resources of the circuit are greatly reduced, and the power consumption is reduced.

The invention discloses a dynamic trapping network deployment method and system fusing attack behavior preferences, and relates to the technical field of network security. The method comprises the following steps: modeling a network topology into a directed acyclic graph, and constructing a dynamic trapping network topology structure fused with attack behavior preference based on attacker behavior preference analysis in combination with situation awareness; modeling an attack and defense confrontation process as a Markov multi-stage dynamic game process, and solving Nash equilibrium to obtain an optimal strategy of each stage; the behavior preference of an attacker is updated in real time by using Bayesian learning and a sliding window mechanism, and the adaptability of a dynamic trapping network to attack and defense situations is enhanced. According to the method, the problems of configuration stiffness and poor attack and defense situation change adaptability in dynamic trap network deployment are solved, the active defense capability aiming at attacker behaviors can be improved, and an effective solution is provided for dynamic deployment of a trap network in a dynamic network environment.

The invention relates to a network discovery method, a first device, a second device, a chip, a computer readable storage medium, a computer program product, a computer program and a communication system. The network discovery method comprises the following steps: a first device sends a discovery request on a first channel; wherein the discovery request is used for indicating or requesting a second device on the first channel to send discovery request reply information, and the discovery request reply information comprises network deployment information. According to the embodiment of the invention, energy consumed by network discovery can be saved.

The application provides a low-altitude airborne terminal heterogeneous network vertical handover method and system, the method comprises the following steps: constructing and dynamically updating a three-dimensional network coverage information library; predicting the future route of the airborne terminal based on its real-time motion state, and obtaining a candidate network set from the three-dimensional network coverage information library according to the prediction result; generating a handover decision weight for each network in the candidate network set based on a preset evaluation model; determining whether to trigger vertical handover through fuzzy logic decision based on the handover decision weight, the current network state and the operating parameters of the airborne terminal; if the vertical handover is triggered, performing a vertical handover operation based on the candidate network set and the handover decision weight. The application is based on the pre-collected network deployment information, combined with the actual flight information for vertical handover, the switching execution logic is simple and efficient, which can effectively avoid the communication interruption problem caused by switching failure or frequent switching, and significantly reduce the power consumption in the communication process.

The present application relates to the technical field of fully-mechanized coal mining, and particularly relates to a multi-working-face-based fully-mechanized coal mining data analysis method and apparatus, and an engineering machine. The multi-working-face-based fully-mechanized coal mining data analysis method comprises: performing unified network deployment on devices on a plurality of working faces; performing data acquisition on the devices that have undergone the unified network deployment; performing selective reporting on the acquired data; and analyzing the reported data to obtain a data analysis result, the data analysis result comprising process model parameters associated with the working faces and / or automation rates associated with the working faces. The present application can at least improve the efficiency of device management, device maintenance and data analysis.

A communication method and a communication apparatus, which are used for implementing communication between a terminal and a core network by means of a unified non-3GPP access gateway, thereby reducing the complexity of network deployment. The method comprises: receiving a first message from a terminal, the first message being used for requesting authentication, connection establishment or connection release, and the first message being an internet protocol security (IPSec) message, or the first message being a quick user datagram protocol internet connection (QUIC) protocol message; and sending a second message to a control plane network element, the second message being a non-access stratum (NAS) message determined on the basis of the first message.

The application discloses a hexagon-based electromagnetic spectrum monitoring network deployment method, which comprises the following steps: constructing a minimum circumscribed rectangle of an electromagnetic spectrum coverage task area, establishing a plane rectangular coordinate system with any two adjacent sides of the minimum circumscribed rectangle as an x-axis and a y-axis; taking a center point of a regular hexagon as a center point of the regular hexagon, taking a side length of the regular hexagon as the side length of the regular hexagon, and making the x-axis coincide with a horizontal symmetry axis of the regular hexagon to construct a first regular hexagon; translating the first regular hexagon to the y-axis direction to obtain a second regular hexagon; translating the first regular hexagon to the x-axis direction and then to the y-axis direction to obtain a third regular hexagon, and the process is repeated until the regular hexagon grid covers the minimum circumscribed rectangle and the number of the regular hexagons is the least; and taking a sensing radius of an electromagnetic spectrum monitoring device as the sensing radius of the electromagnetic spectrum monitoring device. The application can effectively process and solve the task area boundary coverage problem, and is easy to plan, design and solve the number of the electromagnetic spectrum monitoring devices in the task area.

The invention belongs to the technical field of wireless communication, and particularly relates to a post-disaster wireless communication network resource allocation method. The method comprises the following steps: arranging a corresponding strategy network for each agent, training each strategy network by adopting a multi-agent reinforcement learning model comprising each strategy network to obtain an optimal network parameter of each strategy network, and deploying each strategy network configured with the optimal network parameter to the corresponding agent. Therefore, resource allocation in the network is guided; according to the method, algorithm convergence is accelerated, single-step decision delay is reduced, the network throughput is finally improved, and real-time and reliable service quality guarantee is provided for users.

A topology-reprogrammable test environment is provided that can support the needs of CI / CD / CV in the field. The system disclosed provides a highly scalable network architecture to simplify the implementation of network slicing, TaaS and network CI / CD, and solves problems related to the complexity of cloud-native network (CNN) deployments. A Network Cell (NC), comprises or consists of a Containerized Network Function (CNF), a Containerized Digital Twin (CDT), and a Containerized Test Agent (CTA). The CDT has at least two personalities, e.g., an emulator of the CNF in the same NC or a nodal of the CNF. The choice of personality of the CDT is controlled by the CTA of the NC. A number of NCs use a 3D IP address to interconnect and form a new kind of CNN over the infrastructure of VRs.

The present application discloses a method and an apparatus used in a node for Internet of Things communication in wireless communications. A first node sends a first wireless signal in a first time domain resource set. The first wireless signal comprises paging-related information. Recipients of the first wireless signal comprise an Internet of Things device. The time domain position of the first time domain resource set depends on whether the Internet of Things device is in a connected state. The Internet of Things device being in a connected state comprises at least one of: the Internet of Things device being configured with an ID by the first node or the network side; the Internet of Things device being authorized by the first node or the network side; the Internet of Things device having communicated with the first node or the network side within a first time window, the first time window being predefined or configured; or the Internet of Things device having registered with the first node or the network side. The present application achieves precise control of paging occasions, avoiding communication interference while enabling flexible network deployment.

The application discloses a CTC system localization hardware performance monitoring data visualization implementation method, solves the problems of poor adaptability of existing general monitoring schemes to localization hardware and railway business scenes, disconnection of data and business, weak visualization analysis and difficult special network deployment. The method ensures the improvement of data accuracy through automatic matching and multi-dimensional verification of hardware types, differentiated packet loss completion and business correlation abnormal value filtering; constructs a device-line-business three-dimensional layered model, combines railway operation diagrams for differentiated down-sampling and weighted statistics, and automatically associates business event labels to realize deep binding of performance data and business logic; through multi-index linkage visualization, pixel density detection intelligent labeling and multi-dimensional interaction filtering, the performance bottleneck positioning efficiency is improved; through three-level dependency list management, resource path mapping and static link encapsulation, an executable file that can completely run offline is generated, and the stable operation rate of the localization terminal is ensured.

The invention discloses a method and a system for deploying a mobile communication network, and relates to the technical field of mobile communication network deployment. The method comprises the following steps: carrying out network topology design according to user requirements; planning an optimal flight scheme of the unmanned aerial vehicle through a preset algorithm based on the designed network topology; the unmanned aerial vehicle carries an optical fiber and flies according to the optimal flight scheme, and construction of an optical fiber link is completed; and after the optical fiber link is used, recycling the optical fiber. By adopting the method, the deployment efficiency can be improved while the communication reliability is ensured.

The application provides a network configuration method and device, electronic equipment and storage medium. The method comprises the following steps: obtaining a target configuration file, the target configuration file comprising a configuration item and a configuration parameter matched with the configuration item, the target configuration file being used to instruct a target controller to perform a configuration operation on a target area in a Kubernetes cluster; sending the target configuration file to a pre-configured target controller, the target controller being used to perform network configuration on the Kubernetes cluster, the Kubernetes cluster comprising at least one target area, the target area comprising a route reflector (RR) node, a non-RR node and a switch associated with the RR node; and controlling the target controller to perform network configuration on a target parameter of the target area in the Kubernetes cluster based on the target configuration file. Through the above characteristics, the network deployment effect of the Kubernetes cluster can be improved.

This invention relates to the field of information and communication technology, and provides a satellite ground base station and its multi-operator sharing method. The method includes: the satellite ground base station supporting the establishment of NG links with multiple core networks; the satellite ground base station supporting the broadcast of public terrestrial mobile networks supported by multiple core networks; the satellite ground base station supporting the configuration of air interface resource ratios for multiple operators; and the satellite ground base station allocating air interface time and frequency resources according to the air interface resource ratios of each operator. In satellite communication systems, through the method of allocating air interface resources according to operators using the satellite ground base station of this invention, satellite terminals of different operators can access the same satellite ground base station, sharing the satellite ground base station hardware and air interface time and frequency resources, meeting the needs of independent operation of different services, and reducing network deployment and operation costs.

A well network deployment method for increasing the storage capacity of water-flooded high-permeability gas storage facilities, belonging to the field of oil reservoir gas storage construction technology, includes the following steps: S1, employing oil and gas reservoir fine description technology; S2, employing oil and gas reservoir engineering technology; S3, employing gas storage dynamic analysis technology; S4, establishing a comprehensive geological model, and combining steps S2 and S3 to clarify the direction of seepage dominance and delineate seepage zones in oil and gas areas. This invention, under conditions of high well network control and severe water intrusion and gas channeling, can significantly increase the storage capacity of water-flooded areas, solve the common problem of uneven injection-production displacement in sandstone gas storage facilities, and alleviate the contradiction of large differences in displacement effects between favorable and unfavorable areas during cyclic injection-production. This invention can be applied to the expansion of gas storage facilities that have been renovated due to significant seepage dominance or strong planar heterogeneity.

A satellite space target cooperative observation distributed planning method based on multi-agent reinforcement learning, comprising: constructing an on-board Actor network and a ground centralized Critic network to form a centralized training and distributed execution architecture; designing a structured mixed space action, training the Actor-Critic network through a large number of ground simulations and using an improved MAHPPO algorithm and a curriculum learning technique; deploying the trained Actor network on each satellite of the constellation executing the cooperative observation task to realize distributed execution; after uploading the list of space targets to be observed to each satellite through satellite-ground communication, each satellite does not need to communicate with other satellites, each satellite executes the observation target of each time slice decided by the on-board Actor network, and controls the satellite to implement the observation task, thereby realizing the space target cooperative observation task. The present application enables each satellite to complete the cooperative observation without communication during the on-orbit execution, and can be extended to large-scale constellation applications.

The application relates to the technical field of Internet of Things, in particular to a network deployment method and system of a low-power-consumption device. The method comprises the following steps: S1, a master station acquires all channels of a network, wherein a first channel is a stay channel of the low-power-consumption device in an off-network state, and a second channel where a gateway is located is preset; S2, the gateway sends an activation network entry frame in the first channel, and then switches back to the second channel; in step S2, the low-power-consumption device periodically performs CAD detection, if the activation network entry frame is received, the low-power-consumption device switches to the second channel where the gateway is located and sends active uplink data to the gateway, if the activation network entry frame is not received, the low-power-consumption device stays in the first channel, wherein the sending time length of the activation network entry frame is not less than the detection period of the low-power-consumption device, and the gateway processes the active uplink data and gives a response. Through the CAD detection technology of LoRa and the design of the network entry mechanism, the power consumption of the low-power-consumption device in operation is reduced, and through the adjustment of the detection period, real-time communication is realized.

A method to perform beam management (BM) and / or synchronization (Sync) using primary synchronization signal (PSS) when pilot contamination is low to improve system performance is proposed. A UE first determines pilot contamination level on PSS of a synchronization signal block (SSB), depending on different network deployment scenarios. The UE then adaptively perform BM or Sync, by dynamically adjusting to the pilot contamination level on PSS. If the pilot contamination level is high, then the UE follows a 3-symbol mode, e.g., uses only PBCH0, SSS, and PBCH2 symbols for performing BM or Sync. Otherwise, if the pilot contamination level is low, then the UE follows a 4-symbol mode, e.g., uses PSS as an extra symbol for BM or Sync to improve system performance.

The invention discloses a base station deployment method for mine space constraints and related products, which can be applied to the technical field of mine communication network deployment, and the method comprises the following steps: constructing M to-be-selected particles; wherein each particle to be selected comprises three-dimensional position information and antenna angle information of N base stations. And determining a three-dimensional coverage rate of each to-be-selected particle for the to-be-deployed mine, and taking the to-be-selected particle with the highest three-dimensional coverage rate as a first target particle. And iteratively adjusting the first target particle based on a preset updating strategy, and determining a three-dimensional coverage rate of the first target particle to the to-be-deployed mine after each iteration adjustment. And outputting the optimal deployment scheme when the obtained three-dimensional coverage rate meets a preset iteration convergence difference value through continuous K times of iteration adjustment. Therefore, the three-dimensional space information of the mine is taken as a constraint, the three-dimensional position and the antenna angle of the base station are jointly optimized by combining the particle swarm optimization algorithm, and the three-dimensional space coverage rate of deployment of the base station in the mine environment is improved.

The present application relates to the technical field of communications, and in particular, to a data transmission method and apparatus, with the aim of ensuring data transmission continuity, reducing wasted resources caused by disaster recovery backups, and reducing network deployment challenges and costs. The method, which may be executed by an orchestration apparatus, comprises: receiving interruption information, wherein the interruption information comprises first path indicating information and an identifier of a faulty node, and the first path indicating information is used for indicating a first data link for data transmission; sending second path indicating information and second hop count indicating information according to the interruption information, the second path indicating information being used for indicating a second data link, and the second hop count indicating information being used for indicating a remaining hop count corresponding to data transmission on the second data link, wherein the second data link does not comprise a faulty node, or a data exchange node corresponding to the second data link is not a faulty node.

The invention relates to a multi-subnet network construction method and device of a train Ethernet backbone network and a storage medium. The method comprises the following steps: acquiring a first topological parameter of a first backbone node, and acquiring a second topological parameter of a second backbone node; determining a subnet number of each subnet under the first backbone node and the second backbone node according to the second topological parameter and the first topological parameter; setting a network address for each subnet according to the subnet number; according to the network address, constructing a unicast routing forwarding table and a multicast routing forwarding table for each backbone node; and controlling the backbone node to forward the message according to the unicast routing forwarding table or the multicast routing forwarding table. By means of the method, isolation of different network data is achieved, a set of backbone network equipment does not need to be independently configured for each kind of network data, the different network data are distinguished, meanwhile, the number of required train network equipment is reduced, and the multi-subnet deployment cost of the train Ethernet backbone network is reduced.

An apparatus comprises at least one processing device configured to identify an extended processing device and onboard the extended processing device to an edge infrastructure management platform, wherein the extended processing device is added as a component of a legacy device, and integrate the legacy device into the edge infrastructure management platform through one or more operations performed by the extended processing device.

The invention relates to the technical field of laser synthesis, and discloses a cross-environment self-adaptive laser coherent synthesis method, equipment and a medium. The method comprises the following steps: constructing environment distribution containing various parameter combinations, and randomly sampling an environment from the environment distribution at the beginning of each training period; training an adaptive strategy network based on a sampled environment; deploying the trained adaptive strategy network to a laser coherent combination system, and fixing network parameters of the adaptive strategy network; and updating the internal memory state through initial interaction between the self-adaptive strategy network and the current environment, and outputting a phase correction instruction to perform phase control of laser synthesis. According to the method, the environment overfitting problem existing in laser coherent synthesis in traditional reinforcement learning is solved, rapid self-adaption can be achieved only through a small amount of initial interaction, the debugging cost of system deployment and scene switching is greatly reduced, different noise, turbulence intensity and laser array scales can be adapted, and the stable and efficient phase locking control effect is always kept.

The invention relates to the technical field of computer science and information engineering, in particular to a mobile edge computing task unloading optimization method and device, and the method comprises the following steps: S1, carrying out environment modeling: constructing a graph enhancement state space, constructing an action space, and setting a causal demand award function; s2, constructing a neural network structure, wherein the neural network structure comprises a strategy network and a Q network; s3, performing algorithm training: firstly configuring environment parameters and initializing network parameters, secondly performing environment interaction and experience storage, and finally performing network updating and loop iteration; and S4, after training in the S3 is completed, deploying the final strategy network into the dynamic mobile edge computing system for real-time task unloading decision, and embedding vectors for the graph.

The invention discloses a self-adaptive image coding method based on U-shaped federal separation learning, and belongs to the technical field of image coding and unmanned aerial vehicle systems. According to the method, for an unmanned aerial vehicle system with limited resources and highly dynamic environment, a global image coding model is divided into three segments, a head network and a tail network are deployed at each client, and a main body network is deployed at an edge server; a global image coding model is trained through a resource-adaptive U-shaped federal separation learning framework, and client model aggregation is executed once every I rounds of segmentation training; the method comprises the following steps: firstly, analyzing the convergence of a training model, determining conditions required to be met by a training round, solving an objective function for minimizing training time delay, determining segmentation decision points and I of each client, then carrying out training, and deploying the trained model at the client and an edge server. According to the method, the optimal balance between the communication calculation delay and the training convergence can be realized, and the privacy protection, the resource adaptability and the image coding performance can be effectively considered.