539 results about "Service demand" patented technology

The invention relates to the technical field of wireless communication, in particular to a wireless communication network system and method for intelligently fusing a multi-mode heterogeneous network. Comprising a multi-mode access unit; a protocol compatibility and conversion unit; the heterogeneous network intelligent fusion unit completes cross-network dynamic flow collaboration and resource optimization decision through cross-layer feature association mining, service-network two-dimensional weight calibration and a double-closed-loop feedback optimization mechanism, generates a resource scheduling instruction and transmits the resource scheduling instruction to the intelligent scheduling and resource control unit; an intelligent scheduling and resource control unit; and a system control and cooperation unit. According to the invention, the service-network two-dimensional dynamic fusion weight is constructed through the intelligent fusion unit of the heterogeneous network, and bandwidth, frequency spectrum and power resources are allocated according to the priority and margin balance principle in combination with the intelligent scheduling unit, so that the problem of insufficient two-dimensional coordination of resource scheduling is solved, the resource scheduling is matched with the service demand and the network load, and the resource scheduling efficiency is improved. And resource waste or incapability of meeting business requirements is avoided.

The invention discloses an intelligent customer service dialogue management method and system fused with multi-layer memory, and belongs to the technical field of computers, and the method obtains a three-dimensional context through multi-mode context awareness, achieves the dynamic scheduling of a memory system through a memory coordinator, and combines a dynamic construction mechanism of a service situation portrait, thereby achieving the intelligent customer service dialogue management. The problem that the response of the intelligent customer service system is not matched with the complex and dynamic service demand of the user due to the single situation awareness dimension and the rigid memory scheduling mechanism is effectively solved, and the adaptive personalized service response can be generated according to the real-time change of the dialogue situation.

The invention discloses a rail transit multi-network integration method based on a digital trunking technology, relates to the technical field of communication, and aims to solve the problem that a traditional narrowband trunking system cannot meet the requirements of voice and data comprehensive bearing and vehicle-ground large-bandwidth service real-time transmission. The method comprises the following steps: constructing a time division duplex long-term evolution broadband digital trunking unified bearing platform; an intermediate media access control layer fusion architecture is deployed, and seamless mobility management of the heterogeneous network is realized through unified authentication and multi-link aggregation; an intelligent vertical switching algorithm based on prediction and multi-criterion decision is introduced, a bidirectional long-short-term memory network model is utilized to predict a network state trend, and an improved entropy weight method and an analytic hierarchy process are combined to dynamically select an optimal access network according to service requirements. According to the invention, the network operation efficiency and the user experience can be obviously improved, and high reliability and high service quality of the rail transit communication system are ensured.

The invention provides an intelligent customer service work order processing method based on a large language model, a medium and electronic equipment. Full-process automatic processing of user service requirements from receiving to feedback is achieved through modular design. The method comprises the following steps: receiving and preprocessing demand information input by a user; performing semantic understanding on the normalized input by using a large language model, identifying a demand category, and extracting key parameters such as a room number and demand details; selecting a corresponding work order generation tool from a preset tool library based on the identified demand category, and matching a required business interface; a required information list is preset according to different requirement categories, whether the extracted key parameters are complete or not is automatically checked, and if not, a prompt is generated to guide a user to supplement information; after the information is complete, calling a corresponding work order template according to the demand category, filling the key parameters into the template to generate a standard work order, and pushing the standard work order to a back-end business processing system; and receiving a back-end processing result, combining the back-end processing result with basic reply content generated by the tool, and performing retouching through a large language model to form a final reply to be fed back to the user. Through the above process, specific demands of users in the vertical field can be accurately understood, the standard work order can be automatically generated and pushed, and the processing result can be acquired in real time and fed back to the user, so that the problems that existing intelligent customer service cannot extract complete demands, work order generation lacks specifications and the processing result cannot be fed back in a closed loop mode are solved; and the service efficiency and the user experience are greatly improved.

The invention relates to the technical field of communication, and provides a service processing method, a service processing device, a computer readable storage medium and electronic equipment, and the service processing method comprises the steps: receiving a data transmission service request from user equipment after establishing a service subscription relationship with the user equipment; the data transmission service request comprises a service demand; analyzing a data transmission type associated with the data transmission service request according to the service demand; and establishing different data transmission channels according to different data transmission types, and processing the data transmission service request based on the data transmission channels. According to the method disclosed by the invention, through AI proxy collaboration and intelligent path selection, refined identification and adaptive transmission channel construction for different service requirements can be realized, and the network resource utilization rate and the end-to-end data transmission efficiency are remarkably improved.

The invention discloses a pre-configuration protection method based on risk identification, and the method comprises the steps: collecting multi-dimensional data of a target electric power optical communication network, including logic topology information, a service demand set and dynamic environment data; logic links in the target power optical communication network are identified and divided into different shared risk groups, and a comprehensive risk index of each shared risk group is calculated; adding the shared risk groups of which the comprehensive risk indexes are greater than a preset risk index threshold value into a to-be-protected queue, and generating an optimal standby network loop for each shared risk group in the queue to obtain a network protection ring of the to-be-protected queue; when a to-be-processed service request is received, selecting a target protection path for the to-be-processed service request from the network protection ring, so that the to-be-processed service request is switched to the target protection path when a fault occurs; according to the invention, the network can be rapidly switched when a fault occurs, and the reliability and recovery speed of the power optical communication network are improved.

The invention provides a dynamic reconstruction optimization method and system for communication information network topology, and relates to the technical field of communication networks, and the method comprises the steps: firstly obtaining node operation dynamic information, link transmission real-time information and network service demand dynamic data of a communication information network; generating a network topology elastic association body containing a plurality of association rules and logics based on the two; inputting the service demand data into a network topology elastic association body to generate a network topology dynamic demand adaptation factor; generating a network topology reconstruction path self-adaptive sequence containing a specific operation instruction and a time sequence based on the network topology dynamic demand adaptation factor and the network topology elastic correlation body; and adjusting a node connection mode and link transmission configuration in a linkage manner according to a network topology reconstruction path self-adaptive sequence, and synchronously updating an association rule to complete dynamic reconstruction optimization. According to the invention, the network stability, reliability and resource utilization rate are improved.

The invention discloses an unmanned aerial vehicle trajectory optimization and power distribution method, system and device based on cost evaluation reinforcement learning, and a medium, and the method comprises the steps: constructing an unmanned aerial vehicle data service scene under safety constraints, modeling a multi-objective optimization problem of unmanned aerial vehicle trajectory optimization and power distribution, and designing an unmanned aerial vehicle data service evaluation index; converting a multi-objective optimization problem into a constrained Markov decision problem; respectively designing a state space, an action space, an instant reward function and a corresponding cost function; constructing a cost evaluation critic network parallel to the reward evaluation critic network, training and updating network parameters of the unmanned aerial vehicle by using a cost evaluation SAC algorithm according to a constrained Markov decision problem, and calculating trajectory optimization and power distribution parameters of the unmanned aerial vehicle; the system, the equipment and the medium are used for implementing the method. According to the invention, ground user data service requirements of a data service scene under random and dynamic security constraints are met.

The invention provides a networking scene-oriented multipath service optimization method and system, and relates to the technical field of network scheduling optimization, and the method comprises the steps: obtaining topological structure information and service demand information of a communication network in a networking scene, and employing a depth-first search algorithm in combination with a pruning mechanism to generate a candidate path set; on the basis of a marginal value contribution degree theory, calculating a transmission value factor and a path complementary factor of each candidate path in the candidate path set, calculating marginal value contribution degrees of different candidate path combinations according to the two factors, and taking the path combination with the highest marginal value contribution degree as an optimal path combination; and aiming at each path in the optimal path combination, establishing a multi-objective optimization model, and obtaining a final scheduling scheme of the service flow among the paths in the optimal path combination. According to the invention, the problems of lack of differentiated path selection mechanism, poor fault tolerance of single-path transmission, insufficient resource coordination capability and the like in multi-service transmission in the prior art can be solved.

The invention discloses a virtual power plant and resource matching method and system based on cooperation preference in the field of virtual power plant resource matching, and the method comprises the steps: building a photovoltaic, energy storage and air conditioning load multi-mode cooperation preference scoring model, and quantifying the economic effectiveness, equipment loss, user comfort and other multi-dimensional features; a double-tower representation and contrast learning technology is adopted, and resource attributes and service requirements are mapped to a unified semantic space to calculate the matching degree; in combination with an entropy regular optimal transmission algorithm, many-to-many flexible matching is realized on the premise of considering grid power flow safety constraints; and a rolling multi-cycle optimization mechanism is introduced, and a Bayesian update and reinforcement learning dynamic adjustment strategy is adopted, so that the technical problems of insufficient cooperation intention quantification, complex cross-time constraint and difficult security risk control in distributed resource scheduling under high-proportion new energy access can be solved, and the economy and security of virtual power plant scheduling can be effectively improved. And the performance stability of the system under the new energy fluctuation is enhanced.

The invention discloses a multi-unmanned aerial vehicle low-altitude service scheduling result generation method and device, equipment and a medium, and relates to the technical field of unmanned aerial vehicle scheduling, and the method comprises the steps: constructing a low-altitude service semantic grid, converting the service demand characteristics of each region of a city into a region semantic vector, and mapping an unmanned aerial vehicle task to the grid to generate a task semantic vector; a semantic enhancement mechanism is utilized to calculate the semantic association strength of a task and a region, a multi-dimensional fairness index system is constructed, and a dynamic fairness preference weight is generated through self-adaptive correction. And finally, task allocation and path planning are performed based on the dynamic weight and the semantic association strength, so that the dynamic balance service efficiency and fairness of multi-unmanned aerial vehicle scheduling are improved, regional service deviation is dynamically corrected, the service accessibility of vulnerable regions and crowds is ensured, and the method is adaptive to complex urban environments and abnormal scenes.

The invention discloses a resource allocation and configuration method and device and electronic equipment. The method comprises the following steps: converting network resources in a private network into programmable objects, and constructing a resource label model according to attribute information of the programmable objects and the network resources; receiving service demand information, extracting a service intention in the service demand information, and converting the service intention into a standardized intermediate instruction; generating a resource allocation scheme according to the standardized intermediate instruction and the network resource use state information, and evaluating the resource allocation scheme in a digital twin environment of the private network; and under the condition that the evaluation result of the resource allocation scheme in the digital twin environment meets a preset requirement, converting the resource allocation scheme into a control instruction, and sending the control instruction to the network resource. The technical problems of low network resource allocation efficiency and slow service response speed caused by non-uniform resource description and high service demand analysis difficulty in a multi-manufacturer heterogeneous network environment are solved.

The invention discloses a self-adaptive communication protocol switching method and device. The method comprises the following steps: acquiring network environment data corresponding to a target network environment, terminal equipment data corresponding to terminal equipment in the target network environment and service demand data; fusing the three kinds of data to obtain fused feature data; inputting the fused feature data into a network environment prediction model, and processing the fused feature data by using the network environment prediction model to obtain performance prediction data of each candidate network in the target network environment on a future preset time window; according to the adaptation capability value of each communication protocol in the protocol library under the performance prediction data; and after a target communication protocol is selected according to the adaptation capability value and the service demand data, switching to the target communication protocol. According to the invention, the technical problem that a conventional communication system adopts a fixed communication protocol and cannot be dynamically adjusted according to a network environment and service requirements in the prior art, which has great limitation, is solved.

The invention provides a power communication resource dynamic allocation method, and relates to the technical field of power communication resource dynamic allocation, and the method comprises the steps: recognizing a power business data type, and calculating a business weight W; monitoring the quality state of each communication channel in real time and calculating the channel quality Q; monitoring service requirements or channel quality in real time, and triggering dynamic optimization when the channel quality cannot meet the service requirements; excluding businesses needing fixed resource allocation and businesses whose business weights are higher than those of the businesses triggered to be optimized this time, and enabling the rest businesses to participate in dynamic optimization; configuring network equipment parameters according to the result to execute resource allocation optimization; according to the method, the state change of the communication network can be responded in real time to adjust the resource allocation strategy, the risk of communication interruption or flash of key services due to resource optimization is effectively reduced, and finally, the utilization rate of power communication resources is guaranteed; and the reliability, the stability and the real-time performance of core service transmission such as power grid production control and operation monitoring are greatly improved.

The embodiment of the specification provides a gas operation method and an Internet of Things system based on a smart gas call center. The method comprises the following steps: acquiring gas user call data of the call center; predicting demand information of different types of users based on the gas user call data, wherein the demand information at least comprises gas product demand and gas service demand; determining and pushing gas operation push features based on the demand information of different types of users, wherein the gas operation push features comprise push type features and push content features.

The invention provides a link determination method and device, electronic equipment and a storage medium, and relates to the field of mobile communication. The method comprises the following steps: determining a target service type corresponding to service data of a terminal; determining a first prediction result based on the terminal state parameter and the network performance parameter of the first link, the first prediction result being used for indicating the transmission performance which can be reached when the first link transmits the service data of the target service type; determining a second prediction result based on the terminal state parameter and the network performance parameter of the second link, the second prediction result being used for indicating the transmission performance which can be reached when the second link transmits the service data of the target service type; and determining a target link from the first link and the second link based on the first prediction result and the second prediction result. According to the application, the selected target link can meet the service requirement of the target service type, so that the network service quality can meet the service requirement.

The invention discloses an electric power system resource scheduling method and device, and belongs to the technical field of electric power systems, and the method comprises the steps: obtaining the resource data of an electric power system when the natural climbing amount of the electric power system is not greater than the climbing demand of the electric power system, and taking the minimization of the total operation cost of the electric power system and the maximization of the climbing service demand response as targets; constructing an objective function, a system power balance constraint, a transmission capacity constraint, an energy storage charging and discharging constraint, an energy storage energy balance constraint, a climbing ability constraint and a climbing service demand constraint; and solving the target function under each constraint to obtain the output of each thermal power generating unit and each energy storage system in each scheduling period and the up-climbing demand quantity and the down-climbing demand quantity of each flexible climbing price interval in each scheduling period, and scheduling the resources of the power system according to the solving result. By implementing the invention, the problem that the power supply and demand of the power system are unbalanced when the natural climbing amount is not greater than the climbing demand in the prior art can be solved, and the operation stability of the power system is improved.

The application discloses a kind of virtual-real fusion registration satellite internet digital twin deduction evaluation methods, comprising: S1.Satellite internet global network data is acquired, network data is collected and time synchronization interpolation is carried out, and network equipment data matrix is constructed;S2.based on network equipment data matrix, establish satellite network basic routing topology graph;S3.based on satellite network basic routing topology graph, construct by user satellite network dynamic service demand vector, establish satellite network dynamic routing model;S4.based on network dynamic routing model, establish satellite internet digital twin deduction model;S5.based on internet digital twin deduction model, introduce real data and carry out pseudo-real correction, realize the virtual-real fusion digital twin dynamic deduction of all stages;S6.multiple dimensions index and evaluation function are established, and score is calculated.The application can overcome virtual-real mapping distortion, evaluation dimension single and dynamic adaptability insufficient and other problems, complete accurate deduction evaluation to satellite internet.

The invention discloses a code-free application construction method and device based on a multistage service model, and relates to the field of code-free application construction. The method comprises the following steps: receiving a service demand of a user to obtain a demand feature tag; based on the demand feature tags, matching service models meeting conditions to obtain a multi-stage service model set; analyzing and instantiating the multi-stage business model set through a generation engine, and outputting an initial application component; receiving a configuration instruction of a user, and adjusting the initial application component to obtain a target application component; calling a data bridging interface, a permission matrix interface and a cross-component collaboration interface, and establishing a data flow relationship and a permission mapping rule among the components in the target application component to obtain an initial application and integrated link; and verifying the initial application, if the verification result meets the application release condition, deploying the initial application to the target operation environment, and outputting the target application. By implementing the technical scheme provided by the invention, the application construction efficiency and stability can be remarkably improved.

The invention relates to a space-based cloud-oriented intelligent service management arrangement method and apparatus, and a communication device. The method comprises the following steps: a management orchestration body obtains satellite computing service demand data and global resource state data, and obtains task service level protocol parameters and a dynamic fusion resource map based on the satellite computing service demand data and the global resource state data; based on the task service level protocol parameters and the dynamic fusion resource map, generating task scheduling and resource allocation joint strategy information through a deep reinforcement learning model in combination with a preset optimization target; performing network function instance deployment and resource configuration of the satellite computing service based on the strategy information; and obtaining a service execution analysis result of the satellite calculation service, and generating a reward function according to the analysis result in combination with the task service level protocol parameters and the dynamic fusion resource map to update the parameters of the deep reinforcement learning model. According to the invention, better service quality guarantee and higher resource utilization efficiency of the satellite computing service in the space-based network can be ensured.

The invention provides a comprehensive service intelligent management method, which comprises the following steps: S1, acquiring a service demand submitted by a user, and analyzing and generating a resource configuration scheme through an AI algorithm; s2, the resource configuration scheme is automatically checked through an AI auditing engine, and manual auxiliary auditing is triggered; s3, automatically executing cross-system equipment configuration and verifying link performance according to the resource configuration scheme passing the audit; and S4, on the basis of the real-time monitoring data, utilizing an AI algorithm to predict equipment faults and schedule maintenance tasks. According to the method, through full-process AI enabling and cross-system collaborative management, the core pain points of low efficiency, fault processing lagging, non-standard auditing and high cost in traditional communication network management are effectively solved, and powerful support is provided for intelligent, efficient and low-cost operation of the communication network.

The invention discloses a computing power load space-time migration regulation and control method and a related device. The method comprises the following steps: acquiring power regulation information required by a power grid frequency modulation service; according to the power regulation information required by the power grid frequency modulation service, constructing a space-time migration characteristic model of a data center computing power load, and calculating the computing power load based on the space-time migration characteristic model of the data center computing power load; constructing an optimization problem by taking the minimum economic cost as an optimization target according to the computing power load capacity, constructing constraint conditions, solving the optimization problem under the constraint conditions to obtain an optimal regulation and control scheme, and carrying out computing power load space-time migration regulation and control according to the optimal regulation and control scheme. According to the method and the related device, the space-time multi-dimensional adjustment potential of the computing power load can be mined for multi-service requirements, the space-time migration regulation and control of the computing power load are improved, and safe and economical operation of a power grid is ensured.

The invention discloses a satellite switching method and device, equipment, a storage medium and a program product. The method comprises the following steps: performing communication quality prediction based on historical communication index data, reflected pulse intensity data and spatial position data, and determining predicted communication quality data; and performing communication demand analysis based on the communication service parameters of the user satellite communication equipment, and determining communication demand data. And matching at least one target satellite from the plurality of satellites to be selected based on the communication demand data and the predicted communication quality data. According to the technical scheme provided by the invention, the continuity and stability of communication connection of a user in a satellite communication process are fully guaranteed, and the problem of lagging or interruption in real-time communication services such as satellite communication is effectively avoided. According to the technical scheme provided by the invention, satellite switching can be flexibly adjusted and formulated according to the current service demand of the user, smooth and stable execution of the service is ensured, and the user experience is effectively improved.

The invention belongs to the technical field of computing network resource arrangement, and particularly relates to a computing network resource sensing method based on a lightweight data acquisition technology. Operation state data of computing network resources are collected in real time in a non-intrusive mode, a prediction model is constructed by using an intelligent behavior prediction technology and a machine learning algorithm, future behaviors of the computing network resources are predicted, analyzed and processed and converted into a structured format, and the computing network resources are obtained. And a computing network resource arrangement decision strategy is formulated by combining the association mapping relationship between the computing network resource data and the service demand. The method realizes real-time capture and accurate prediction of the computing network resource state; compared with the prior art, the operation state data of the computing network resources can be more comprehensively and accurately obtained, the change trend of the resources can be predicted in advance, and a timely and reliable basis is provided for resource arrangement decision making.

The invention provides an ad hoc network and 5G network intelligent fusion handheld terminal and a switching strategy method. The handheld terminal comprises an ad hoc network module, a 5G module, a network detection module, a service extraction module, a power management module and a switching decision module. The ad hoc network module provides an ad hoc network communication link; the 5G module provides a 5G communication link; the network detection module periodically monitors the channel quality of the 5G link and the ad hoc network link; the service demand extraction module is used for determining whether to perform channel switching immediately or not according to the influence degree of the channel switching on the application for different service types; the power management module monitors the residual electric quantity of the equipment in real time; and the switching decision module automatically selects to switch an ad hoc network or a 5G channel according to factors such as link quality, battery power and service types. According to the invention, seamless, efficient and intelligent switching between the ad hoc network and the 5G network is realized through the ad hoc network + 5G fusion design and the switching strategy, and the communication effect and the user experience of the handheld terminal are improved.

The invention discloses an intelligent agent-based office network and server network intelligent isolation system and method, a storage medium and computer equipment, and the method comprises the steps that a business process analyzer determines a core business application and a data flow according to an enterprise business process, and determines business demand information according to the core business application and the data flow; the security policy engine configures a basic isolation rule of the intelligent isolation gateway according to the service demand information and the initial security policy; each sensing agent monitors network flow data and system behavior data of a deployment position; the analysis agent analyzes the network flow data and the system behavior data to generate a first risk identification result; the security policy engine receives the first risk identification result and generates a dynamic security policy according to the first risk identification result; the execution agent adjusts isolation parameters of the intelligent isolation gateway based on the dynamic security policy; and the intelligent isolation gateway isolates and controls communication data between the office network and the server network based on the basic isolation rule and the adjusted isolation parameters.

Disclosed embodiments are related to Management Data Analytics (MDA) relation with Self-Organizing Network (SON) functions and coverage issues analysis use case. An MDA Service (MDAS) obtains input data related to one or more managed networks and services from one or more data sources; generates an analytics report based on analysis of the input data; and sends an analytics report to a Self-Organizing Network (SON) function for root cause analysis of ongoing issues, prevention of potential issues, and / or prediction of network or service demands. The analytics report may describe an identified network or cell coverage issue related to the SON function. Other embodiments may be described and / or claimed.

The invention discloses an analysis method for 5G network user perception improvement based on wireless intelligent arrangement, and the method specifically comprises the following steps: 1, the perception of an online user terminal is evaluated in real time, and the perception evaluation comprises the multi-dimensional evaluation of the data transmission congestion state of the user terminal and the wireless channel quality; and 2, when the perceptibility evaluation result indicates that the user experience is degraded, a wireless intelligent arrangement decision is triggered, and the decision is based on the service requirement, the terminal capability and the space-time position of the user terminal. According to the analysis method for improving 5G network user perception based on wireless intelligent arrangement, through AI-driven dynamic resource scheduling and in combination with a predictive network self-optimization function, the end-to-end time delay of low-time-delay services such as high-definition video calls, cloud games and VR / AR is guaranteed to be lower than 20 milliseconds, the lagging phenomenon is remarkably eliminated, and the user perception is improved. Seamless service continuity guarantee is achieved, and measurement-free switching is achieved through a wireless fingerprint grid knowledge base.

The invention discloses a script generation method and device, equipment, a storage medium and a product, which are applied to the technical field of computer data processing, and the method comprises the following steps: obtaining business demand information corresponding to a target business function; semantic analysis is conducted on the service demand information, a template configuration file is generated, and the template configuration file at least comprises service parameters needed for achieving the target service function, attribute information of the service parameters and logic rules corresponding to the service parameters; analyzing the logic rule to generate an abstract syntax tree corresponding to the target service function; and performing data integration on the service parameters, the attribute information of the service parameters and the abstract syntax tree to generate an executable script for realizing a target service function. According to the scheme, manual code writing and manual template configuration are not needed, and the script generation efficiency is improved.

The invention provides a government affair hotline resource optimization method and device based on time sequence prediction and reinforcement learning. The method comprises the steps of obtaining historical service work order data of a preset historical time period from a government affair hotline service platform; according to the historical service work order, utilizing a time sequence prediction model to predict future service work order data in a preset future time period; and determining a resource scheduling strategy in the preset future time period by using a reinforcement learning model. According to the technical scheme provided by the invention, in order to improve the working efficiency and reduce the user waiting time and unnecessary troubles in the process that government affair hotlines serve people, the historical work order data is deeply analyzed by using the time sequence prediction model, and possible problem hotspots and service demand peak periods in the future can be more accurately predicted. The distribution strategy of manpower and technical resources is dynamically adjusted in combination with a reinforcement learning algorithm, and it is ensured that the optimal government affair hotline service response speed and service level can be kept in different time periods.