444 results about "Service quality" patented technology

The invention discloses a grassroots society digital governance method and system, and the method comprises the steps: collecting multi-source heterogeneous data in real time through an Internet of Things sensing network disposed in a grassroots community, and generating a standardized multi-mode sensing data flow; based on the multi-modal perception data stream, outputting a time-space associated cleaned data set; inputting the cleaned data set into a multi-scale space-time encoder, and generating a feature tensor containing regional hotspot distribution and a risk propagation path; based on the feature tensor, constructing a dynamic risk knowledge graph, and outputting a decision matrix including a risk level and an optimal intervention path; inputting the decision matrix into a strategy optimization engine to obtain a hierarchical governance instruction set; and on the basis of real-time governance feedback data after the hierarchical governance instruction set is executed, a conflict instruction in the strategy chain is autonomously corrected through a fuzzy reinforcement learning algorithm. By utilizing the embodiment of the invention, an efficient, intelligent and traceable digital governance scheme can be realized, so that the social governance efficiency and the service quality are improved.

The invention relates to the technical field of data processing, and provides a train dynamic scheduling method and a resource allocation system, through real-time acquisition and processing of heterogeneous data, generation of train priorities, and generation and verification execution of a scheduling scheme, fine management of a whole train scheduling process is realized, all steps cooperate with one another and are progressive layer by layer, and the scheduling efficiency is improved. Various complex factors in the train running process can be comprehensively considered, the limitation that a traditional dispatching mode depends on experience or a single index is changed, the scientificity, accuracy and timeliness of train dispatching decisions are remarkably improved, resources can be dynamically and efficiently allocated, train running arrangement can be optimized, and the train dispatching efficiency is improved. The transportation efficiency and the service quality are improved, and the ever-increasing diversified requirements of modern railway transportation are effectively met.

The invention relates to the technical field of semantic analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an intention analysis and strategy generation method, device, equipment and medium, and the method comprises the steps: obtaining interaction data, recognizing an interaction type according to metadata features, selecting a corresponding analysis model to analyze and process data, and generating a text corpus; current user information is extracted from the text corpus, user intention score analysis is executed based on an intention analysis strategy corresponding to the interaction type, and a current user intention score is generated; and generating a demand list according to the user information, the intention score and the interaction type, and generating and outputting an interaction strategy based on the user information and the demand list. Through interaction data processing and automatic intention scoring analysis, the demand list and the interaction strategy of the customer can be quickly and accurately generated, the customer information processing efficiency and accuracy are improved, the workload of manual input and analysis is reduced, and the customer service quality and the response speed are improved.

The invention discloses a dynamic library management method and system based on artificial intelligence, and relates to the technical field of library management, and the method comprises the following five steps: firstly, constructing a reader portrait through collecting basic information, borrowing history and other data of a reader by using TF-IDF analysis and a machine learning algorithm; secondly, a positioning tag and a sensor are deployed to be combined with a book RFID tag, a path is optimized according to reader behavior data, and the book retrieval efficiency is improved; monitoring and analyzing borrowing behavior data and reader portraits, establishing a borrowing risk assessment model, assessing risks by adopting a logistic regression algorithm, providing decision suggestions for workers, quantitatively adjusting the borrowing quantity, and reducing the risk of overdue or damaged books; through application of the artificial intelligence technology, automation, intellectualization and individuation of library management are realized, the management efficiency and the service quality are remarkably improved, and the operation effect of the library is enhanced.

The invention relates to the technical field of rail transit communication, and discloses a communication network optimization method and device for rail transit. According to the communication network optimization method and device for rail transit, the quality of the communication link is regulated and controlled according to the real-time state of train operation, the stability of data transmission can be guaranteed, the reliability of the communication network in the train operation process is improved, accurate transmission of key data such as train operation control is guaranteed, and the service life of the communication network is prolonged. Traffic is regulated and controlled according to load distribution of network nodes of a track area, network congestion of a hot spot area can be effectively relieved, network loads are balanced, the utilization efficiency of network resources is improved, network operation is smoother, normal development of various services is guaranteed, access priority is regulated and controlled according to different service requirements, and the service quality is improved. Therefore, the emergency message can be transmitted preferentially, the timeliness and the efficiency of emergency handling are improved, and the safety and the emergency response capability of the rail transit system are enhanced.

The invention relates to the technical field of logistics and supply chain management, and discloses a one-station inspection platform-based product management method, which comprises the following steps of S1, constructing an optimal transportation problem model, defining a resource circulation relationship between a supplier and an order, and calculating an optimal scheme allocated to the order by the supplier by taking the minimum transportation cost as a target; s2, based on a game theory model, strategy interaction among a plurality of suppliers is considered, a supplier resource allocation strategy is optimized through a game, and balance of resource scheduling is ensured; s3, a Markov decision process is adopted, and order circulation and resource scheduling strategies are adjusted through real-time feedback so as to adapt to dynamic changes of service requirements; and S4, carrying out multi-objective optimization. According to the invention, through a dynamic optimization and real-time data feedback mechanism based on the one-station inspection platform, efficient resource scheduling and order circulation are realized, the maximization of the resource utilization rate is ensured, the delivery timeliness is improved, and the cost and the service quality are optimized at the same time.

The present application relates to the technical field of communications, and discloses a path planning method and apparatus, a device, a system, and a storage medium. The method comprises: acquiring traffic prediction information respectively corresponding to at least one time period; and on the basis of the traffic prediction information respectively corresponding to the at least one time period and at least one selectable path respectively corresponding to each service, determining a target forwarding path of each service meeting path planning objectives. The path planning objectives comprise: the service traffic borne by any link in a hierarchical network in any time period is less than or equal to the bandwidth capacity upper limit of any link, load balancing is realized between multiple links connected to a same network node in the hierarchical network, and the transmission quality of the target forwarding path of any service meets a quality requirement of any service. Path planning of a global service is realized, network link congestion can be reduced, and better effects that load balancing between all network links is realized and a service forwarding path meets a service quality requirement are achieved.

The invention provides a supplier service quality assessment management system and method based on dynamic weight optimization, and belongs to the technical field of weight adjustment. The total index module is used for determining quality assessment indexes and sub-indexes thereof according to supplier service contents and contract requirements; the data acquisition module is used for acquiring historical performance data of a target supplier and standardizing the historical performance data to obtain standard performance data; the first scoring module is used for determining a first score of the quality assessment index according to the initial weight of the quality assessment index and the quantification method in combination with the standard performance data; the dynamic weight module is used for generating a weight adjustment strategy according to a business scene of the standard expression data, and obtaining a first weight of the quality assessment index after adjusting an initial weight; and the scoring module is used for calculating a quality assessment score of the target supplier according to the first weight and the first score. The accuracy and the dynamic adaptability of supplier service assessment are improved, and quality assessment and decision support are optimized.

The invention discloses a large model task scheduling optimization method and device, and the method comprises the steps: analyzing a task type and a service quality requirement corresponding to a large model reasoning task when a scheduling request of the large model reasoning task is received; determining current state information and historical execution information corresponding to the large model reasoning task; inputting the task type, the service quality requirement, the current state information and the historical execution information into a pre-trained scheduling agent, so that the scheduling agent outputs a scheduling action corresponding to the large model reasoning task; executing a scheduling action on the large model reasoning task, and recording corresponding performance data of the scheduling action in an execution process; and inputting the performance data into the scheduling agent, so that the scheduling agent updates a weight parameter of the scheduling agent according to the performance data and a preset reward function. The problem that a traditional static scheduling strategy cannot adapt to a complex heterogeneous environment is effectively solved, and the system response efficiency, the resource utilization rate and the user satisfaction degree are remarkably improved.

The invention discloses an intelligent scheduling method based on task optimization. According to the method, firstly, the task load of each time period is predicted through historical data, and then an M / M / c queuing model is established to quantify a task queuing duration expected value as an optimization target. A two-stage optimization strategy is adopted: in the first stage, the optimal number of service desks in each time period is determined by applying dynamic planning, and accurate distribution of human resources is realized; in the second stage, specific employees are distributed to shifts through constraint planning, and meanwhile, complex constraints such as total working time fixing, continuous working duration, shift intervals and skill matching are met. According to the system, a queuing theory, constraint optimization and a prediction model can be combined, and on the premise of ensuring the feasibility of a scheduling scheme, the task processing waiting time is effectively shortened, and the service quality and the human resource utilization rate are improved.

The invention relates to the technical field of environmental sanitation service quality management, and discloses an environmental sanitation service evaluation method based on a task decoupling and closed-loop feedback mechanism, and the method comprises the steps: carrying out the processing of environmental sanitation operation flow data and service item feature data of a target region through a task decoupling model, and generating a task decomposition thermodynamic diagram and a weight gradient field; secondly, constructing a multi-dimensional evaluation index system, and formulating a dynamic data acquisition strategy in combination with a DBSCAN clustering algorithm; the feedback data acquisition equipment acquires service feedback data according to the strategy, and identifies a service quality level and a defect item through a random forest model; and finally, based on a closed-loop feedback mechanism, the evaluation data are uploaded to a management control center to carry out adaptive correction of the index threshold and the weight. According to the method, fine modeling of environmental sanitation operation is realized through task decoupling, the evaluation standard is dynamically optimized by using closed-loop feedback, the problems of single evaluation dimension and index updating lagging in a traditional method are solved, and the accuracy and timeliness of environmental sanitation service evaluation are improved.

The invention discloses an irregular ship scheduling method and system considering uncertain harbor time, and a medium, and belongs to the technical field of shipping management. The method comprises the following steps: collecting ship, cargo, port and interference event data; generating an initial scheduling scheme by adopting a greedy strategy; generating multiple groups of random interference scenes based on Monte Carlo simulation; a two-stage stochastic programming model is constructed, in the first stage, income maximization serves as a target, and an initial plan is generated through damage and repair operator iterative optimization by means of a self-adaptive large neighborhood search algorithm; in the second stage, aiming at each interference scene, a recovery network is constructed for the influenced goods, and an optimal recovery strategy and adjustment cost are solved by utilizing a shortest path algorithm; and finally, outputting a scheduling scheme including a ship path, a navigational speed and a multi-scene recovery strategy through iterative optimization. According to the method, the earnings and the operation efficiency of the shipping companies are improved, the adjustment cost caused by uncertainty is reduced to the greatest extent, the benefits of the shipping companies and cargo owners can be balanced in a complex scheduling problem, and the service quality is improved.

The invention provides an intelligent drill evaluation method and system based on a large model and RAG, a medium, a program product and a terminal. The method comprises the steps that a virtual training scene is constructed based on a large language model; the trainee carries out dialogue interaction with the virtual customer portrait in the virtual training scene, and dialogue interaction data is collected in real time; and analyzing and feeding back the virtual customer and the dialogue interaction data by adopting RAG, and evaluating the comprehensive ability of the trainee based on a multi-dimensional evaluation index. According to the invention, trainees are helped to identify portrait characteristics of virtual customers, determine questions possibly concerned by the portrait customers and provide answering strategies; and the professional ability of the trainee is comprehensively evaluated from multiple dimensions of answer fluency, objection question processing, portrait question pertinence, customer emotion processing, insurance professional knowledge and the like, so that the accuracy and fairness of evaluation are ensured. According to the method, virtual customer portrait analysis is combined with insurance industry information and enterprise private domain knowledge, the professional ability and service quality of trainees can be comprehensively improved, and a multi-dimensional evaluation mechanism is of great significance to improvement of customer service quality and satisfaction.

The invention relates to the technical field of resource scheduling, in particular to a rural tourism industry chain collaborative optimization method based on a knowledge graph, and the method comprises the steps: constructing a dynamic knowledge graph, generating a personalized itinerary plan, carrying out dynamic resource scheduling and supply chain optimization, carrying out service quality closed-loop control, and carrying out partition graph comparison optimization. Compared with the defect that an existing recommendation system depends on historical static data to generate a fixed route and cannot respond to real-time bearing capacity change to cause excessive crowding of hot scenic spots, the scheme has the advantages that through bearing capacity threshold hierarchical control and a replacement engine dynamic triggering mechanism, knowledge graph correlation degree screening and traffic timeliness constraint are combined, so that the real-time bearing capacity change can be responded; and when overload occurs, automatic shunting is performed to substitute nodes with similar experiences and exclusive preferences are pushed, so that the experience comfort of tourists is guaranteed, regional resource loads are balanced, and dynamic balance of supply and demand is realized.

The invention relates to the technical field of artificial intelligence, and discloses an artificial intelligence-based verbal skill partner training method, device and equipment and a storage medium, and the method comprises the steps: obtaining a dialogue state between an AI partner training person based on a DNQ model and a user in a service dialogue scene; obtaining an award generated by a service verbal skill adopted by the user in the conversation state and a new conversation state; obtaining dialogue experience between the AI training partner and the user according to the dialogue state, the service verbal skill, the reward and the new dialogue state; performing reinforcement learning training on the DNQ model according to dialogue experience; and performing parameter updating on the DNQ model to guide the user to perform service verbal skill adjustment. The method can be applied to a verbal skill partner training scene of financial insurance service or a verbal skill partner training scene of medical service, can provide highly personalized, real-time feedback and continuously optimized verbal skill partner training for the user, effectively improves the service quality, customer satisfaction and training efficiency of the user, and saves the training cost at the same time.

The invention relates to the technical field of e-commerce, and discloses an e-commerce customer service processing system with intelligent quality inspection and high-concurrency simulation capabilities. According to the invention, millisecond index calculation and real-time alarm of full customer service dialogues are realized through a bypass monitoring technology, a traditional lagging mode of post sampling inspection is changed, and management response is converted from passive remedy to active intervention; a high-concurrency pressure simulation module reproduces a business scene in an e-commerce peak period by simulating a script of a real user behavior and a distributed cluster, and a real basis is provided for system capacity planning and stability guarantee; the integrated intelligent verbal skill evaluation module deeply analyzes the dialogue quality from multiple dimensions such as semantics, compliance and emotional change based on a natural language processing technology, and generates an evaluation report with guidance, so that the professional level of customer service is improved; and the service quality, the operation robustness and the management intelligence level of the e-commerce customer service system are improved.

The embodiment of the invention provides a random access method and device, relates to the technical field of communication, and aims to reduce the influence on the ongoing service of terminal equipment, improve the service quality and improve the user experience. The method comprises the following steps: the terminal equipment sends a random access lead code; the terminal equipment receives a random access response message, wherein the random access response message carries a time advance TA value; and under the condition that the TA value is greater than the first preset threshold, the terminal equipment retransmits the random access lead code.

The invention relates to the field of shared control, and discloses an intelligent shared control method and system of a plasma waterless washing machine, which are used for solving the core pain points of the traditional shared washing machine in the dimensions of prediction, energy consumption, maintenance and control. According to the method, through fusion of multi-model cooperative calculation and interdisciplinary theory, full-link optimization control is combined with an evolutionary game theory incentive mechanism and a Lyapunov energy function optimization algorithm, an equipment start-stop strategy and a user integral rule are dynamically generated, and energy consumption and service quality are balanced; and constructing a thermodynamic entropy increase optimization model to dynamically update an environment coupling coefficient and a weight parameter, and integrating meteorological and power grid data to form a self-adaptive negative feedback control ring. According to the invention, the limitation of traditional single-point optimization is broken through, the cleaning uniformity error is improved, the fault early warning response speed is accelerated, and the energy efficiency and reliability of the shared washing machine are remarkably improved.

The invention belongs to the technical field of public transport scheduling, and discloses a public transport capacity monitoring and scheduling method and system, and the method comprises the steps: collecting the real-time passenger flow volume, historical passenger flow volume and environmental factor data of a target bus line, and carrying out the standardization and abnormality detection; constructing a hybrid prediction model comprising a time sequence decomposition model and a random fluctuation model, and predicting the passenger flow in the future period; the vehicles are divided into fixed shifts, maneuvering shifts and standby shifts, and vehicle configuration is dynamically adjusted according to the predicted load factor; through multi-source data fusion and an intelligent prediction algorithm, accurate monitoring and dynamic scheduling of the public transport capacity are realized, the vehicle utilization rate and the service quality are improved, and the operation cost is reduced.

The invention discloses a dynamic context window customer service quality inspection method based on a large model, and the method comprises the following steps: S1, generating a dynamic window: scoring the dialogue round of a customer service and a user, dynamically updating and maintaining a context window according to a scoring result, and carrying out the context reconstruction of a dialogue in the window; s2, multi-dimensional quality inspection: inputting the dialogue text in the dynamic window into a large model, and outputting a preset field through a customized prompt trigger model; s3, clustering attribution: carrying out semantic clustering on related contents output by the large model by adopting a kmeans algorithm and BERT vectorization, and then generating a general description and an operable suggestion for each clustering result through prompt; and S4, result output and application: generating a structured json result containing a multi-dimensional quality inspection result and a clustering result, wherein the structured json result is used for api calling or visual platform display. The method has the advantages that efficient, accurate and multi-dimensional customer service quality inspection can be achieved, and the service quality can be improved and overcome.

The invention relates to the technical field of digital twinborn system technologies, in particular to a hospital construction and reconstruction evaluation method and system based on VR assistance and digital twinborn technology design operation, which can improve the design efficiency and quality, reduce the risk and cost, and improve the operation efficiency and service quality. The method comprises the steps of collecting multi-source heterogeneous data of a target courtyard area; feature extraction is carried out on the multi-source heterogeneous data, a parameter feature set used for describing and evaluating courtyard performance is obtained, and the parameter feature set comprises a space utilization rate, an illumination condition, a ventilation effect, a noise level and a people flow and logistics path; building a virtual model of the target courtyard area by using a digital twinborn technology based on the parameter feature set; importing the constructed virtual model into a preset VR system, so that the model is virtually presented in the VR system; real-time interactive adjustment and simulation are performed on courtyard design by using a VR system; and collecting feedback data generated when the user interacts with the model in the VR environment.

The invention relates to the technical field of machine learning, and discloses an outsourcing service quality evaluation method based on deep learning, which comprises the following steps: capturing operational micro habit dynamics of a service subject through lightweight representation data, establishing a self-adaptively updated reference normal state model, monitoring deviation in real time, generating an early disturbance signal, and determining the outsourcing service quality according to the early disturbance signal; and performing correlation analysis on the multiple signals to identify a predefined disturbance mode, and finally dynamically evaluating the service quality based on mode matching. According to the method, early-stage risk early warning which cannot be captured by a traditional macroscopic index is realized through fine-grained perception and modeled association of micro habits, and meanwhile, a judgment threshold is dynamically calibrated in combination with a situation beacon, so that the early-warning precision and timeliness are remarkably improved, and the early-warning effect is improved. And the multi-dimensional monitoring capability from individual anomaly to collective out-of-order is expanded by means of group behavior entropy change analysis.

The invention provides a communication method and a communication device, which are used for solving the problems of network resource waste or service quality reduction and the like and poorer self-adaptive capability when fixed interaction processes and related parameters are applied to scenes such as different network states or different terminal states and the like during calling of an existing data analysis function. The method comprises the following steps: a first network element receives a first message from a second network element, wherein the first message is used for requesting task decomposition of at least one service request; the first network element obtains a task decomposition result corresponding to the service request, the task decomposition result comprises identification information of one or more service functions, the task decomposition result is obtained according to an artificial intelligence AI model, and the service functions are used for realizing corresponding data processing functions; and the first network element sends the task decomposition result to the second network element.

The invention provides a communication method, a communication device and a communication system. The method comprises the following steps: acquiring RDMA information of a network function network element; and judging whether to use RDMA transmission or not according to the RDMA information of the network function network element. In the core network, a large amount of data is transmitted based on the RDMA protocol instead of the SBI protocol, so that the real-time data or real-time signaling transmitted on the service bus cannot be influenced, and the service quality can be improved. Moreover, the data transmission based on the RDMA protocol can reduce the CPU load of the network element of the core network, and can meet the requirements of low time delay and high throughput of data transmission.

The invention provides a salary payment management interaction method, system and device and a medium, and relates to the technical field of accounting services, and the method comprises the steps: firstly integrating a salary mode setting control, an income tax calculation control and a salary grouping payment control through a salary payment management interaction main interface; detailed salary structure configuration, formula editing and salary issuing subject classification association are carried out on the salary mode setting sub-interface, and a flexible salary configuration rule meeting actual requirements is generated; in the income tax calculation sub-interface, the special deduction data is automatically matched according to the preset salary and tax rules, the amount of payable tax and the actual salary are accurately calculated, and the accuracy and compliance of tax processing are ensured. And finally, effective management of the service object and accurate payment of the salary are realized on the salary grouping payment sub-interface, so that the salary processing efficiency is improved, the timeliness and correctness of tax payment are ensured, and the professional level and service quality of enterprise salary management are integrally improved.

The invention belongs to the field of flight evaluation, and provides a flight operation guarantee service quality evaluation analysis method and system, and the method comprises the steps: collecting multi-dimensional guarantee service index data in a flight operation guarantee process; collecting airport operation situation data; inputting the airport situation vector into a trained neural network model, and outputting a corresponding index weight correction factor to obtain a correction weight; performing weighted calculation on the standardized index matrix based on the correction weight to obtain a comprehensive service quality evaluation value; calculating a variance of the comprehensive service quality evaluation value in a preset time period, and performing optimization iteration on the neural network model by adopting a back propagation algorithm by taking the variance as a loss function until the loss function is converged; and outputting a comprehensive service quality evaluation result obtained based on the final correction weight.

Proposed is a V2X apparatus for measuring or predicting service quality, and the V2X apparatus comprises: a transceiver configured to receive a service quality measurement value or a service quality prediction value from at least one user device or transmit a request for service quality improvement according to service quality prediction; and a processor configured to acquire a service quality prediction value on the basis of the received service quality measurement value or the received service quality prediction value, wherein the received service quality measurement value is acquired when a first user device receives a V2X message that has been transmitted by the first user device, and the received service quality measurement value or the received service quality prediction value may be classified according to information regarding a geographical area for V2X.

The invention provides a bus dynamic multi-objective optimization scheduling method based on reinforcement learning. The method comprises the following steps: firstly, initializing a motorcade scale and a one-way set, and segmenting an operation time period into a plurality of rescheduling stages; constructing a reinforcement learning model of the current rescheduling stage; sequentially carrying out decision making on each decision point in the current rescheduling stage by utilizing a reinforcement learning model to form an optimal solution of the current rescheduling stage; repeating the decision-making process of the current rescheduling stage for multiple times to form an optimal solution set of the current stage; and sequentially processing each rescheduling stage until all rescheduling stages are processed. Through the scheme provided by the invention, the vehicle scheduling scheme can be more suitable for a real operation environment, conflicts between targets are fully considered, and the operation level and the service quality of buses are improved.

The invention discloses a supermarket cash register energy consumption intelligent regulation and control and energy efficiency optimization method and a management system. According to the invention, through accurate linkage of passenger flow prediction and equipment regulation and control, dynamic balance between energy consumption and service requirements is realized. In a low-peak period, the screen brightness is automatically reduced, the CPU operation frequency is reduced, and the idle cash register is turned off, so that the electric power waste when the equipment is in a no-load state is reduced; and the standby equipment is activated in advance and the performance parameters are recovered in the peak period, so that the cashier queuing problem caused by temporary starting is avoided. Based on elastic adjustment of actual passenger flow, energy consumption is directly matched with real business requirements, invalid energy consumption in a traditional fixed operation mode is avoided, the checkout efficiency of customers in peak hours is ensured, the energy utilization efficiency of equipment is fundamentally improved, historical energy consumption analysis provides a datum reference for a regulation and control strategy, and the energy utilization rate of the equipment is improved. The cashier service quality is ensured, the energy consumption cost is reduced to the maximum extent, the workload of manual inspection and intervention is reduced, and equipment management is more efficient.

The invention relates to a token management method and device, equipment and a storage medium. The method comprises the steps of obtaining a storage performance parameter value corresponding to an access request instruction in response to the access request instruction, and deleting a corresponding token quantity from a token bucket of a storage system according to the storage performance parameter value. Wherein the tokens in the token bucket are uniformly filled at preset time intervals based on the maximum token quantity; the maximum token quantity is determined according to the storage performance upper limit of the storage system in a service quality period. By adopting the method, the reasonability of token filling in the token bucket of the storage system can be improved.