200 results about "Service quality" patented technology

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 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 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 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 discloses a method, a system, equipment and a medium for energy management and economic dispatching optimization of an optical storage and charging system, and relates to the technical field of optical storage and charging. The comprehensive operation state model represents an operation rule and an economic index of the optical storage and charging system in a future scheduling period; based on the comprehensive operation state model, solving a multi-objective optimization problem to obtain a Pareto optimal solution set considering economy, environmental protection property and service quality; and selecting an optimal scheduling strategy from the Pareto optimal solution set by adopting a multi-agent equilibrium game mechanism so as to determine a final energy management and economic scheduling scheme. According to the method, the problems of difficulty in multi-target coordination, insufficient electricity price response capability and user behavior modeling simplification in the existing energy management technology of the optical storage and charging system are solved, so that the overall benefit of the system is better, the method can adapt to various market mechanisms and different meteorological conditions, and the application scene is wide.

The invention provides an artificial intelligence-driven bus real-time scheduling and path optimization method. The artificial intelligence-driven bus real-time scheduling and path optimization method comprises the following steps: S1, multi-source data acquisition; s2, data preprocessing; s3, constructing an artificial intelligence scheduling optimization model; s4, generating a real-time scheduling decision; s5, vehicle execution and data feedback; and S6, path dynamic optimization. Through deep fusion of an artificial intelligence technology and public transportation services, the precision, dynamic and intelligent scheduling decision is realized, and finally the operation efficiency and service quality of a public transportation system are improved.

The invention discloses an urban rail transit peak period train departure interval optimization method based on multi-line cooperative scheduling, and relates to the technical field of rail transit operation management. The method comprises the following steps: firstly, constructing a network topology containing key transfer stations and a passenger flow OD matrix; establishing a passenger travel space-time network model to accurately describe a transfer waiting process; further constructing an optimization model with the goal of minimizing the total cost of the system, wherein the model comprehensively considers the passenger waiting time, the in-vehicle crowding degree, the operation cost and the transfer collaboration degree; and finally, designing a mixed intelligent algorithm combining Lagrangian relaxation and a meta-heuristic algorithm for solving, and generating a multi-line cooperative departure interval scheme. According to the method, the limitation of single-line independent scheduling is broken through, resource allocation can be optimized from the overall perspective of a line network, the total travel time of passengers and transfer station congestion are effectively reduced, and the overall transportation efficiency and service quality of a rail transit system in peak periods are remarkably improved.

The invention relates to the technical field of artificial intelligence, old-age service and quality monitoring, in particular to an artificial intelligence-driven precise old-age service matching and quality monitoring system, which comprises a service demand analysis module, a service resource matching module, a multi-modal data acquisition module, a topological data analysis module, a service quality monitoring module and a user interaction module, the physical health data and daily activity information of the old people are analyzed by adopting a deep learning technology, and personalized service demand evaluation is realized; intelligent scheduling of service resources is carried out based on a multi-agent system; the service quality manifold is constructed through the topological data analysis technology, the topological distance between the real-time service data and the standard service quality manifold is calculated, whole-process monitoring and early warning of the service quality are achieved, the problems that in existing old-age care services, demand evaluation is not accurate, the resource configuration efficiency is low, and service quality monitoring is not comprehensive are solved, and the service quality monitoring efficiency is improved. The service matching accuracy and the resource utilization efficiency are remarkably improved, and the service abnormity is found in advance and accurately positioned.

The invention discloses a power enterprise agent platform based on a large language model, and relates to the technical field of artificial intelligence and power systems, and the platform comprises a data governance module, a model deployment module, a platform building module and an application development module. Through the technical path of large model enabling, agent landing and electric power scene deep adaptation, the core pain points of a traditional electric power enterprise in the aspects of efficiency, safety, data utilization, service quality and the like are systematically solved, four dimensions of intelligent operation and maintenance, data-driven decision, user experience upgrading and cost optimization are covered, and the method has the advantages of being high in practicability and easy to popularize. The digital competitiveness of a power enterprise is remarkably improved, and the requirements of a novel power system for high automation, high robustness and agile response are met; the intelligent agent and the workflow are effectively combined together, a single automation mode is replaced, complex task processing time is shortened, conventional task efficiency is improved, and flexibility and execution stability are balanced.

The invention discloses a customized bus evaluation method and device and a storage medium, and relates to the technical field of public transportation. The evaluation method of the customized bus comprises the following steps: acquiring first vehicle-road interaction data of the customized bus, wherein the first vehicle-road interaction data is interaction data between a vehicle-mounted communication unit and a road side communication unit of the customized bus; processing the first vehicle-road interaction data to obtain an evaluation value corresponding to an evaluation index under at least one evaluation dimension, the at least one evaluation dimension at least comprising a vehicle-road cooperation service level dimension, and the vehicle-road cooperation service level dimension being used for evaluating the service effect of the customized bus in the vehicle-road cooperation environment; and determining an evaluation score of the customized bus by using the evaluation value corresponding to the evaluation index, the evaluation score being used for indicating the service quality of the customized bus. According to the embodiment of the invention, the reliability of customized bus evaluation can be improved.

The present disclosure provides a communication processing method, device, equipment, chip and medium, wherein the communication processing method comprises: performing single radio voice call continuity (SRVCC) switching, wherein the SRVCC switching is used to maintain a service; obtaining first data information of the service in a case where the SRVCC switching is not completed; determining second data information according to the first data information; and playing the second data information. Thus, the data information received before the SRVCC switching is completed can be processed optimally, and the data information obtained by the optimal processing can be played in time, thereby effectively ensuring the continuity of the service and improving the service quality.

This invention discloses a method for ranking reserve projects for new power grid infrastructure, comprising: constructing a ranking indicator system from five dimensions: power grid development, security and supply, service quality, efficiency and effectiveness, and green and low-carbon development; collecting raw indicator data and distinguishing indicator types; obtaining objective weights for the indicators through a combination of two objective weighting methods; constructing a matrix by standardization transformation and weight combination; calculating relative proximity to form an objective ranking; subsequently integrating expert rankings; obtaining a subjective consensus ranking by constructing a pairwise preference matrix and an integer programming model; and finally, calculating standardized scores and weighted fusion of the subjective and objective ranking results using a weighted aggregation method to determine the ranking position of the reserve projects. This method balances data objectivity and expert experience, covers the core requirements of projects from multiple dimensions, has a rigorous ranking logic, and effectively improves the scientificity and accuracy of ranking reserve projects for new power grid infrastructure.

The invention relates to an urban rail transit multi-target transfer connection optimization method and system. The method comprises the following steps: S1, obtaining a line network working diagram and passenger flow data, determining a key transfer train pair according to the line network working diagram and the passenger flow data, and constructing a connection influence factor evaluation index according to the key transfer train pair; and S2, constructing a multi-objective optimization model according to the connection influence factor evaluation indexes. And S3, solving the multi-objective optimization model in combination with an operation scale adjustment mechanism so as to output a preferred adjustment scheme. And S4, under the constraint that the time from the tail end station to the departure station of the train is not changed, different operation levels are used for the transfer train in sections before and after the transfer station and the operation time is adjusted by adopting an optimal adjustment scheme, so that a transfer station connection optimization suggestion scheme is obtained. According to the method, the key transfer station connection efficiency can be improved, the passenger transfer cost is reduced, the overall line network operation efficiency and service quality are improved, and the urban rail transit network is powerfully promoted to develop towards the seamless and efficient direction.

The invention relates to a service processing method and device, electronic equipment and a storage medium, and the method comprises the steps: determining the regulation priority of each business plug-in under the condition that a current load state meets a set regulation triggering condition in response to a service request, and determining a target regulation strategy according to the current load state; performing regulation and control operation on the selected business plug-in according to the target regulation and control strategy, and performing resource capacity expansion according to the load change condition of the business system; and adjusting the target regulation and control strategy based on the system load state after the resource capacity expansion, and processing the service request by using the adjusted system resource. According to the method, accurate and intelligent regulation and control operation and resource expansion collaborative optimization processing are performed on a service system, so that stable operation of core services is ensured, efficient utilization of resources and elastic adaptation of system resources are realized, and therefore, under high-fluctuation and high-real-time scenes such as financial quotation, the service quality of the system is improved. Triple goals of guaranteeing the extreme user experience, maximizing the resource utilization rate and reducing the operation and maintenance complexity are synchronously achieved.

A communication control method and a node that allow a user equipment to perform handover to an optimal cell according to a service type are provided. The communication control method includes receiving, at a node, a first message including network slice information related to a network slice and / or service quality information indicating service quality from a core network apparatus. The communication control method includes receiving, at the node, a measurement report from a user equipment. The communication control method further includes determining, at the node, a threshold value to be used for handover decision, based on the network slice information and / or the service quality information, in response to reception of the measurement report. The communication control method further includes deciding, at the node, whether to handover the user equipment, based on a received quality value indicating received quality included in the measurement report and the threshold value.

The invention relates to improving the attention of a person driving a vehicle (20) to road traffic. To improve attention, the invention provides for degrading the service quality of a communication connection (14) when it is detected (12) that the person's attention falls below a threshold that depends on road traffic.

The application discloses a kind of integrated multi-platform data distribution and control method of collection, comprising: constructing order field mapping rule library, the order data of each catering take-out platform is converted into the order data of uniform standard format;Using order decoding module, the order data of standard format is decoded and format conversion, print order and the execution state and time progress of each meal preparation task are monitored in real time;Large batch order is identified, and large batch order is handled by single order;The delivery status of order is updated in real time, and the latest delivery information is pushed to customer;Based on order delivery data and weather data, predict the overtime risk and overtime phase of order;Judge whether merchant agrees to return or order, and merchant confirmation information is synchronized to catering take-out platform.The application improves the intelligent level of order processing, delivery task allocation and delivery monitoring, significantly improves the operation efficiency and service quality of take-out platform, and optimizes the dining experience of customer.

The invention provides a scheduling method for dual-objective optimization of a multi-agent flow shop under time-of-use electricity price, and relates to the technical field of intelligent manufacturing and production scheduling. According to the method, unified modeling is carried out on the total power cost TEC and the total customer completion time TCTA, and a dual-target mixed integer programming model is constructed; a double-node decision tree structure is constructed, and synchronous processing of task sorting and processing time interval distribution is achieved; analyzing the structural characteristics of the multi-agent flow shop under the constraint of time-of-use electricity price, designing a series of inequality constraints and multiple pruning rules, and compressing a search space on the premise of ensuring the integrity of a feasible solution; the method comprises the following steps of: performing dual-objective cooperative solution, embedding a branch and bound algorithm into an improved epsilon-constraint framework to perform iterative solution, accurately obtaining a Pareto frontier, and providing multiple optimal scheduling schemes balanced between cost and service quality for decision makers. According to the method, dual decisions of task sorting and cycle allocation can be realized, and the problems of decision model splitting, low solving algorithm efficiency and the like are solved.

The invention discloses an Internet of Vehicles service quality determination method and device, a medium and a program product, belongs to the technical field of Internet of Vehicles, and is used for determining the Internet of Vehicles service quality. The method comprises the following steps: acquiring signaling data related to the Internet of Vehicles from transaction detailed record data; determining an Internet of Vehicles service corresponding to the signaling data according to the characteristics of the signaling data; and determining the service quality of the Internet of Vehicles service according to the general index and the target index corresponding to the Internet of Vehicles service.

The invention discloses an intelligent management system applied to cruising taxis to obtain short-distance reloading opportunities, belongs to the technical field of intelligent traffic, and aims to solve the problem of service quality caused by receiving short-distance orders by taxis in transportation junctions. The system automatically identifies and verifies short-distance orders received at a hub station through data acquisition, order identification, point management, reloading opportunity granting and other modules, and grants points to a driver according to multi-dimensional factors such as waiting time and mileage. And the driver can use the obtained credits to exchange the authority of queuing-free access to the reloading channel. According to the invention, multi-source data such as vehicle snapshot, a GPS and a taximeter are fused to carry out order authenticity verification, and an excitation strategy can be dynamically optimized based on operation data. According to the scheme, traditional passive punishment is converted into active excitation, the driver and passenger contradiction is effectively solved, and the taxi operation efficiency and the travel experience of passengers are remarkably improved.

The embodiment of the present application provides a method and device for feasibility evaluation, which introduces at least one of the following information when the control device sends the first information for requesting the execution device to perform the feasibility evaluation on the first network demand information: the reservation demand information of the network resource corresponding to the first network demand information, the information feedback demand information of the network resource corresponding to the first network demand information, and the modification suggestion feedback demand information of the first network demand information. Through the above method, the operator can reserve the required network resource, feed back the network resource of the service demand and provide the change suggestion for the service demand while performing the feasibility evaluation on the service quality, so that the application scenario of the feasibility evaluation is effectively widened, the success rate of the service issuing is further improved, and the service deployment time is reduced.

The application provides a broadband service quality difference identification method, device, equipment and medium, and relates to the technical field of communication. The method comprises the following steps: obtaining user usage data generated by a user using a broadband network; inputting the user usage data into a trained quality difference identification model to obtain a quality difference identification result output by the quality difference identification model; the quality difference identification result is used to indicate a user with a quality difference problem; and the quality difference identification model is trained based on historical quality difference data of a body sense generated by the broadband network after a user uses the broadband network with added preset network loss. The application realizes active evaluation of the broadband service quality level, so as to accurately label each potential quality difference user, and then find problems in advance and timely repair the broadband, thereby improving user experience and stickiness.

The invention relates to a driver departure control method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring driving behavior data of a current driver, determining a driving risk score of the current driver according to the driving behavior data, acquiring passenger evaluation data of the current driver, determining a service quality score of the current driver according to the passenger evaluation data, acquiring historical operation data of the current driver, and determining a service quality score of the current driver according to the historical operation data; according to the historical operation data, determining a revenue efficiency score of the current driver, according to the driving risk score, the service quality score and the revenue efficiency score of the current driver, determining a driving strategy of the current driver, the driving strategy including a driving address and driving time, and sending the driving strategy to a terminal corresponding to the current driver. Therefore, the current driver is controlled to leave. By adopting the method, different drivers can be guided to select proper time periods and go to proper places to receive orders, so that the waiting time of the drivers is shortened, and the order receiving success rate of the drivers is improved.

The present application relates to the technical field of teaching quality evaluation, in particular to a service quality dynamic evaluation method for an online teaching platform, comprising: collecting learning behavior data of an online education platform based on the scene of teaching task access; decomposing the obtained learning behavior data in multiple modal scenes to determine the scene feature matrix under each scene; integrating real-time learning behavior data based on the scene feature matrix under each scene to determine the real-time interaction degree of learning behavior, and constructing a learning behavior portrait according to the response time under real-time interaction; calculating the group response time of each teaching task based on the obtained learning behavior portrait, and determining the interaction mode exhibited by the teaching task according to the task completion status corresponding to the teaching task; and based on the interaction mode exhibited by the teaching task, using the isolation forest algorithm for time series regression verification to determine the evaluation score of each user. The efficiency and accuracy of data processing are improved.

The invention relates to the technical field of park asset management, in particular to a park asset operation management system, which comprises a unified asset sensing module for acquiring a real-time operation state, a real-time economic factor and a real-time environment factor of assets; the multi-dimensional digital twin engine is used for calculating the real-time economic dimension and the real-time ESG dimension of the assets in real time based on the data; the predictive simulation module deduces the comprehensive quantitative influence of an operation strategy on economy, ESG and service quality; and the autonomous arrangement engine autonomously selects an optimal strategy and generates a control instruction according to the deduction result and a preset decision rule. The multi-dimensional twin body capable of calculating economic and ESG cost is constructed, and simulation and autonomous arrangement are combined, so that the change of asset operation from passive response to active predictive optimization is realized; and automatic cooperative balance can be achieved among conflicting targets of cost, ESG and service quality.

The application discloses a kind of comprehensive intelligent monitoring decision system and method for overlapping shield tunnel system, system includes information acquisition system, iterative optimization state real-time evaluation system and intelligent maintenance decision system;First, preset model is trained by numerical calculation and other data;Operational measured data trains feedback model, and the output result of the weighted two models obtains tunnel deformation prediction value;Again, experience overlapping tunnel safety evaluation system and iterative optimization evaluation system are established, and the depth correlation of tunnel state, damage, maintenance decision is carried out by correlation degree intelligent real-time analysis, realize tunnel state real-time monitoring-tunnel damage real-time capture-tunnel maintenance decision real-time update, and the intelligent collocation of maintenance measure is carried out, then according to the operation effect feedback iterative optimization prediction model and safety evaluation system.The application realizes the real-time perception, intelligent diagnosis and maintenance of whole life cycle overall service performance of overlapping shield system, and improves the long-term service quality of overlapping shield tunnel structure.

The invention discloses an orthosis adaptive question-answer database construction method based on machine learning, and relates to the technical field of data processing.The method comprises the steps that firstly, an application platform of an orthosis adaptive question-answer database is marked as an orthosis question-answer interaction platform, and the operation process of the orthosis question-answer interaction platform is analyzed; the method comprises the following steps: performing dynamic adjustment on operation parameters of an orthosis question and answer interaction platform, monitoring to obtain question and answer quality data of the orthosis question and answer interaction platform in a preset monitoring period after the operation parameters are adjusted, and analyzing to obtain knowledge update indexes and semantic matching deviation values of the orthosis question and answer interaction platform in each monitoring period; and finally, according to the knowledge updating index and the semantic matching deviation value of the orthosis question and answer interaction platform in each monitoring period, processing to obtain updating information of the orthosis question and answer interaction platform in each monitoring period, and performing parameter configuration management on the orthosis question and answer interaction platform. And the service quality and the operation efficiency of the orthosis adaptive question and answer platform are improved.

The application provides a method, system and device for dynamically evaluating the delivery capacity of a delivery service provider, the method comprising: acquiring external data and delivery data of the delivery service provider in real time, determining multi-dimensional feature data and a historical performance score of the delivery service provider corresponding to a preset prediction time window according to the cumulative external data and the cumulative delivery data; converting the multi-dimensional feature data into a feature vector and inputting the feature vector into a transport capacity prediction model to obtain a transport capacity prediction result corresponding to the delivery service provider, and determining a transport capacity score corresponding to the delivery service provider according to the transport capacity prediction result; and determining a delivery capacity score corresponding to the delivery service provider according to the historical performance score and the transport capacity score. The application can dynamically evaluate the real-time delivery capacity of the delivery service provider, so that the delivery scheduling can be performed according to the real-time delivery capacity of different delivery service providers, the delivery success rate is improved, the delivery demand of users can be better met, the user experience is improved, and the delivery service quality of the delivery service provider is improved.

The invention relates to the technical field of intelligent medical treatment and public health management, and discloses a physical examination integrated management method and system based on intelligent public health, and the method comprises the following steps: firstly constructing a quality control model and a personnel equipment initial capability portrait; then responding to the appointment, and executing quality perception type scheduling according to the portrait and the resource availability; collecting business data and process metadata through a mobile workstation, and dynamically updating a capability portrait according to the business data and the process metadata; then aggregating the data, evaluating the data confidence of the abnormal indexes in combination with the updated portraits, and generating a report with scores; and finally, according to the severity and confidence of the abnormal indexes, differentiated follow-up service pushing is executed. According to the method, capability portraits of operators and equipment are established, process metadata in the physical examination process is collected and dynamically updated, and in the resource scheduling stage, the system can accurately match health requirements of residents with the service quality of service resources in a feedforward mode.