16results about How to "Improve service level" patented technology

The invention discloses a network information consultation system and method. The system comprises an information consultation platform and a data storage module set on a webpage, and a control module. The consultation platform comprises a consultation instruction, a judgment instruction, a selection instruction, a primary information negotiation instruction, a signature instruction, a payment confirmation instruction, a formal negotiation room entering instruction and an evaluation instruction. The data storage module comprises a standard information module, a data update module, a storage module and an evaluation module. The control module comprises a judgment module, a display control module, a bargain control module, a signature control module, a payment control module, a password payment module and the evaluation module. The consultation method comprises a selection step, an individual consultation entering step, a bargain step, a signature step, a charging payment step, a payment password step, a formal consultation step and an evaluation step. The information consultation method and the consultation system are organically combined together, and a concise and transparent network information consultation platform is provided for a customer.

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 application provides a travel time prediction method fusing uncertainty modeling, and belongs to the field of intelligent traffic and navigation. The method first acquires static road network features, dynamic traffic features and road section external features, constructs a road network directed graph and defines a route R, finds feature values corresponding to road sections in R, constructs initial node embedding and initial edge embedding, and constructs a prediction model; after preprocessing of initial values, each layer of graph convolution network updates node embedding and edge embedding through modeling of interaction between nodes and edges, and finally obtains iterative node embedding and edge embedding; position encoding is performed on the processed route to construct a matrix PE; route embedding is obtained by adding the final node embedding and PE, multi-head attention is performed on the route embedding, and then average pooling is performed to obtain arrival time representation; uncertainty quantization and correction are performed on the arrival time representation to obtain predicted arrival time and upper and lower bounds. The application quantizes the uncertainty of the time prediction result.

This invention discloses a SKU shelving method and storage medium for a mobile robot warehousing system. The method includes: acquiring data information from the mobile robot warehousing system; constructing an SKU shelving decision model based on the acquired data information; constructing a calculation method for an SKU shelving strategy based on the data information and the SKU shelving decision model; calculating the SKU shelving result of the mobile robot warehousing system according to the calculation method, and implementing the method. The SKU shelving method strategy for a mobile robot warehousing system provided by this invention proposes an SKU shelving method from a globally optimal perspective. Compared with existing technologies, it can more rationally allocate shelving locations for SKUs, reduce the number of shelves required to complete all orders, and improve picking efficiency. This invention has good practicality and operability, and the calculation method is simple, providing a new and efficient strategy for solving the SKU shelving problem in mobile robot warehousing systems.

The application discloses a road pavement inspection and maintenance method and a related device. The method comprises the following steps: acquiring multiple frames of road images of a to-be-detected road; dividing the to-be-detected road into multiple regions according to the multiple frames of road images; selecting a detection point from each region of the multiple regions to obtain a target detection point corresponding to each region; marking each region of the multiple regions according to the target detection point corresponding to each region to obtain multiple pavement type identifiers; and determining a pavement maintenance scheme corresponding to each region according to the pavement type identifiers. The application is beneficial to improving the use performance and service level of the road.

This invention relates to the field of logistics route optimization technology, specifically a method for optimizing collaborative routes among multiple couriers in urban last-mile logistics. The method includes: receiving and integrating a set of real-time delivery tasks and a set of courier statuses uploaded from station terminal equipment; using an improved clustering algorithm to initially divide the real-time delivery task set into task clusters corresponding to the number of couriers and associating them with initial responsible couriers; planning preliminary travel routes for each task cluster that start from the courier's real-time location, serve all task points, and meet constraints, generating a preliminary route plan set; calculating the boundary task exchange benefits between task clusters, and performing global collaborative optimization of the preliminary route plan set through cross-cluster task redistribution iterative processing to generate a final collaborative route plan. This method can improve the coordination and efficiency of urban last-mile logistics delivery and optimize resource allocation.

The invention discloses an intelligent calculation method for road subgrade pavement deflection data, and relates to the technical field of road engineering. Comprising the steps that a multi-model fusion intelligent calculation framework is constructed, reinforcement learning and deep learning algorithms are integrated, a desktop application program capable of being independently executed is packaged, intelligent processing of deflection detection data collection is achieved, and the intelligent processing comprises deflection value temperature correction calculation and deflection representative value calculation. According to the method, efficient calculation is carried out on the actually measured roadbed pavement deflection value, the calculation efficiency of the deflection value is remarkably improved by establishing a calculation model and optimizing a calculation process and an algorithm architecture, and the order of magnitude of the calculation efficiency is improved; according to the method, a traditional calculation mode is innovated, and a rapid and accurate solution is provided for roadbed and pavement detection.

The present application relates to the technical field of Internet of Things, and in particular to an Internet of Things card management platform, comprising: a data calculation module configured to generate a plurality of device network quality data according to real-time network parameters corresponding to a plurality of operator networks respectively; a map generation module configured to gather the plurality of device network quality data and generate a regional network quality map; a strategy management module configured to perform network state prediction and global optimization analysis based on the regional network quality map and generate a target switching strategy; and an output execution module configured to issue the target switching strategy to a target terminal, so that the target terminal performs a switching operation of an operator network based on the target switching strategy, thereby effectively solving the problem that the existing Internet of Things card management cannot guarantee the connection continuity and service quality during the cross-network movement of a device.

The invention provides a power customer service risk processing method and device, equipment and a medium, and relates to the field of information processing.The method comprises the steps that a current dialogue text stream is collected, and a customer service staff text stream and a power customer text stream are separated from the current dialogue text stream; defining an analyzed limited text range for the client text flow, and performing sentiment analysis on the client text flow in the limited text range through a pre-trained sentiment analysis model to obtain a negative sentiment type and a negative sentiment intensity value of the client; processing the negative emotion type and the negative emotion intensity value to obtain a risk value; if the risk value is greater than or equal to a preset threshold value, predicting the probability of occurrence of the target negative behavior of the power customer based on the current dialogue text stream and the historical service record of the power customer; and according to the negative emotion type, the negative emotion intensity value, the type of the target negative behavior and the occurrence probability of the target negative behavior, generating and displaying response skill suggestions recommended to the customer service staff.

This application discloses a method, apparatus, equipment, medium, and product for evaluating the effectiveness of transportation and tourism services, relating to the field of intelligent transportation technology. The method includes: acquiring data on first transportation stations, first tourist attractions, and first road network in a target area under a first scenario, and data on second transportation stations, second tourist attractions, and second road network in a second scenario; determining the number of first transportation stations, the proportion of first transfer stations, and a first accessibility index based on the data under the first scenario, and determining the number of second transportation stations, the proportion of second transfer stations, and a second accessibility index based on the data under the second scenario; and determining the effectiveness evaluation result based on the number of first transportation stations, the proportion of first transfer stations, the number of second transportation stations, the proportion of second transfer stations, the first accessibility index, and the second accessibility index. This method can achieve accurate evaluation of the effectiveness of transportation and tourism services.

The utility model discloses a display screen, in particular to an electronic light multifunctional display screen, which comprises a first section bar and a plurality of light-emitting units, each light-emitting unit is arranged on the first section bar, each light-emitting unit comprises a second section bar, each second section bar is connected with the first section bar in an embedded and clamped manner, and two ends of each second section bar are fixedly connected with end plates. The upper side of the second profile is fixedly connected with light-transmitting glass, and a lamp panel is embedded in the inner wall of the second profile. The technical scheme of the utility model aims to quickly and accurately inform passengers of the station information, save time and further improve the travel efficiency of the passengers.

The application discloses a method for determining an ionosphere anomaly monitoring threshold of a Beidou satellite-based augmentation system, comprising the following steps: acquiring ionosphere piercing point vertical delay values and position information thereof; generating an ionosphere data set; acquiring ionosphere piercing point delay values in a fitting domain around a to-be-fitted point in the ionosphere data set, and calculating at least one monitoring statistic; and determining a monitoring statistic threshold according to a MaxEnt threshold algorithm and the monitoring statistic. K The application is directed to the ionosphere environment characteristics of a service area of the Beidou satellite-based augmentation system, the ionosphere state is monitored through ionosphere anomaly monitoring statistics, and the ionosphere anomaly monitoring threshold is re-analyzed and calculated, so that the Beidou satellite-based augmentation system service integrity under ionosphere anomaly conditions can be ensured, and meanwhile, a higher satellite-based augmentation system user service level can be provided under a quiet ionosphere condition.

The application provides a power user power consumption behavior portrait method considering power consumption sensitivity, and belongs to the technical field of industrial data processing. The method solves the problem that in most power user portrait methods, sensitive loads and basic loads influenced by other factors are mixed for analysis, which makes the portrait result not fine enough and unable to accurately grasp the power consumption behavior characteristics of users. The method comprises the following steps: obtaining a power load data set, drawing a load curve, and performing preliminary clustering; labeling the preliminary clustering cluster; inputting the preliminary clustered load data set into an STL model for decomposition and division into basic loads and sensitive loads; performing clustering analysis on the basic loads and the sensitive loads respectively, defining a basic load label library and an external factor sensitive load label library according to the clustering results; and labeling each user with two types of labels according to the basic load label library and the external factor sensitive load label library, combining the labels of the initial clustering results, and generating a precise portrait of the power user.

The utility model relates to the technical field of vehicles, in particular to a vehicle detention reminding device with a shading structure, which comprises a relay base, a photoelectric sensor is connected onto the relay base, the photoelectric sensor provides a leading signal and is used for detecting whether a vehicle is detented, a shading plate is connected to the front side of the relay base, and an electric wire is connected to the lower side of the relay base. The lower part of the calling machine is connected with a control module, the upper part of the control module is provided with a delayer, the upper side of the calling machine is connected with a display screen, and the lower side of the calling machine is connected with a mounting seat. Through cooperative work of the control module and the delayer, intelligent control over the calling machine and the display screen is achieved, the normal passing state and the abnormal detention state are effectively distinguished, the waiting time of a driver and passengers is remarkably shortened, the response accuracy and stability of equipment are improved, and the service life of the equipment is prolonged. In addition, pertinence and practicability of information prompting are enhanced, and traffic management efficiency and service level are improved.

The application provides a communication connection method and device and electronic equipment, the method comprises the following steps: initiating a communication request to a client based on a target service type; determining an evaluation parameter of each customer service in a corresponding customer service group according to a first priority coefficient of the corresponding customer service group and a strategy parameter of each customer service in the customer service group, wherein the strategy parameter of each customer service is obtained according to a routing strategy of the corresponding customer service group of the target service type; determining a communication priority of each customer service in the corresponding customer service group of the target service type according to the evaluation parameter of each customer service; and establishing a communication connection between the client and a customer service device corresponding to a target customer service according to the communication priority. The application can effectively improve the adverse effects such as low service level caused by uneven distribution of customer lists.

The invention provides a high-speed rail train seat allocation optimization method and device, and the method comprises the steps: obtaining the seat occupation information of a target high-speed rail train at the current moment in response to the received seat request information sent by a passenger, constructing a seat matrix representing the corresponding occupancy state of the seats of the target high-speed train distributed in each riding interval at the current moment; respectively inputting the seat matrix and the seat request information into a seat distribution model based on Markov decision so as to make a decision by using a decision sub-model corresponding to each riding interval in the seat distribution model and output a local action decision result of the riding interval; and the seat distribution model updates the seat matrix based on the local action decision result and the seat request information to obtain an updated seat matrix so as to determine a seat distribution result. Through the method, the passenger seat utilization rate and the passenger satisfaction rate of the high-speed rail train are improved, and the comprehensiveness and adaptability of seat distribution of the high-speed rail train are further improved.