17 results about "Passenger satisfaction" patented technology

The invention relates to the technical field of intelligent fitness bus stations, and particularly discloses a sports equipment matching recommendation system for an intelligent fitness bus station. According to the method, the duration constraint influence factor is calculated according to the predicted waiting duration of the target passenger and the effective exercise duration of each to-be-analyzed sports apparatus, and the time limit of the passenger staying at the bus station is fully considered, so that the recommended apparatus can achieve a certain exercise effect within the time range acceptable by the passenger, and the user experience is improved. The recommendation feasibility and practicability are improved, the final matching recommendation degree is calculated according to the basic matching recommendation degree and the duration constraint influence factor, the recommendation result is further optimized on the basis of comprehensively considering the physiological features, the exercise preference and the time constraint, the finally recommended exercise equipment is made to better meet the actual requirements and conditions of passengers, and the user experience is improved. Sports equipment selection more conforming to the overall condition is provided for passengers, the satisfaction degree of the passengers on recommendation results is improved, and the willingness of the passengers to use the sports equipment of the intelligent fitness bus station is enhanced.

The invention discloses a rail transit ticket price optimization method and system based on big data, and relates to the technical field of intelligent optimization, and the method comprises the following steps: carrying out the first matching according to operation data and a distance radiation condition, carrying out the second matching according to the operation data and a date radiation condition, and calculating overlapping passenger flow resources and inverse difference passenger flow resources; and performing first optimization, calculating the total profit after the first optimization, and performing second optimization on the ticket price of the station after the first optimization according to the profit expectation. According to the invention, the ticket price is optimized, the passenger flow is distributed more reasonably, the congestion in peak hours is reduced, the utilization rate of trains is improved, the ticket price is optimized, the ticket price income is improved, the satisfaction degree of passengers is improved, the ticket price is flexibly adjusted according to different dates, time and passenger flow changes, the market change and the passenger demand are better adapted, and the market competitiveness is improved. The ticket price optimization method based on the big data significantly improves the operation efficiency and economic benefits of rail transit in practical application, and can provide higher-quality services for passengers at the same time.

To provide a technique of increasing a passenger satisfaction degree in a service for distributing content to passengers of vehicles.SOLUTION: A control unit of an information processing device acquires a passage time at which a vehicle actually passes a prescribed halfway point of a scheduled travel route, and calculates a scheduled arrival time at which the vehicle is predicted to arrive at a destination of the scheduled travel route in accordance with the acquired passage time. The control unit of the information processing device calculates a surplus time length representing the difference between the scheduled arrival time and a scheduled content distribution end time if the scheduled content distribution end time is earlier than the calculated scheduled arrival time. The control unit of the information processing device outputs information about the calculated surplus time length and proposal information including information for encouraging a delay of the scheduled content distribution end time.SELECTED DRAWING: Figure 5

A kind of urban rail transit line transport capacity precision regulation and control method, comprising: S100. Obtain urban rail transit line transfer passenger data, according to the transfer passenger data, section passenger flow information is obtained;S200. Obtain car fixed number information, according to the section passenger flow information and car fixed number information, the section congestion degree of urban rail transit line is obtained, according to the section congestion degree, transfer passenger flow density information is obtained;S300. Establish periodic train diagram evaluation mechanism, according to the transfer passenger flow density information, optimize rail transit line train diagram;S400. Real-time update the transfer passenger flow density information, the train diagram iterative optimization is carried out, set the iteration number or other iteration termination condition, obtain the final rail transit line train diagram.The method disclosed in the application considers the distribution of transport capacity in transfer station with different transfer passenger flow density, can save passenger travel time, improve passenger satisfaction, and reasonably allocate transport capacity.

The invention discloses an intelligent passenger satisfaction prediction method and system and a storage medium, and belongs to the technical field of data processing. The method comprises the following steps: collecting multi-source data of a target passenger and an associated group thereof; based on the multi-source data, respectively generating a substantial experience feature representation of the target passenger and a psychological expectation feature representation of multiple dimensions; performing dynamic fusion on the essential experience feature representation and the psychological expectation feature representation of the multiple dimensions through a difference perception fusion mechanism to generate a comprehensive feature representation; and based on the comprehensive feature representation, outputting a satisfaction prediction value through a machine learning model. According to the method, accurate prediction of the passenger satisfaction is realized by fusing the multi-source data and dynamically quantifying the expected difference.

The invention discloses a dynamic aircraft stand redistribution method based on a passenger gathering degree and an electronic terminal, and the method comprises the steps: obtaining aircraft stand information and initial flight plan information of an airport, and obtaining flight delay information; according to the flight initial plan information, according to a flight first-arrival first-service rule, carrying out machine position distribution, and generating a machine position pre-distribution scheme; calculating a single-flight passenger gathering probability at a boarding gate; and setting parameters of a taboo search algorithm, taking the minimum passenger adjustment loss time after the aircraft position changes as a target function, inputting the aircraft position pre-distribution scheme and the flight delay information into the taboo search algorithm for solving, and generating an aircraft position redistribution scheme. According to the invention, extra adjustment time of passengers caused by change of the boarding gate can be reduced to ensure the satisfaction of the passengers; the tabu length is adjusted to be a variable which changes along with the frequency of a tabu object, and a neighborhood moving method is finely divided, so that the solving speed is improved, and rapid optimization is realized.

A system and method for individualized airline passenger disembarkment integrates with Passenger Service Systems (PSS) and Airport Operational Databases (AODB) using IATA New Distribution Capability (NDC) standards for real-time data exchange. Passengers book priority disembarkment options during reservations, with availability determined via priority queues in distributed software modules interacting with cloud-based hardware to allocate limited slots efficiently. Upon detecting delays, the system identifies at-risk passengers for missed connections by computing gate-to-gate travel times using graph data structures, assigns priority disembarkment passes (physical or virtual) with verification elements such as QR codes, NFC, or RFID, and deactivates passes post-disembarkment via geo-fencing or hash-based structures. This reduces airline costs, enhances operational efficiency by minimizing latency and optimizing resources, and complies with aviation regulations across multiple jurisdictions while improving passenger satisfaction.

In order to improve passenger satisfaction with a transportation service and to provide an operation plan creation means capable of reducing operating costs for a transportation service provider, an operation plan creation device comprises: a transportation leg network generation unit that generates transportation leg network information that defines each transportation leg of the transportation service; a cancellation determination unit that generates transportation leg cancellation possibility information that indicates whether or not cancellation of each transportation leg of the transportation service is possible; a travel route candidate determination unit that generates travel route candidate information that indicates a travel route candidate for each travel plan in passenger travel plan information; a people flow prediction unit that generates people flow prediction information that indicates a predicted people flow in the transportation service; and an operation plan generation unit that generates new operation plan information in which certain transportation legs of the transportation service are eliminated.

The invention discloses an aviation service recommendation method. The method comprises the steps of obtaining user behavior data of a to-be-tripped passenger and preprocessing the user behavior data; wherein the user behavior data comprises personal attribute data, flight travel data and service purchase records; inputting the preprocessed user behavior data into a pre-trained service recommendation model, and outputting a passenger feature tag of the to-be-tripped passenger; generating a service recommendation strategy based on the passenger feature tag; according to the service recommendation strategy, carrying out aviation service recommendation on the to-be-tripped passenger; according to the method, the requirements and preferences of the passengers can be more accurately captured, and the accuracy of aviation service recommendation is improved, so that the service quality and the satisfaction degree of the passengers are improved.

The embodiment of the invention provides a bullet train-based along-the-way wind and light video playing method and related equipment, a bullet train comprises a plurality of bullet train carriages, each bullet train carriage is provided with at least one public display screen and a plurality of passenger seats and passenger interaction terminals, and the method comprises the following steps: acquiring real-time geographic position information of the bullet train in the running process, the real-time geographical location information is matched with a plurality of sceneries along the way; when the real-time geographical location information is matched with the target scenery along the way, controlling a public display screen and a passenger interaction terminal to play a scenery introduction video; in response to a reading request of the target passenger interaction terminal for the target interest point, playing detailed introduction data of the target interest point in the target passenger interaction terminal; and determining the remaining time along the way based on the playing end time, further obtaining the compressed introduction video, and playing the compressed introduction video on the target passenger interaction terminal after the detailed introduction data is played on the target passenger interaction terminal, thereby remarkably improving the riding satisfaction of the passenger.

An elevator group control optimization scheduling method based on evolutionary scheduling domain and nonlinear coupled objectives includes the following steps: S1: Operation status perception and basic data construction; S2: Evolutionary scheduling domain construction; S3: Risk perception nonlinear scheduling objective construction; S4: AI large model parameter generation and interpretation; S5: Group control elevator dispatch decision and execution; S6: Iterative execution. This invention suppresses the tail of waiting time distribution through nonlinear coupled objectives and CVaR long-tail penalty, significantly reducing waiting time and improving passenger satisfaction and comfort; it balances efficiency, energy consumption, and fairness through nonlinear coupled objectives, and constrains adaptive adjustment to ensure safety and stability; it uses a large language model to parse natural language rules, emergency instructions, and passenger preferences, quickly integrating manager intentions into scheduling decisions to achieve interpretable and flexible strategy adjustments; the evolutionary scheduling domain enables smooth transitions between different traffic modes, avoiding the performance drop caused by traditional hard switching between "up" and "down".

The invention discloses an intelligent bus timetable dynamic generation method and system based on multi-source data, and belongs to the technical field of intelligent city buses, and the method comprises the following steps: 1, analyzing a city bus multi-line data file, and obtaining a data set of line station names, longitudes and latitudes, historical passenger flow data, initial departure time and legal departure frequency; 2, time periods are dynamically divided based on a dynamic time period division algorithm and passenger flow, an optimization model is constructed by adopting three timetable generation principles and four departure frequency calculation methods, and an optimized departure time sequence of each station is generated based on the initial departure time and the dynamic optimization model; 3, adjusting the departure-arrival time of multiple routes at the transfer station through a transfer cooperation algorithm; and step 4, outputting the optimized departure time table and a visual output result. The problem of low efficiency of traditional scheduling can be solved, the operation cost is reduced, and the satisfaction degree of passengers is improved.

The invention belongs to the technical field of airport natural person unique ID identification, and discloses an airport natural person unique ID method and system based on data braiding. The method comprises the following steps: collecting certificate information and basic information of a natural person; uniqueness verification is carried out through key fields of the natural person certificate information and the basic information, and whether the same natural person exists or not is checked; generating a persistent unique ID through the UUID, and distributing the unique ID for the merged natural persons; natural person attributes are bound, and a correlation knowledge graph is established through the natural person unique ID and the natural person information. According to the invention, data verification and encryption are carried out on the unique ID of the natural person, and the travel efficiency is improved through flow optimization and resource cooperation, so that the travel of passengers is more convenient and efficient. The airport service is continuously optimized and improved by means of data weaving and a natural person unique ID technology, and the travel satisfaction degree of passengers is improved.

The invention provides a passenger demand driven train operation adjustment method and system, and belongs to the technical field of train operation scheduling. A train operation adjustment model is constructed, and a micro train timetable is generated; generating a passenger path selection set by adopting a shortest path algorithm: constructing a passenger discrete selection model, obtaining passenger travel behavior change characteristics caused by train timetable changes, and describing distribution of passengers on train services; integrating the train operation adjustment model and the passenger discrete selection model into a mixed integer nonlinear model; and a transformation and linearization method is introduced to linearize nonlinear terms of the mixed integer nonlinear model, a mixed integer linear programming model is formed and solved, and a final adjusted train operation scheme is obtained. The method is used for adjusting the train operation plan under the interference condition, when the original train operation plan cannot be executed, the train operation plan influenced by interval blocking can be rapidly and automatically adjusted, and meanwhile the passenger satisfaction degree and the enterprise operation benefit can be maximized.

This invention discloses a cross-domain preference prediction method for cruise services based on transfer learning, belonging to the field of smart tourism and personalized recommendation technology. The method includes: constructing a cross-domain data preprocessing and feature enhancement module, achieving feature space alignment and semantic enhancement through Z-score normalization, dimensional expansion, and an autoencoder; constructing a similarity matrix by fusing category, geospatial, and label semantic information, and generating pseudo-preference labels for cruise services based on the similarity matrix and a masking filtering mechanism; constructing and pre-training a multilayer perceptron model, freezing and scaling some low-level parameters, jointly training a domain adaptation module and a prediction head, constructing an adapted target model, and outputting cruise preference prediction results. This invention solves the problems of feature dimension mismatch and scarce labeled data in cruise scenarios, providing reliable preference prediction results for personalized cruise service recommendations, and is of great significance for improving passenger satisfaction and optimizing service resource allocation.

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.

The invention relates to the technical field of public transport service evaluation, in particular to a demand response type public transport passenger satisfaction evaluation method based on a structural equation model, which comprises the following steps: proposing a research hypothesis based on the characteristics of a response type public transport, and obtaining satisfaction survey data based on the research hypothesis; calculating a cloned Bach coefficient according to the preprocessed data to verify reliability, and verifying structural validity of the preprocessed data through a KMO value and Bartlet sphere test; inputting the preprocessed data into a structural equation model on the basis of a core latent variable and a hypothetical path, performing parameter estimation by adopting a maximum likelihood estimation method, performing model fitting inspection on the basis of a model output result to obtain a standardized path coefficient and saliency, establishing a path saliency matrix table, and calculating a path saliency matrix table; and performing effect analysis according to the path significance matrix table to obtain a total effect sequence of each core latent variable on the passenger satisfaction and key influence factors. According to the invention, the collaboration between the service quality and the passenger satisfaction is improved.