Tourism business management method and system

Abstract

The invention relates to the technical field of text travel service management, and discloses a text travel service management method and system, and the method comprises the steps: obtaining ticket business data and historical ticket booking data of a text travel field, predicting the customer order amount of a prediction day, and generating a text travel configuration scheme; monitoring the entrance and exit passenger flow volume of the travel field in real time to obtain a first passenger flow volume, and if early warning is carried out, generating a first early warning task; acquiring a passenger flow distribution condition according to the information of each sub-region, and if early warning is carried out, generating a second early warning task; and dynamically generating an optimal sightseeing path by combining the sightseeing influence factor of each sub-region. According to the invention, the tourist scale can be pre-estimated in advance to generate a tourist configuration scheme, the entrance and exit passenger flow volume is monitored in real time, whether the overall passenger flow exceeds the carrying capacity is found in time, early warning measures are taken, a corresponding emergency plan is started, and an optimal tourist route is dynamically generated to guide tourists to reasonably plan the tourist travel. And the sightseeing fluency and comfort of the tourists are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cultural tourism business management, and in particular to a cultural tourism business management method and system. Background Art

[0002] With the continuous improvement of people's quality of life, tourism has become one of the main ways for people to relax and relieve stress. During holidays, major cultural and tourism areas are crowded with people, and the passenger carrying capacity of scenic spots faces huge challenges.

[0003] In the traditional cultural tourism operation mode, there is a lack of effective means of passenger flow prediction, and it is impossible to accurately estimate the number of tourists in the scenic area every day and every time period. At present, most of them rely on experience or simple historical data statistics, and it is difficult to combine multi-dimensional factors to make accurate passenger flow predictions; the operation management is poor, and daily operation management is highly dependent on a large amount of manpower input. For example, in ticket sales, ticket checking, and guided tours, manual operations consume a lot of manpower costs, and data cannot be shared and circulated in real time, making it difficult for managers to fully and accurately grasp the operation status of cultural tourism; the cultural tourism area has a large amount of tourist data and business data, but due to the lack of effective data mining and analysis technology, the value of these data has not been fully utilized. There is a lack of a complete passenger flow warning mechanism, and it is impossible to issue warning signals in time according to the real-time changes in passenger flow to remind managers to take corresponding measures. When the passenger flow of cultural and tourist attractions approaches or exceeds the carrying capacity, the emergency plan cannot be quickly activated to carry out effective flow restriction, diversion and guidance work, which is easy to cause safety accidents and threaten the safety of tourists' lives and property. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a cultural tourism business management method to solve the above problems.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a cultural tourism business management method, comprising:

[0008] Obtain ticketing data and historical booking data in the field of culture and tourism, predict the number of customers on the forecast day, obtain the forecast result of the number of customers, and generate the cultural and tourism configuration plan for the day;

[0009] Based on the cultural and tourism configuration plan for the day, the entrance and exit passenger flow of the cultural and tourism field is monitored in real time, a first passenger flow in the cultural and tourism field is calculated, the first passenger flow is compared with the passenger load threshold, and it is determined whether to issue an early warning. If an early warning is issued, a first early warning task is generated;

[0010] Based on the passenger flow situation in the cultural and tourism field, and according to the information of each sub-region divided in the cultural and tourism field, the passenger flow distribution of each sub-region is obtained, and it is determined whether to issue an early warning. If an early warning is issued, a second early warning task is generated;

[0011] Based on the passenger flow distribution of each sub-area and combined with the sightseeing influencing factors of each sub-area, an optimal sightseeing route is dynamically generated for each sub-area.

[0012] As a preferred solution of the cultural tourism business management method of the present invention, obtaining ticketing data and historical ticket booking data in the cultural tourism field includes:

[0013] The ticketing data includes the weather type, date attributes, ticket booking data, and platform hot spot data of the forecast day, and the platform hot spot data includes the platform's search volume, browsing volume, click volume, and discussion volume;

[0014] The historical data includes customer order data of different time periods in the past three years and customer order data under different weather types in each period;

[0015] The weather types are divided into sunny days, cloudy days, rainy days, and snowy days, and the date types are divided into weekdays, weekends, and holidays.

[0016] As a preferred solution of the cultural tourism business management method of the present invention, the customer order volume on the forecast day is forecasted to obtain the customer order volume forecast result, which includes:

[0017] Obtain the weather forecast data for the forecast day, determine the weather type corresponding to the forecast day, and perform data preprocessing to obtain the weather attribute value for the forecast day;

[0018] Obtain the date data of the forecast day, determine the date type of the forecast day, and perform data preprocessing to obtain the date attribute value of the forecast day;

[0019] Select data with the same weather attributes and date attributes in the same time period from historical data, train and verify the customer order prediction model, input the weather attribute values ​​and date attribute values ​​of the prediction day into the model, and obtain the first predicted customer order volume on the prediction day;

[0020] Calculate the forecast comprehensive impact factor based on the actual ticket booking volume before the forecast time, as well as the platform's search volume, page views, clicks, and discussion volume in the past three days;

[0021] Based on the forecast comprehensive impact factor, the first forecast average customer volume on the forecast day is corrected to obtain the second forecast average customer volume on the forecast day.

[0022] As a preferred solution of the cultural tourism business management method of the present invention, generating the first warning task includes:

[0023] According to the set passenger flow monitoring cycle, the entrance and exit passenger flow of the cultural and tourism field is monitored in real time, the total number of entrances and exits in the current passenger flow monitoring cycle and the initial number of people in the previous passenger flow monitoring cycle are obtained, and the first passenger flow in the current passenger flow monitoring cycle is calculated;

[0024] Obtain sub-region environmental data and calculate the maximum number of people that can be accommodated in the cultural and tourism field as the passenger capacity threshold of the cultural and tourism field;

[0025] If the first passenger flow is less than the passenger capacity threshold, no passenger flow warning is performed, and passenger flow monitoring of the next cycle is performed according to the passenger flow monitoring cycle;

[0026] If the first passenger flow is greater than the passenger capacity threshold, a passenger flow warning is performed and a first warning task is generated;

[0027] The first warning task includes calculating the frequency of people leaving the cultural and tourism sector based on the number of people exiting the current passenger flow monitoring cycle to set the frequency of entrance opening, and conducting passenger flow monitoring for the next cycle based on the adjusted passenger flow monitoring cycle.

[0028] As a preferred solution of the cultural tourism business management method of the present invention, obtaining the passenger flow distribution of each sub-area and determining whether to issue an early warning includes:

[0029] The passenger flow monitoring cycle is divided into several warning time periods, and the passenger flow data of each sub-area within the warning time period is obtained through the monitoring points at the entrances and exits of each sub-area. The total number of people in the sub-area is obtained according to the number of people at the entrances and exits of each sub-area, so as to calculate the passenger flow mean of each sub-area;

[0030] Compare the passenger flow mean with the flow threshold, if the passenger flow mean is less than the flow threshold, continue monitoring, if the passenger flow mean is greater than the flow threshold, issue a first-level warning;

[0031] Based on the passenger flow mean, the passenger flow change index is calculated, and combined with the passenger flow in and out frequency of each sub-area, the passenger flow comprehensive index of the sub-area is obtained to determine whether to issue a secondary warning;

[0032] If a second-level warning is carried out, a second warning task is generated for the current sub-area.

[0033] As a preferred solution of the cultural tourism business management method of the present invention, the second warning task includes:

[0034] According to the warning time period of the sub-area, set the opening time of the sub-area entrance, and determine the passenger flow allowed to enter each time the entrance is opened according to the frequency of passenger flow entry and exit;

[0035] Based on the opening time of the sub-area entrance and the passenger flow entering, combined with the number of people waiting at the sub-area entrance, the estimated queue time of the sub-area is obtained and displayed in the sub-area;

[0036] Increase the number of guides and security personnel, and broadcast announcements to guide passenger flow in this sub-area and speed up the flow frequency of passenger flow.

[0037] As a preferred solution of the cultural tourism business management method of the present invention, dynamically generating the optimal tour path for each sub-area includes:

[0038] According to the historical visit volume of each sub-region in the cultural and tourism field in the past month, the sub-regions are ranked and the regional popularity value is obtained as the first visit influencing factor;

[0039] Based on the comprehensive passenger flow index of each sub-region, the passenger flow of the sub-regions is sorted to obtain the regional passenger flow value as the second tourism influencing factor;

[0040] Obtain the distance value between the current sub-area and other sub-areas as the third tour influencing factor;

[0041] Based on the first tour influence factor, the second tour influence factor and the third tour influence factor, an optimal tour route is planned for each area.

[0042] In a second aspect, the present invention provides a cultural tourism business management system, including:

[0043] The collection configuration module is used to obtain ticketing data and historical ticket booking data in the field of culture and tourism, predict the number of customer orders on the forecast day, obtain the forecast result of the number of customer orders, and generate the cultural and tourism configuration plan for the day;

[0044] A first warning module is used to monitor the entrance and exit passenger flow of the cultural and tourism field in real time based on the cultural and tourism configuration plan of the day, calculate the first passenger flow in the cultural and tourism field, compare the first passenger flow with the passenger load threshold, determine whether to issue a warning, and if so, generate a first warning task;

[0045] The second warning module is used to obtain the passenger flow distribution of each sub-area based on the passenger flow in the cultural and tourism field and the information of each sub-area divided in the cultural and tourism field, and determine whether to issue a warning. If a warning is issued, a second warning task is generated;

[0046] The planning module is used to dynamically generate the optimal tour route for each sub-area based on the passenger flow distribution of each sub-area and in combination with the tour influencing factors of each sub-area.

[0047] In a third aspect, the present invention provides an electronic device, comprising:

[0048] Memory and processor;

[0049] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the cultural and tourism business management method are implemented.

[0050] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the cultural and tourism business management method.

[0051] Compared with the prior art, the present invention has the following beneficial effects: the present invention predicts the number of customer orders by acquiring ticketing data and historical ticket booking data in the field of culture and tourism, and can estimate the scale of tourists in advance. Based on the cultural and tourism configuration plan for the day generated thereby, preparations in personnel, materials, facilities, etc. can be made in advance to avoid waste or shortage of resources; real-time monitoring of entrance and exit passenger flow can promptly discover whether the overall cultural and tourism passenger flow exceeds the carrying capacity, so as to quickly take early warning measures, analyze the passenger flow distribution in each region based on the passenger carrying capacity and issue early warnings, realize the refined management of passenger flow in each region within the field of culture and tourism, effectively prevent congestion and safety hazards in local areas, and initiate corresponding emergency plans; dynamically generate the optimal tour route based on the passenger flow distribution in each region and the tour influencing factors, which can guide tourists to reasonably plan their tour itineraries and improve the fluency and comfort of tourists' tours. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0053] Figure 1 The figure is a schematic diagram of the overall process of a cultural tourism business management method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0055] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0056] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0057] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0058] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0059] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0060] Reference Figure 1 , is an embodiment of the present invention, and provides a cultural tourism business management method, comprising:

[0061] S100, obtaining ticketing data and historical ticket booking data in the field of culture and tourism, predicting the number of customer orders on the forecast day, obtaining the forecast result of the number of customer orders, and generating a cultural and tourism configuration plan for the day;

[0062] S200, based on the cultural tourism configuration plan of the day, monitor the entrance and exit passenger flow of the cultural tourism field in real time, calculate the first passenger flow in the cultural tourism field, compare the first passenger flow with the passenger load threshold, determine whether to issue an early warning, and if so, generate a first early warning task;

[0063] S300, based on the passenger flow situation in the cultural and tourism field and according to the information of each sub-region divided in the cultural and tourism field, obtain the passenger flow distribution situation of each sub-region, and determine whether to issue an early warning. If an early warning is issued, generate a second early warning task;

[0064] S400, based on the passenger flow distribution of each sub-area and combined with the tourism influencing factors of each sub-area, dynamically generate the optimal tourism route for each sub-area.

[0065] Specifically, the present invention is applied to the field of culture and tourism, which generally refers to large scenic spots, cultural and creative blocks, indoor cultural and tourism exhibition halls, etc. Multiple monitoring points are set at the entrances and exits of the cultural and tourism field and in each sub-area divided within the cultural and tourism field, and monitoring equipment (such as sensors and other monitoring equipment) are installed to monitor the passenger flow inside and outside the area, which can effectively understand the flow of personnel in the area, adjust and mobilize the cultural and tourism configuration in time, and warn of emergencies, effectively improve the business management level of cultural and tourism, enhance the tourists' experience, and improve the regional management system.

[0066] In a preferred embodiment, obtaining ticketing data and historical ticket booking data in the field of culture and tourism includes:

[0067] Ticketing data includes the weather type, date attributes, booking data, and platform hotspot data of the forecasted day. Platform hotspot data includes the platform's search volume, views, clicks, and discussion volume.

[0068] The historical data includes the customer order data of different time periods in the past three years and the customer order data under different weather types in each period. The different time periods can be various customer order data of different seasons and different holidays in different seasons. The customer order data of all different weather types in this period of different seasons and different holidays in different seasons;

[0069] Among them, weather types are divided into sunny, cloudy, rainy, and snowy days, and date types are divided into weekdays, weekends, and holidays.

[0070] In a preferred embodiment, predicting the customer order volume on the prediction day to obtain the customer order volume prediction result includes:

[0071] Obtain the weather forecast data for the forecast day, determine the weather type corresponding to the forecast day, and perform data preprocessing to obtain the weather attribute value for the forecast day;

[0072] Obtain the date data of the forecast day, determine the date type of the forecast day, and perform data preprocessing to obtain the date attribute value of the forecast day;

[0073] Select data with the same weather attributes and date attributes in the same time period from historical data, train and verify the customer order prediction model, input the weather attribute values ​​and date attribute values ​​of the prediction day into the model, and obtain the first predicted customer order volume on the prediction day;

[0074] Calculate the forecast comprehensive impact factor based on the actual ticket booking volume before the forecast time, as well as the platform's search volume, page views, clicks, and discussion volume in the past three days;

[0075] Based on the forecast comprehensive impact factor, the first forecast customer order quantity on the forecast day is revised to obtain the second forecast customer order quantity on the forecast day.

[0076] Specifically, the weather type and date type of the collected day are cleaned, missing values ​​and outliers are processed, the weather type is converted into a numerical code (such as sunny day = 1, cloudy day = 2, rainy day = 3, snowy day = 4), and the weather attribute value of the predicted day is obtained; the date type is converted into a numerical code (such as weekday = 0, weekend = 1, holiday = 2), and the date attribute value of the predicted day is obtained; based on the weather attribute value and the date attribute value, historical data similar to the target date is extracted, including the actual customer order volume, and the average ticket booking volume of similar historical dates is calculated, and the weather type and date type are used as features, and the customer order volume is used as the target variable. Preferably, the customer order volume prediction model can select a random forest model or an XGBoost model, and the model is trained with historical data, and then the weather attribute value and the date attribute value of the predicted day are input into the model to obtain the first predicted customer order volume for the predicted day.

[0077] Furthermore, the actual ticket booking volume of the day before the prediction time, as well as the search volume, page views, click volume, and discussion volume of the platform (online ticket purchasing platform) in the past three days are obtained and standardized. Since there is a time difference between the prediction time and the actual day, there will be new ticket bookings. The growth of this part can be estimated based on the ticket booking growth trend in historical data. Let T be the length of time from the prediction time point to the actual date (in days), r is the average daily growth rate, then the predicted new order volume ΔX n It is expressed as:

[0078] ΔX n =X a ×(1+r) T

[0079] Among them, X a Indicates the actual ticket booking volume for the day just before the forecast.

[0080] Furthermore, we analyze the impact of hot spot data and evaluate its impact on the final ticket booking volume by analyzing the search volume, click volume, pageview volume, and discussion volume of the online platform. The impact of these indicators on the ticket booking volume can be represented by a weighted function. The hot spot impact coefficient is obtained by weighted summing these indicators. Combined with the incremental forecast of the actual order volume and the hot spot impact coefficient, the comprehensive impact factor α is calculated, which is expressed as:

[0081]

[0082] Among them, Y represents the first predicted customer order volume on the prediction day, I represents the hot spot influence coefficient, ω 1 ,ω 2 They respectively represent weight coefficients, which are set according to the actual application scenario and can also be set through machine learning. The second predicted customer order volume on the prediction day is calculated by multiplying the first predicted customer order volume on the prediction day by the comprehensive influencing factor, that is, the final customer order volume forecast value for that day.

[0083] It should be noted that the actual number of existing orders is a very important reference data point when making predictions. By considering this known data and estimating the number of new orders in the future, the accuracy of the prediction can be improved. In addition, now all cultural and tourism ticketing is purchased online, so the online platform hot data search volume, click volume, pageview volume and discussion volume reflect the user's recent interest and attention, which can help capture short-term trend changes and more accurately predict future ticket bookings. The initial prediction is based on historical data and fixed features (weather type, date type), but these features may not be able to fully capture short-term changes. By introducing real-time data, the current market situation and user behavior can be better reflected. The use of influencing factors for correction has high flexibility. The weights and calculation methods can be adjusted according to actual conditions, so that the model can better adapt to different scenarios and changes. The performance of the model is evaluated regularly, and the accuracy of the prediction is measured using indicators such as mean square error (MSE) and mean absolute error (MAE).

[0084] Exemplarily, generating a cultural and tourism configuration plan for the day includes:

[0085] Set the range of customer order levels for different customer order quantities, define three customer order levels according to the number of customer orders, and the specific values ​​can be set according to the actual application scenarios, which can be defined as low-flow customer orders, medium-flow customer orders and high-flow customer orders. Set different cultural and tourism configuration plans and passenger flow monitoring cycles in the cultural and tourism field according to different customer order levels. The cultural and tourism configuration plan may include but is not limited to personnel quantity arrangement, entrance and exit opening settings, facility configuration, number of tour materials, etc. Optional personnel arrangements include the local distribution and quantity configuration of guides, security, cleaning personnel, etc., the number and time of entrance and exit opening, and the facilities may be the number of tour buses, etc. The passenger flow monitoring cycle is set with different monitoring cycles according to different customer order levels. For example, the passenger flow monitoring cycle for the low-flow customer order level is 6 hours, the passenger flow monitoring cycle for the medium-flow customer order level is 3 hours, and the passenger flow monitoring cycle for the medium-flow customer order level is 0.5 hours. The corresponding service plan can be generated according to the actual situation, which greatly reduces the possibility of emergencies.

[0086] In a preferred embodiment, according to the set passenger flow monitoring cycle, the entrance and exit passenger flow of the cultural and tourism field is monitored in real time, the total number of entrances and exits in the current passenger flow monitoring cycle and the initial number of people in the previous passenger flow monitoring cycle are obtained, and the first passenger flow in the current passenger flow monitoring cycle is calculated;

[0087] Obtain sub-region environmental data and calculate the maximum number of people that can be accommodated in the cultural and tourism field as the passenger capacity threshold of the cultural and tourism field;

[0088] If the first passenger flow is less than the passenger capacity threshold, no passenger flow warning is performed, and passenger flow monitoring of the next cycle is performed according to the passenger flow monitoring cycle;

[0089] If the first passenger flow is greater than the passenger capacity threshold, a passenger flow warning is performed and a first warning task is generated;

[0090] The first warning task includes calculating the frequency of people leaving based on the number of people exiting the cultural and tourism sector during the current passenger flow monitoring cycle, in order to set the frequency of entrance opening, and conducting passenger flow monitoring for the next cycle based on the adjusted passenger flow monitoring cycle.

[0091] Specifically, according to the cultural and tourism configuration plan generated by the passenger volume prediction in step S100, the passenger flow monitoring cycle value of the day is obtained, and the opening time of the cultural and tourism area on that day is taken as the initial time. The monitoring and early warning time points are set for the start and end times of the cultural and tourism operations based on the time period of the passenger flow monitoring cycle. Based on this time point, the data of the passenger flow monitoring cycle is used as the basis, and the initial number of people in the previous passenger flow monitoring cycle is added to the total number of people entering through all entrances in the current passenger flow monitoring cycle, and then the total number of people leaving through all exits in the current passenger flow monitoring cycle is subtracted to calculate the first passenger flow in the current passenger flow monitoring cycle. It is compared with the passenger capacity threshold to determine whether to issue an early warning. If no early warning is issued, the monitoring task is completed continuously according to the monitoring time. If an early warning is issued, the first early warning task is generated. Among them, the sub-region environmental data is obtained, which can be the regional type, regional area, per capita minimum occupied area standard or per capita tour area of ​​each cultural and tourism area, and the overall passenger capacity threshold of the cultural and tourism area is obtained by calculation, and then the two are compared and judged. The content of the first early warning task includes closing the cultural and tourism ticket inspection entrance to stop tourists from entering, and suspending online ticket sales activities at the same time, and halving the passenger flow monitoring cycle of the day. According to the current passenger flow monitoring cycle, the number of people at the exit is identified, the frequency of people leaving is calculated, and the opening frequency of the entrance is set according to the frequency of people leaving, so as to meet the requirement that the passenger flow is less than the maximum passenger capacity, prevent the number of people from being too dense, causing congestion or other unexpected situations, and conduct passenger flow monitoring for the next cycle according to the adjusted passenger flow monitoring cycle.

[0092] In an optional implementation, the cultural and tourism passenger capacity threshold can be calculated by considering the spatial carrying capacity, dividing the cultural and tourism field into different functional areas, which can be tourist areas, rest areas, roads, etc., obtaining the area of ​​the functional area and the per capita minimum occupied area standard stipulated in each functional area, for example, the per capita minimum occupied area of ​​the tourist area is 5 square meters, the rest area is 3 square meters, etc.), calculating the maximum number of people carried by each functional area, and then calculating the overall passenger capacity threshold of the cultural and tourism, which can be expressed as:

[0093]

[0094] Among them, SF i Represents the area of ​​each functional area, a i Indicates the minimum per capita occupied area standard of each functional area, M i It indicates the maximum number of passengers that can be carried in each functional area, and M indicates the passenger capacity threshold.

[0095] In another optional implementation, the passenger capacity threshold may refer to the area with the smallest traffic capacity in the cultural and tourism area as the bottleneck area, which may be a narrow passage, entrance, etc. The maximum number of people N in the bottleneck area is calculated based on the width and length of the bottleneck area, as well as the safe speed of people in the area (e.g., 0.5 m / s) and the average stay time (e.g., 10 seconds), and is expressed as:

[0096]

[0097] Where W represents the width of the bottleneck area, L represents the length of the bottleneck area, and s a represents the per capita occupied area in the bottleneck area, v represents the safe passage speed of personnel in the bottleneck area, and t represents the average stay time of personnel in the area;

[0098] According to the maximum number of people that the bottleneck area can carry and the ratio of the bottleneck area to the total area of ​​the scenic spot, the overall passenger capacity threshold of the cultural tourism is calculated and expressed as:

[0099]

[0100] Among them, ST represents the total area in the cultural and tourism field, and O represents the passenger capacity threshold.

[0101] In a preferred embodiment, obtaining the passenger flow distribution of each sub-area and determining whether to issue an early warning includes:

[0102] Step 1: Divide the passenger flow monitoring cycle into several warning time periods, obtain the passenger flow data of each sub-area within the warning time period through the monitoring points at the entrance and exit of each sub-area, obtain the total number of people in the sub-area according to the number of people entering and exiting each sub-area, and calculate the passenger flow mean of each sub-area;

[0103] Step 2: Compare the passenger flow mean with the flow threshold. If the passenger flow mean is less than the flow threshold, continue monitoring. If the passenger flow mean is greater than the flow threshold, issue a first-level warning.

[0104] Step 3: Based on the passenger flow mean, calculate the passenger flow change index, and combine the passenger flow in and out frequency of each sub-area to obtain the passenger flow comprehensive index of the sub-area to determine whether to issue a secondary warning;

[0105] Step 4: If a second-level warning is issued, a second warning task is generated for the current sub-area

[0106] Among them, in the above step three, if it is judged based on the comprehensive passenger flow indicators that no secondary warning is required, then return to step one to continue monitoring the next warning time period. If in step two, the passenger flow mean is greater than the flow threshold, it means that a first-level warning has been issued for two consecutive monitoring periods. In this case, the judgment in step three can be omitted and a secondary warning is directly issued, and a second warning task is generated for execution. If the passenger flow mean in the monitoring of the next warning time period is less than the flow threshold, no warning is issued and the next stage of monitoring is continued. In this embodiment, the passenger flow monitoring cycle is divided into a number of warning time periods, which can be set according to the actual scenario.

[0107] Exemplarily, the passenger flow mean D of each sub-area is expressed as:

[0108]

[0109] Among them, NC 0 Indicates the initial population of the sub-region, NC in Indicates the number of people entering the sub-area during the same warning period, NC out It indicates the number of people who leave the sub-area during the same warning period. SC indicates the area of ​​the sub-area. The flow threshold can be set according to the application scenario.

[0110] The passenger flow change index ΔD is expressed as:

[0111]

[0112] Among them, D t represents the mean passenger flow of the sub-area in the current warning time period, D t-1 represents the mean passenger flow of the sub-area in the previous warning period, and Δt represents the time interval of the warning period;

[0113] The comprehensive passenger flow index C of the sub-area is expressed as:

[0114] C=ω 3 ×ΔD+ω 4 ×Δf

[0115]

[0116] Among them, Δf represents the difference in the frequency of entry and exit of the sub-area in the current warning time period, ω 3 ,ω 4 Represents the weight coefficient.

[0117] Specifically, if the current passenger flow in a sub-area is large, the passenger flow mobility is poor, and the passenger flow concentration is high, then the comprehensive passenger flow index must be a negative number. A reasonable indicator threshold based on the scenic area safety standards is set for judgment. If it exceeds the threshold, a second-level warning is issued. It can make accurate judgments on warnings. Through comparison, it can intuitively know whether the current passenger flow is within a safe range. Combined with dynamic change trends, potential risks can be detected in advance, and early warnings can be issued to prevent safety accidents caused by excessive gathering of tourists, such as crowding and trampling. It helps to take measures before the passenger flow affects the tourist experience, improve overall satisfaction, dynamically monitor the population flow change rate and entry and exit frequency, provide real-time data support for management, and predict the risk of excessive passenger flow in advance, so that there is more time to initiate emergency plans.

[0118] In a preferred embodiment, the second warning task includes:

[0119] According to the warning time period of the sub-area, set the opening time of the sub-area entrance, and determine the passenger flow allowed to enter each time the entrance is opened according to the frequency of passenger flow entry and exit;

[0120] Based on the opening time of the sub-area entrance and the passenger flow entering, combined with the number of people waiting at the sub-area entrance, the estimated queue time of the sub-area is obtained and displayed in the sub-area;

[0121] Increase the number of guides and security personnel, and broadcast announcements to guide passenger flow in this sub-area and speed up the flow frequency of passenger flow.

[0122] Specifically, the sub-area dynamically adjusts the opening time of the sub-area entrance according to the warning time period, and refers to the frequency of passenger flow out to determine the passenger flow allowed to enter when the entrance is opened. This is used to control the real-time number of people in the sub-area and avoid excessive growth in the number of people. The waiting time in the queue is also calculated so that tourists can know the waiting time in advance and arrange their itinerary reasonably.

[0123] It should be noted that this step can accurately control the number of tourists entering the sub-area, alleviate the passenger flow pressure in the sub-area from the source, ensure the safety and sightseeing experience of tourists, avoid congestion and chaos caused by too many tourists, and provide tourists with transparent information, reduce tourists' anxiety caused by unknown waiting time, and improve tourist satisfaction. At the same time, tourists can decide whether to wait to enter according to the length of the queue, which can also disperse the passenger flow to a certain extent. In the early warning state, the culture and tourism department will send additional guides and security personnel to each area to guide tourists to avoid tourists gathering in certain areas, maintain on-site order, and ensure the safety of tourists, so as to speed up the flow of passengers and improve the regional carrying efficiency.

[0124] In a preferred embodiment, dynamically generating an optimal tour path for each sub-area includes:

[0125] According to the historical visit volume of each sub-region in the cultural and tourism field in the past month, the sub-regions are ranked and the regional popularity value is obtained as the first visit influencing factor;

[0126] Based on the comprehensive passenger flow index of each sub-region, the passenger flow of the sub-regions is sorted to obtain the regional passenger flow value as the second tourism influencing factor;

[0127] Obtain the distance value between the current sub-area and other sub-areas as the third tour influencing factor;

[0128] Based on the first tour influence factor, the second tour influence factor and the third tour influence factor, the optimal tour route is planned for each area.

[0129] Specifically, collect the number of daily visitors to each sub-region in the cultural and tourism field in the past month, ensure the integrity and accuracy of the data, calculate the popularity value, and conduct statistical analysis on the historical visit volume of each sub-region. The average visit volume of each sub-region in the past month can be calculated as the popularity value of the sub-region. The higher the popularity value, the more popular the region is; according to the comprehensive passenger flow index obtained above, the passenger flow of each sub-region is sorted according to this index to obtain the passenger flow value; through the cultural and tourism area map or geographic information system (GIS), measure and record the actual distance or walking time between each sub-region and other sub-regions as the distance value. Define the objective function, and set the tour path as p = (p 1 ,p 2 ,...,p j ), where p j It represents the j-th visited sub-area. The goal is to find a path, which can be the best path for the five nearby sub-areas. The total score after comprehensively considering the popularity value, passenger flow value and distance value is optimal, and the ranking is performed. The path is dynamically analyzed and planned for the actual situation of each sub-area. The total score function can be defined as the weighted sum of the popularity value, passenger flow value and distance value. The starting point of the path is the current sub-area, and the end point is the last sub-area. The heuristic algorithm is used for solving, such as genetic algorithm, simulated annealing algorithm, etc., and the optimal path recommendation is displayed on the sub-area display screen. Due to the real-time changes in the passenger flow of the scenic spot, the passenger flow value of each sub-area is recalculated at intervals (such as half an hour or one hour), and the tour path is replanned according to the new data to ensure that the most reasonable suggestions are provided to tourists.

[0130] It should be noted that the present invention comprehensively improves the efficiency of cultural and tourism operations and the experience of tourists through multi-dimensional management of cultural and tourism businesses. By obtaining ticketing data and historical ticket booking data to predict the number of customer orders, the scale of tourists can be estimated in advance. Based on the cultural and tourism configuration plan generated on the day, preparations can be made in advance in terms of personnel, materials, facilities, etc. to avoid waste or shortage of resources, achieve optimal allocation of resources, and ensure the orderliness and efficiency of daily operations; real-time monitoring of the passenger flow at the entrances and exits of the cultural and tourism field can promptly discover whether the overall passenger flow of cultural and tourism exceeds the carrying capacity, so as to quickly take early warning measures and build a solid defense line for safe operations. At the same time, the passenger flow of each sub-area is analyzed based on the passenger load. The distribution of passenger flow in each sub-region and the factors affecting the tour are combined to dynamically generate the optimal tour route, which can guide tourists to plan their tour itineraries reasonably, balance the passenger flow of each scenic spot, reduce the waiting time of tourists in popular scenic spots, improve the smoothness and comfort of tourists' tours, and allow tourists to have a better travel experience.

[0131] The above is a schematic scheme of a cultural tourism business management method of this embodiment. It should be noted that the technical scheme of the cultural tourism business management system and the technical scheme of the cultural tourism business management method described above are of the same concept, and the details of the technical scheme of the cultural tourism business management system not described in detail in this embodiment can be referred to the description of the technical scheme of the cultural tourism business management method described above.

[0132] In this embodiment, the cultural tourism business management system includes:

[0133] The collection configuration module is used to obtain ticketing data and historical ticket booking data in the field of culture and tourism, predict the number of customer orders on the forecast day, obtain the forecast result of the number of customer orders, and generate the cultural and tourism configuration plan for the day;

[0134] The first warning module is used to monitor the entrance and exit passenger flow of the cultural and tourism field in real time based on the cultural and tourism configuration plan of the day, calculate the first passenger flow in the cultural and tourism field, compare the first passenger flow with the passenger load threshold, and determine whether to issue a warning. If a warning is issued, a first warning task is generated;

[0135] The second warning module is used to obtain the passenger flow distribution of each sub-area based on the passenger flow in the cultural and tourism field and the information of each sub-area divided in the cultural and tourism field, and determine whether to issue a warning. If a warning is issued, a second warning task is generated;

[0136] The planning module is used to dynamically generate the optimal tour route for each sub-area based on the passenger flow distribution of each sub-area and combined with the tour influencing factors of each sub-area.

[0137] This embodiment further provides an electronic device suitable for cultural and tourism business management, including:

[0138] Memory and processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the cultural and tourism business management method proposed in the above embodiment.

[0139] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for implementing cultural and tourism business management as proposed in the above embodiment is implemented.

[0140] The storage medium proposed in this embodiment and the method for implementing cultural and tourism business management proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0141] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0142] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A cultural tourism business management method, characterized in that: include: Obtain ticketing data and historical booking data in the field of culture and tourism, predict the number of customers on the forecast day, obtain the forecast result of the number of customers, and generate the cultural and tourism configuration plan for the day; Based on the cultural and tourism configuration plan for the day, the entrance and exit passenger flow of the cultural and tourism field is monitored in real time, a first passenger flow in the cultural and tourism field is calculated, the first passenger flow is compared with the passenger load threshold, and it is determined whether to issue an early warning. If an early warning is issued, a first early warning task is generated; Based on the passenger flow situation in the cultural and tourism field, and according to the information of each sub-region divided in the cultural and tourism field, the passenger flow distribution of each sub-region is obtained, and it is determined whether to issue an early warning. If an early warning is issued, a second early warning task is generated; Based on the passenger flow distribution of each sub-area and combined with the sightseeing influencing factors of each sub-area, an optimal sightseeing route is dynamically generated for each sub-area.

2. The cultural tourism business management method according to claim 1, characterized in that: The acquisition of ticketing data and historical ticket booking data in the field of culture and tourism includes: The ticketing data includes the weather type, date attributes, ticket booking data, and platform hot spot data of the forecast day, and the platform hot spot data includes the platform's search volume, browsing volume, click volume, and discussion volume; The historical data includes customer order data of different time periods in the past three years and customer order data under different weather types in each period; The weather types are divided into sunny days, cloudy days, rainy days and snowy days.

3. The cultural tourism business management method according to claim 2, characterized in that: The customer order volume on the forecast day is predicted, and the customer order volume prediction results include: Obtain the weather forecast data for the forecast day, determine the weather type corresponding to the forecast day, and perform data preprocessing to obtain the weather attribute value for the forecast day; Obtain the date data of the predicted day, determine the date type of the predicted day, and perform data preprocessing to obtain the date attribute value of the predicted day, where the date type is divided into working days, weekends, and holidays; Select data with the same weather attributes and date attributes in the same time period from historical data, train and verify the customer order prediction model, input the weather attribute values ​​and date attribute values ​​of the prediction day into the model, and obtain the first predicted customer order volume on the prediction day; Calculate the forecast comprehensive impact factor based on the actual ticket booking volume before the forecast time, as well as the platform's search volume, page views, clicks, and discussion volume in the past three days; Based on the forecast comprehensive impact factor, the first forecast average customer volume on the forecast day is corrected to obtain the second forecast average customer volume on the forecast day.

4. The cultural tourism business management method according to claim 3, characterized in that: The generating of the first warning task comprises: According to the set passenger flow monitoring cycle, the entrance and exit passenger flow of the cultural and tourism field is monitored in real time, the total number of entrances and exits in the current passenger flow monitoring cycle and the initial number of people in the previous passenger flow monitoring cycle are obtained, and the first passenger flow in the current passenger flow monitoring cycle is calculated; Obtain sub-region environmental data and calculate the maximum number of people that can be accommodated in the cultural and tourism field as the passenger capacity threshold of the cultural and tourism field; If the first passenger flow is less than the passenger capacity threshold, no passenger flow warning is performed, and passenger flow monitoring of the next cycle is performed according to the passenger flow monitoring cycle; If the first passenger flow is greater than the passenger capacity threshold, a passenger flow warning is performed and a first warning task is generated; The first warning task includes calculating the frequency of people leaving the cultural and tourism sector based on the number of people exiting the current passenger flow monitoring cycle to set the frequency of entrance opening, and conducting passenger flow monitoring for the next cycle based on the adjusted passenger flow monitoring cycle.

5. The cultural tourism business management method according to claim 4, characterized in that: The obtaining of passenger flow distribution in each sub-area and determining whether to issue an early warning includes: The passenger flow monitoring cycle is divided into several warning time periods, and the passenger flow data of each sub-area within the warning time period is obtained through the monitoring points at the entrances and exits of each sub-area. The total number of people in the sub-area is obtained according to the number of people at the entrances and exits of each sub-area, so as to calculate the passenger flow mean of each sub-area; Compare the passenger flow mean with the flow threshold, if the passenger flow mean is less than the flow threshold, continue monitoring, if the passenger flow mean is greater than the flow threshold, issue a first-level warning; Based on the passenger flow mean, the passenger flow change index is calculated, and combined with the passenger flow in and out frequency of each sub-area, the passenger flow comprehensive index of the sub-area is obtained to determine whether to issue a secondary warning; If a second-level warning is carried out, a second warning task is generated for the current sub-area.

6. The cultural tourism business management method according to claim 5, characterized in that: The second early warning task includes: According to the warning time period of the sub-area, set the opening time of the sub-area entrance, and determine the passenger flow allowed to enter each time the entrance is opened according to the frequency of passenger flow entry and exit; Based on the opening time of the sub-area entrance and the passenger flow entering, combined with the number of people waiting at the sub-area entrance, the estimated queue time of the sub-area is obtained and displayed in the sub-area; Increase the number of guides and security personnel, and broadcast announcements to guide passenger flow in this sub-area and speed up the flow frequency of passenger flow.

7. The cultural tourism business management method according to claim 1, characterized in that: The dynamically generating the optimal tour path for each sub-area includes: According to the historical visit volume of each sub-region in the cultural and tourism field in the past month, the sub-regions are ranked and the regional popularity value is obtained as the first visit influencing factor; Based on the comprehensive passenger flow index of each sub-region, the passenger flow of the sub-regions is sorted to obtain the regional passenger flow value as the second tourism influencing factor; Obtain the distance value between the current sub-area and other sub-areas as the third tour influencing factor; Based on the first tour influence factor, the second tour influence factor and the third tour influence factor, an optimal tour route is planned for each area.

8. A cultural tourism business management system, characterized in that: include, The collection configuration module is used to obtain ticketing data and historical ticket booking data in the field of culture and tourism, predict the number of customer orders on the forecast day, obtain the forecast result of the number of customer orders, and generate the cultural and tourism configuration plan for the day; A first warning module is used to monitor the entrance and exit passenger flow of the cultural and tourism field in real time based on the cultural and tourism configuration plan of the day, calculate the first passenger flow in the cultural and tourism field, compare the first passenger flow with the passenger load threshold, determine whether to issue a warning, and if so, generate a first warning task; The second warning module is used to obtain the passenger flow distribution of each sub-area based on the passenger flow in the cultural and tourism field and the information of each sub-area divided in the cultural and tourism field, and determine whether to issue a warning. If a warning is issued, a second warning task is generated; The planning module is used to dynamically generate the optimal tour route for each sub-area based on the passenger flow distribution of each sub-area and in combination with the tour influencing factors of each sub-area.

9. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the cultural and tourism business management method described in any one of claims 1 to 7 can be implemented.

10. A computer-readable storage medium, characterized in that: It stores computer executable instructions, which, when executed by a processor, implement the cultural and tourism business management method described in any one of claims 1 to 7.

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