Refueling service information pushing method and gas station service system

Abstract

The invention discloses a refueling service information pushing method and a gas station service system, and relates to the technical field of information pushing.The method comprises the steps of sales data processing, refueling service pushing and gas station activity pushing.The method includes the steps that firstly, gas station sales data are uploaded to a cloud database; the method comprises the following steps: analyzing refueling service data of each gas station to obtain an oil product sales preference, setting a refueling service recommendation scheme according to driving data and use data of a target user, uploading the refueling service recommendation scheme to a cloud database when the driving is finished, and finally formulating a gas station activity pushing scheme according to cloud data records of the target user. According to the method, through deep analysis and integration of multi-source data, accurate refueling service information pushing for different users is realized, and the pertinence and efficiency of the refueling service are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of information push, and particularly relates to a method for pushing refueling service information and a gas station service system. Background Art

[0002] With the continuous growth of the automobile ownership, the scale of the refueling service market is constantly expanding. However, gas stations lack accurate understanding of user needs and personalized services. Therefore, a method for pushing refueling service information and a gas station service system are needed.

[0003] The prior art, such as the invention patent application with the publication number CN113596132B, discloses a method for pushing refueling service information and a gas station service system for a mobile gas station. Through this invention, a new solution that enables the mobile gas station to actively push refueling service information is provided. First, vehicle identification information of passing vehicles is collected through vehicle information collection devices arranged in the surrounding area. Then, based on this vehicle identification information, the nearest refueling information, the publicly disclosed fuel consumption information of the manufacturer, and the mobile phone number of the vehicle owner are obtained by connecting to the network in sequence. Finally, when it is found that there may be a shortage of fuel in the passing vehicle based on the aforementioned nearest refueling information and the publicly disclosed fuel consumption information of the manufacturer, a refueling service information carrying the location of the mobile gas station is actively sent to the mobile phone terminal of the vehicle owner, so that the vehicle owner can discover the mobile gas station and arrive nearby and refuel when it is confirmed that there is a shortage of fuel, thereby achieving the purpose of convenient refueling and avoiding wasting limited on-vehicle fuel.

[0004] For the above solution, there are the following technical problems: 1. The above solution mainly collects vehicle identification information, the publicly disclosed fuel consumption information of vehicle manufacturers, etc. The analysis content focuses on aspects such as vehicle refueling historical data, fuel consumption calculation, and comparison with preset thresholds, without analyzing data from multiple dimensions such as gas station sales data, driving data of target users, usage data, and browsing records of long-distance driving communication forums, and it is impossible to obtain the characteristics and needs of gas stations and users more comprehensively.

[0005] 2. The above solution determines whether to push refueling service information based on the relationship between vehicle fuel consumption and refueling volume. The pushed content is mainly basic information such as the geographical location, fuel type, and refuelable volume of the mobile gas station. The recommendation method is relatively simple and direct, with poor flexibility. There is no refueling service recommendation plan and gas station activity push plan based on the characteristics of oil products, and it is impossible to provide more personalized and targeted service recommendations according to the different needs and scenarios of users, with weak flexibility and adaptability.

[0006] 3. The above solution does not consider the user's behavioral habits and preferences in other aspects, such as the user's behavioral habits and preferences during long-distance driving. It is impossible to understand the user's potential needs from a broader perspective, and the long-distance driving needs of the user are not explored. Accordingly, a corresponding fueling service recommendation and activity push plan cannot be formulated, and the needs of the user in different scenarios cannot be met. Summary of the Invention

[0007] Aiming at the above existing technical deficiencies, the purpose of the present invention is to provide a fueling service information push method and a gas station service system.

[0008] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a fueling service information push method, including the following steps: Step 1. Sales data processing: After the gas station sales, upload the gas station sales data to the cloud database, obtain the fueling service data of each gas station from the gas station sales data in the cloud database, analyze the fueling service data of each gas station, and obtain the fuel sales preferences of each gas station.

[0009] Step 2. Fueling service push: Collect the driving data of the target user, analyze the driving data of the target user, obtain each preset demand gas station of the target user, obtain the usage data of the target user from the cloud database, analyze the usage data of the target user, obtain the fuel consumption preferences of the target user, and then set the fueling service recommendation plan for the target user. When the target user's driving ends, upload the cloud-based basic fueling service recommendation data.

[0010] Step 3. Gas station activity push: According to the cloud fueling service recommendation data record of the target user, conduct a fueling communication forum recommendation, and then collect the browsing records of the target user's fueling communication forum, analyze to obtain each pre-used long-distance path of the target user, obtain the fueling service data of the long-distance path from the cloud database, and analyze according to the fuel consumption preferences of the target user and the fueling service data of the long-distance path to obtain a gas station activity push plan. When the target user's long-distance driving ends, upload the cloud long-distance fueling service recommendation data.

[0011] Preferably, the process of setting the fueling service recommendation plan for the target user is as follows: If a certain type of fuel in the fuel sales preference of a certain preset demand gas station is the same as a certain type of fuel in the fuel consumption preferences of various types of fuels of the target user, record this preset demand gas station as the preset used gas station of the target user, and thus obtain each preset demand gas station at each fueling demand path point of the target user. Substitute the fueling opportunity preference index at each fueling demand path point of the target user and the fueling correction service index of each preset used gas station into the path point usage index calculation formula to obtain the path point usage index at each fueling demand path point of the target user.

[0012] Record each refueling demand waypoint with an exponent greater than the preset standard waypoint of the target user as each refueling usage waypoint, and arrange each preset refueling gas station of each refueling usage waypoint in ascending order according to the refueling correction service index to obtain the preset refueling gas station sequence of each refueling usage waypoint.

[0013] The refueling service recommendation plan for the target user is: when the target user travels to each refueling usage waypoint, recommend the first preset number of each preset refueling gas station in the preset refueling gas station sequence of each refueling usage waypoint.

[0014] On the other hand, the present invention provides a gas station service system, including the following modules: a sales data processing module, which is used to upload gas station sales data to the cloud database after the gas station sales, obtain the refueling service data of each gas station from the gas station sales data in the cloud database, analyze the refueling service data of each gas station, and obtain the oil product sales preferences of each gas station.

[0015] A refueling service push module, which is used to collect the driving data of the target user, analyze the driving data of the target user to obtain each preset demand gas station of the target user, obtain the usage data of the target user from the cloud database, analyze the usage data of the target user to obtain the refueling consumption preferences of the target user, and then set the refueling service recommendation plan for the target user, and upload the cloud-based basic refueling service recommendation data at the end of the target user's driving.

[0016] A gas station activity push module, which is used to recommend a refueling communication forum according to the cloud refueling service recommendation data record of the target user, and then collect the browsing records of the refueling communication forum of the target user, analyze to obtain each pre-used long-distance path of the target user, obtain the refueling service data of the long-distance path from the cloud database, and analyze to obtain a gas station activity push plan according to the refueling consumption preferences of the target user and the refueling service data of the long-distance path, and upload the cloud long-distance refueling service recommendation data at the end of the target user's long-distance driving.

[0017] The beneficial effects of the present invention are as follows: 1. The present invention uploads the gas station sales data to the cloud database, obtains the oil product sales preferences through the analysis of the refueling service data of each gas station, then sets the refueling service recommendation plan according to the driving data and usage data of the target user, uploads it to the cloud database at the end of the driving, and finally formulates a gas station activity push plan based on the cloud data record of the target user, and uploads the cloud long-distance refueling service recommendation data at the end of the target user's long-distance driving. This method realizes the accurate push of refueling service information for different users through in-depth analysis and integration of multi-source data, and improves the pertinence and efficiency of refueling services.

[0018] 2. The present invention deeply analyzes multi-dimensional data such as the refueling frequency and periodic refueling volume of each gas station, can accurately grasp the fuel sales preferences of each gas station, and at the same time collects the driving data of target users. Combining factors such as the current temperature, it can accurately determine the preset demand gas stations of target users. At the same time, through the analysis of the usage data of target users, it can clearly understand the refueling consumption preferences of users, laying a solid foundation for providing personalized services.

[0019] 3. Based on the preset demand gas stations and refueling consumption preferences of target users, the present invention sets up a refueling service recommendation scheme. When the user drives to a specific path point, it recommends the gas stations at the front of the preset usage gas station sequence according to the path point usage index, realizing the personalization and precision of refueling service recommendation. This greatly improves the efficiency of users obtaining appropriate refueling services and enhances the user experience.

[0020] 4. When uploading the basic refueling service recommendation data and long-distance refueling service recommendation data to the cloud, the present invention analyzes the validity of the data and only uploads the data to the cloud when the data is valid. This mechanism ensures the validity and reliability of the cloud data, thereby improving the scientific nature of data analysis and decision-making, and contributing to the continuous optimization of the refueling service recommendation scheme and activity push scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0022] Figure 1 It is a schematic flow chart of the implementation steps of the method of the present invention.

[0023] Figure 2 It is a schematic connection diagram of the system structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0025] According to Figure 1As shown in the figure, the present invention provides a method for pushing refueling service information, including the following steps: Step 1, sales data processing: After the gas station makes a sale, upload the gas station sales data to the cloud database, obtain the refueling service data of each gas station from the gas station sales data in the cloud database, and analyze the refueling service data of each gas station to obtain the fuel sales preferences of each gas station.

[0026] In a specific embodiment, the analysis of the refueling service data of each gas station is as follows: The refueling service data of each gas station includes the refueling frequency, periodic refueling volume, periodic refueling times, average refueling distance, usage frequency of various types of fuels, purchase frequency of various types of fuels, average refueling volume of various types of fuels, and single - time maximum refueling volume of various types of fuels.

[0027] Substitute the usage frequency, purchase frequency, average refueling volume, and single - time maximum refueling volume of various types of fuels of each gas station into the refueling service index calculation formula to obtain the refueling service index of various types of fuels of each gas station. Substitute the refueling frequency, periodic refueling volume, periodic refueling times, and average refueling distance of each gas station into the refueling service correction index calculation formula to obtain the refueling service correction index of each gas station. Obtain the refueling service correction factor corresponding to each refueling service correction index from the cloud database, and further obtain the refueling service correction factor of each gas station.

[0028] It should be noted that the refueling service index calculation formula: , where is the refueling service index of type - b fuel at gas station a, a is the number of each gas station, the value of a is a positive integer, b is the number of various types of fuels, the value of b is a positive integer, , , and are respectively the usage frequency, purchase frequency, average refueling volume, and single - time maximum refueling volume of type - b fuel at gas station a, , , and are respectively the preset standard usage frequency, standard purchase frequency, standard average refueling volume, and standard single - time maximum refueling volume, , , and are respectively the preset weight factors of usage frequency, purchase frequency weight factor, average refueling volume weight factor, and single - time maximum refueling volume weight factor, , , , , .

[0029] Standard parameters , , and are the usage frequency threshold, purchase frequency threshold, average refueling volume threshold, and single - maximum refueling volume threshold of a normal gas station respectively. When the actual value is greater than the threshold, it indicates that this type of oil product should be preferentially used when using oil products. The specific values are set by the staff. For example is 0.86, is 0.73, is 0.92 and is 0.85. The weight factors , , and have their specific values set by the staff. For example is 0.2, is 0.3, is 0.2 and is 0.3.

[0030] The calculation formula for the refueling service correction index is: , where is the refueling service correction index of gas station a, , , and are the refueling frequency, periodic refueling volume, periodic refueling times, and average refueling usage distance of gas station a respectively, , , and are the preset standard refueling frequency, standard periodic refueling volume, standard periodic refueling times, and standard average refueling usage distance respectively, , , and are the preset refueling frequency weight factor, periodic refueling volume weight factor, periodic refueling times weight factor, and average refueling usage distance weight factor respectively, , , , , .

[0031] The standard parameters , , and are set in the same process as the standard parameters . For example is 0.8, is 0.7, is 0.5 and is 0.8. The weight factor , , and The setting process of is the same as that of the weight factor is 0.2, is 0.3, is 0.2 and is 0.3.

[0032] Obtain the seasonal refueling service correction factor and date refueling service correction factor of various oil products from the cloud database, and substitute the refueling service correction factor of each gas station, the refueling service index of various oil products, the seasonal refueling service correction factor of various oil products, and the date refueling service correction factor of various oil products into the refueling correction service index calculation formula to obtain the refueling correction service index of various oil products at each gas station.

[0033] It should be noted that the seasonal refueling service correction factor and the date refueling service correction factor are the change trends of the refueling service index in the current season and the current date compared with the annual average refueling service index. The specific acquisition process can be set by the moving average trend elimination method. The moving average trend elimination method is a method for measuring trends, which is an existing technology and can be queried from the Internet and will not be elaborated here. The types of dates include weekdays, various holidays, and weekends.

[0034] The refueling correction service index calculation formula is: , where is the refueling correction service index of type b oil products at gas station a, and are the seasonal refueling service correction factor and date refueling service correction factor of various oil products respectively, is the refueling service correction factor of each gas station.

[0035] Record the oil products of each gas station that are greater than or equal to the preset standard refueling correction service index as the preferred sales oil products of each gas station at each gas station, so as to obtain the oil product sales preferences of each gas station.

[0036] It should be noted that the standard refueling correction service index is the threshold of the refueling correction service index of a normal gas station. When the refueling correction service index is greater than the threshold, it indicates that users prefer to choose the corresponding gas station when refueling. The specific value is set by the staff. For example, the standard refueling correction service index is 0.65.

[0037] Step 2: Fueling service push: Collect the driving data of the target user, analyze the driving data of the target user to obtain the preset demand gas stations of the target user, obtain the usage data of the target user from the cloud database, analyze the usage data of the target user to obtain the fuel consumption preferences of the target user, and then set the fueling service recommendation plan for the target user. When the target user's driving ends, upload the cloud-based basic fueling service recommendation data.

[0038] In a specific embodiment, the process of collecting the driving data of the target user is as follows: Connect to the database of the target user's vehicle and obtain the driving data of the target user from the database of the target user's vehicle.

[0039] In a specific embodiment, the process of analyzing the driving data of the target user is as follows: The driving data of the target user includes the current driving duration, the current driving distance, the refueling times of each fuel level, and the average refueling amount of each fuel level. Substitute them into the fueling preference index calculation formula to obtain the fueling preference index of each fuel level. Substitute the current fuel level driving times and the current fuel level driving frequency of the target user's current route into the driving preference matching index calculation formula to obtain the fueling matching index of the current route. Obtain the fueling correction factor of the current temperature from the cloud database. Substitute the fueling preference index of each fuel level, the fueling matching index of the current route, and the fueling correction factor of the current temperature into the fueling timing preference index calculation formula to obtain the fueling timing preference index of each fuel level of the target user.

[0040] It should be noted that the fueling preference index calculation formula: , where is the fueling preference index of level c fuel, c is the number of the fuel level interval, and the value of c is a positive integer. , , and are the current driving duration, the current driving distance, the refueling times of level c fuel, and the average refueling amount of level c fuel respectively. , , and are the preset standard driving duration, standard driving distance, refueling times of the standard fuel level, and refueling amount of the standard fuel level respectively. and are the preset refueling times weight factor and refueling amount weight factor respectively. , , , and are the preset driving duration weight factor and driving distance weight factor respectively. , , 。

[0041] Standard parameters 、 、 and The setting process of is the same as that of the standard parameters For example is 0.75, is 0.73, is 0.62 and is 0.81. The weight factors 、 、 and The setting process of is the same as that of the weight factor For example is 0.55, is 0.45, is 0.4 and is 0.6.

[0042] Calculation formula for the driving preference matching index: , where is the refueling matching index of the current path, and are respectively the current fuel quantity driving times and the current fuel quantity driving frequency of the target user's current path, and are respectively the preset standard driving times and the standard driving frequency, and are respectively the preset driving times weight factor and the driving frequency weight factor, , , .

[0043] Standard parameters and The setting process of is the same as that of the standard parameters For example is 0.8 and is 0.8. The weight factors and The setting process of is the same as that of the weight factor For example is 0.7 and is 0.3.

[0044] Calculation formula for the refueling timing preference index: , where is the refueling timing preference index of the target user for each fuel quantity, is the refueling correction factor for the current temperature.

[0045] Collect the fuel quantity change trend of the target user, predict the fuel quantity at each path point of the target user, and then obtain the refueling timing preference index of each path point of the target user. Record the path points where the refueling timing preference index of the target user is greater than the preset standard refueling timing preference index as each refueling demand path point. Obtain each available gas station at each path point from the cloud database, and record each available gas station at each refueling demand path point of the target user as each preset demand gas station.

[0046] It should be noted that to collect the fuel quantity change trend of the target user: calculate the change in the fuel quantity of the target user with respect to the distance through the moving average method.

[0047] The standard refueling timing preference index is as follows: Obtain the distances between adjacent path points of the current path from the cloud database, and then obtain the fuel quantity change amounts between adjacent path points of the current path. Based on the current fuel quantity, obtain the fuel quantity at each path point of the target user, and then obtain the refueling timing preference index of each path point of the target user.

[0048] The standard refueling timing preference index is the threshold of the refueling timing preference index for normal path points. When the refueling timing preference index is greater than the threshold, it indicates that the target user prefers to refuel at the corresponding path point. The specific value is set by the staff. For example, the standard refueling timing preference index is 0.65.

[0049] In a specific embodiment, the analysis of the usage data of the target user is as follows: The usage data of the target user includes the usage frequencies of various types of oils of the target user, the usage frequency of the current driving path, and the usage frequency of the current temperature. Substitute the usage frequencies of various types of oils of the target user, the usage frequency of the current driving path, and the usage frequency of the current temperature into the refueling preference index calculation formula to obtain the refueling preference index of various types of oils of the target user.

[0050] It should be noted that the refueling preference index calculation formula is: , where is the refueling preference index of the target user for type b oil, , and are respectively the usage frequency of type b oil, the usage frequency of the current driving path, and the usage frequency of the current temperature of the target user, , and are respectively the standard usage frequency of oil, the standard usage frequency of oil for the driving path, and the standard usage frequency of oil for the temperature, , and are respectively the weight factor of the usage frequency of oil, the weight factor of the usage frequency of oil for the driving path, and the weight factor of the usage frequency of oil for the temperature, , , , .

[0051] Standard parameters , and The setting process of is the same as that of the standard parameters . For example is 0.83, is 0.52 and is 0.87. The weight factors , and The setting process of is the same as that of the weight factor . For example is 0.3, is 0.4 and is 0.3.

[0052] Record the various types of oil products for which the target user is greater than or equal to the preset standard refueling preference index as the refueling consumption preference oil products for each type, so as to obtain the refueling consumption preference of the target user.

[0053] It should be noted that the standard refueling preference index is the threshold of the refueling preference index for the target user's normal refueling. When the refueling preference index is greater than the threshold, it indicates that the target user prefers to use the corresponding oil product when refueling. The specific value is set by the staff. For example, the standard refueling preference index is 0.75.

[0054] In a specific embodiment, the setting of the refueling service recommendation scheme for the target user is as follows: If a certain type of oil product in the oil product sales preference of a certain preset demand gas station is the same as a certain type of oil product in the refueling consumption preference of various types of oil products of the target user, record this preset demand gas station as the preset used gas station of the target user, so as to obtain the preset demand gas stations at each refueling demand path point of the target user. Substitute the refueling timing preference index of each refueling demand path point of the target user and the refueling correction service index of each preset used gas station into the path point usage index calculation formula to obtain the path point usage index of each refueling demand path point of the target user.

[0055] It should be noted that the path point usage index calculation formula is: , where is the path point usage index of the refueling demand path point d of the target user, is the refueling timing preference index of the refueling demand path point d of the target user, is the refueling correction service index of the preset used gas station e at the refueling demand path point d. e is the number of the preset used gas station, and the value of e is a positive integer. is the standard refueling correction service index. To preset the weight factor for using gas station e , .

[0056] Record the maximum refueling correction service index of various types of oil products in the refueling consumption preferences of the target users of each preset used gas station as the refueling correction service index of each preset used gas station.

[0057] Standard parameter The specific value is set by the staff. For example is 0.68, and the weight factor is set related to the distance from each preset used gas station to the corresponding refueling demand path point. The farther the distance, the smaller the weight factor. For example is 0.15.

[0058] Record the refueling demand path points where the target user's usage index of the preset standard path point is greater than the preset standard as each refueling usage path point, and arrange the preset used gas stations of each refueling usage path point in ascending order according to the refueling correction service index to obtain the sequence of preset used gas stations for each refueling usage path point.

[0059] It should be noted that the usage index of the standard path point is the threshold of the path point usage index of the normal path point. When the path point usage index is greater than the threshold, it indicates that the target user is used to refueling at the corresponding path point. The specific value is set by the staff. For example, the usage index of the standard path point is 0.93.

[0060] The refueling service recommendation plan for the target user is: when the target user travels to each refueling usage path point, recommend the preset number of preset used gas stations at the front of the sequence of preset used gas stations for each refueling usage path point.

[0061] In a specific embodiment, the process of uploading the cloud-based basic refueling service recommendation data is as follows: Obtain the recommendation selection rate of each cycle of various unit cycles of the target user from the cloud database, fit the recommendation selection rate of each cycle of various unit cycles of the target user to obtain the recommendation selection rate change curve of the recommendation selection rate of various unit cycles of the target user changing with time, and then obtain the average slope and current slope of the recommendation selection rate change curve of various unit cycles of the target user. Obtain the data effective index corresponding to the slope of each recommendation selection rate change curve from the cloud database to obtain the average data effective index and current data effective index of the recommendation selection rate change curve of various unit cycles of the target user. Substitute the average data effective index and current data effective index of various unit cycles of the target user into the data effective evaluation index calculation formula to obtain the data effective evaluation index of the target user's current refueling service recommendation data.

[0062] It should be noted that various unit cycles refer to various cycles with different statistical time lengths. For example, the type cycle with a statistical unit of one week, the type cycle with a statistical unit of one month, etc. The recommended selection rate is the number of refueling times for the recommended plan at the gas station within the corresponding cycle divided by the total number of refueling times.

[0063] The calculation formula for the data effective evaluation index is: , where is the data effective evaluation index of the current refueling service recommendation data for the target user, and are the average data effective index and the current data effective index of the t-type unit cycle of the target user respectively. t is the number of the various unit cycles, , , the value of n is the total number of types of the various unit cycles, is the preset standard data effective index, and are the weight factors of the preset average data effective index and the current data effective index respectively, , , , is the weight factor of the t-type unit cycle, , .

[0064] Standard parameter is set in the same process as the standard parameter . For example, is 0.8, and the setting process of the weight factors , and is the same as the setting process of the weight factor . For example, is 0.3, is 0.7, and is 0.14.

[0065] If the data effective evaluation index of the current refueling service recommendation data for the target user is greater than the preset standard data effective evaluation index, upload the current refueling service recommendation data of the target user to the cloud database.

[0066] It should be noted that the standard data effective evaluation index is the threshold of the data effective evaluation index for normal data. When the data effective evaluation index is greater than the threshold, it indicates that the corresponding data is valid data and can be uploaded to the cloud. The specific value is set by the staff. For example, the standard data effective evaluation index is 0.87.

[0067] Step 3: Gas station activity push: Based on the cloud-based fueling service recommendation data records of the target users, recommend fueling communication forums, and then collect the browsing records of the target users' fueling communication forums. Analyze to obtain the pre-used long-distance routes of the target users. Retrieve the fueling service data for the long-distance routes from the cloud database. Based on the fueling consumption preferences of the target users and the fueling service data for the long-distance routes, analyze to obtain a gas station activity push plan. When the target users' long-distance driving ends, upload the cloud-based long-distance fueling service recommendation data.

[0068] In a specific embodiment, the process of recommending the fueling communication forums is as follows: When the refueling volume recommended in the cloud-based fueling service recommendation data records of the target users is greater than the preset refueling volume, recommend the target fueling communication forums.

[0069] In a specific embodiment, the process of collecting the browsing records of the target users' fueling communication forums is as follows: The browsing record data of the target users' fueling communication forums includes the average browsing duration, average browsing times, and maximum single-browsing duration of each long-distance route node article for each long-distance route. When the target users browse the fueling communication forums, collect the browsing time of the target users on each web page of the fueling communication forums, and record the times simultaneously. Based on the long-distance route node articles in the content of each web page of the fueling communication forums, obtain the browsing duration and browsing times of each browsing of each long-distance route node article for each long-distance route. Select the maximum duration of each long-distance route node article as the maximum single-browsing duration of each long-distance route node article. At the same time, calculate the average value of the browsing duration and browsing times of each browsing of each long-distance route node article for each long-distance route to obtain the average browsing duration and average browsing times of each long-distance route node article for each long-distance route.

[0070] In a specific embodiment, the process of analyzing to obtain the pre-used long-distance routes of the target users is as follows: Substitute the average browsing duration, average browsing times, and maximum single-browsing duration of each long-distance route node article for each long-distance route into the path preference index calculation formula to obtain the path preference index of each long-distance route of the target users. Record the long-distance routes with a path preference index greater than the preset standard path preference index as the pre-used long-distance routes of the target users.

[0071] It should be noted that the path preference index calculation formula is: , where is the path preference index of the long-distance route g of the target user, g is the number of each long-distance route, and the value of g is a positive integer. 、 and They are respectively the average browsing duration, average browsing times, and maximum single browsing duration of the long-distance path node i of the long-distance path h. i is the number of the long-distance path node. , , where the value of v is the total number of long-distance path nodes. , and They are respectively the preset standard browsing duration, standard maximum browsing duration, and standard browsing times. and They are respectively the weight factor of the browsing duration and the weight factor of the browsing times preset. , , , is the weight factor of each long-distance path node preset. , .

[0072] Standard parameters , and are set in the same process as the standard parameter . For example, is 0.8, is 0.71, and is 0.82. The setting process of the weight factors , and is the same as the setting process of the weight factor . For example, is 0.2, is 0.8, and is 0.15.

[0073] By the browsing duration and browsing times of the user for each long-distance path node of each long path, the attention degree of the user to each long-distance path node of each long path is judged. By the maximum single browsing duration, the attention depth of the user to each long-distance path node of each long path is judged. Thus, the information acceptance degree of the user to each long-distance path node of each long path is analyzed. According to the combination of each long-distance path node, the information acceptance degree of each overall long path is obtained. The long paths with higher information acceptance degree are concerned by the target user, and the priority of the analysis arrangement in the system is improved. The priority is described by the path preference index. When it is greater than the standard path preference index, it is recorded as the pre-used long-distance path of the target user, indicating that the target user is concerned about the message of this long-distance path and gives priority to analyzing this long-distance path in the data analysis process and pushing the gas station information of this long-distance path in the information push process.

[0074] The standard path preference index is the threshold of the path preference index for normal long - distance paths. When the path preference index is greater than the threshold, it indicates that the target user may drive the corresponding long - distance path. The specific value is set by the staff. For example, the standard path preference index is 1.56.

[0075] In a specific embodiment, the obtained gas station activity push plan is analyzed as follows: The refueling service data for long - distance paths includes the recommendation rate, usage rate, and usage amount of various types of oil products for each distance. Then, the recommendation rate, usage rate, and usage amount of various types of oil products for each pre - used long - distance path of the target user are obtained. The refueling consumption preference of the target user is: the refueling preference index of various types of oil products of the target user. Substitute the recommendation rate, usage rate, usage amount, and refueling preference index of various types of oil products for each pre - used long - distance path of the target user into the long - distance refueling preference index calculation formula to obtain the long - distance refueling preference index of various types of oil products for each pre - used long - distance path of the target user. Select the oil product with the maximum long - distance refueling preference index as the pre - used long - distance oil product for each pre - used long - distance path of the target user.

[0076] It should be noted that the long - distance refueling preference index calculation formula is: , where is the long - distance refueling preference index of the b - type oil product for the long - distance path g pre - used by the target user, h is the number of each pre - used long - distance path of the target user, and the value of h is a positive integer. 、 and are respectively the recommendation rate, usage rate, and usage amount of the b - type oil product for the long - distance path h pre - used by the target user. 、 and are respectively the preset standard recommendation rate, standard usage rate, and standard usage amount. 、 and are respectively the preset recommendation rate weight factor, usage rate weight factor, and usage amount weight factor. , , , .

[0077] Standard parameters 、 and are set in the same process as the standard parameter . For example is 0.7, is 0.5 and is 0.8. The setting process of the weight factors 、 and is the same as the setting process of the weight factor The setting process is the same. For example, is 0.3, is 0.2, and is 0.5.

[0078] Obtain the fuel sales preferences of each gas station on each long-distance path from the cloud database. If the fuel to be pre-used for long-distance by the target user belongs to the fuel sales preference of a certain gas station on the corresponding pre-used long-distance path, it indicates that this gas station is the preset long-distance use gas station for the target user on this pre-used long-distance path, and thus obtain the preset long-distance use gas stations for each pre-used long-distance path of the target user.

[0079] Gas station activity push plan: When there are preferential activities at the preset long-distance use gas stations of the target user, push notifications to the target user. At the same time, when the target user drives into a certain pre-used long-distance path, push the corresponding preset long-distance use gas stations of this pre-used long-distance path.

[0080] In a specific embodiment, the process of uploading the cloud long-distance refueling service recommendation data is as follows: Obtain the long-distance path recommendation selection rates of each cycle of various unit cycles of the target user from the cloud database. According to the analysis method of the recommendation selection rates of each cycle of various unit cycles of the target user, analyze the long-distance path recommendation selection rates of each cycle of various unit cycles of the target user to obtain the data effective evaluation index of the target user's current long-distance refueling service recommendation data. When the data effective evaluation index of the target user's current long-distance refueling service recommendation data is greater than the preset standard data effective evaluation index, upload the target user's current long-distance refueling service recommendation data to the cloud.

[0081] According to Figure 2 As shown, the present invention provides a gas station service system, including the following modules: a sales data processing module, a refueling service push module, a gas station activity push module, and a cloud database.

[0082] The refueling service push module is respectively connected to the sales data processing module and the gas station activity push module, and the sales data processing module, the refueling service push module, and the gas station activity push module are all connected to the cloud database.

[0083] The sales data processing module is used to upload the gas station sales data to the cloud database after the gas station sales, obtain the refueling service data of each gas station from the gas station sales data in the cloud database, and analyze the refueling service data of each gas station to obtain the fuel sales preferences of each gas station.

[0084] The refueling service push module is used to collect the driving data of the target user, analyze the driving data of the target user to obtain each preset demand gas station of the target user, obtain the usage data of the target user from the cloud database, analyze the usage data of the target user to obtain the refueling consumption preference of the target user, and then set the refueling service recommendation plan for the target user. When the target user's driving ends, collect the refueling service recommendation data of the current driving and upload the cloud-based basic refueling service recommendation data.

[0085] The gas station activity push module is used to recommend a refueling communication forum based on the cloud refueling service recommendation data record of the target user, and then collect the browsing records of the refueling communication forum of the target user, analyze to obtain each pre-used long-distance path of the target user, obtain the refueling service data of the long-distance path from the cloud database, and analyze to obtain the gas station activity push plan according to the refueling consumption preference of the target user and the refueling service data of the long-distance path. When the target user's long-distance driving ends, upload the cloud long-distance refueling service recommendation data.

[0086] The cloud database is used to store the refueling service data of each gas station, the refueling service correction factors corresponding to each refueling service correction index, the seasonal refueling service correction factors of various oil products, the date refueling service correction factors of various oil products, the usage data of the target user, the refueling correction factor of the current temperature, each available gas station at each path point, the distances between adjacent path points of the current path, the recommended selection rates of each cycle of various unit cycles of the target user, the data validity index corresponding to the slope of each recommended selection rate change curve, the refueling service data of the long-distance path, the oil product sales preferences of each gas station on each long-distance path, and the long-distance path recommended selection rates of each cycle of various unit cycles of the target user.

[0087] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution. As long as they do not deviate from the concept of the invention or exceed the scope defined by this specification, they should all fall within the protection scope of the present invention.

Claims

1. A method for pushing refueling service information, characterized in that, The steps are as follows: Step 1, sales data processing: After sales at the gas station, upload the gas station sales data to the cloud database. Obtain the refueling service data of each gas station from the gas station sales data in the cloud database, and analyze the refueling service data of each gas station to obtain the fuel sales preferences of each gas station; Step 2, refueling service push: Collect the driving data of the target user, analyze the driving data of the target user to obtain each preset demand gas station of the target user, obtain the usage data of the target user from the cloud database, analyze the usage data of the target user to obtain the refueling consumption preferences of the target user, and then set the refueling service recommendation plan for the target user. When the target user's driving ends, upload the cloud-based basic refueling service recommendation data; Step 3, gas station activity push: According to the cloud-based refueling service recommendation data record of the target user, conduct a refueling communication forum recommendation. Then collect the browsing records of the refueling communication forum of the target user, analyze to obtain each pre-used long-distance route of the target user, obtain the refueling service data of the long-distance route from the cloud database, and according to the refueling consumption preferences of the target user and the refueling service data of the long-distance route, analyze to obtain the gas station activity push plan. When the target user's long-distance driving ends, upload the cloud-based long-distance refueling service recommendation data.

2. The fueling service information push method according to claim 1, wherein The analysis of the refueling service data of each gas station is as follows: The refueling service data of each gas station includes the refueling frequency, periodic refueling volume, periodic refueling times, average refueling distance, usage frequency of various types of fuels, purchase frequency of various types of fuels, average refueling volume of various types of fuels, and single-time maximum refueling volume of various types of fuels of each gas station; Substitute the usage frequency, purchase frequency, average refueling volume, and single-time maximum refueling volume of various types of fuels of each gas station into the refueling service index calculation formula to obtain the refueling service index of various types of fuels of each gas station. Substitute the refueling frequency, periodic refueling volume, periodic refueling times, and average refueling distance of each gas station into the refueling service correction index calculation formula to obtain the refueling service correction index of each gas station. Obtain the refueling service correction factor corresponding to each refueling service correction index from the cloud database, and then obtain the refueling service correction factor of each gas station; Obtain the seasonal refueling service correction factor and date refueling service correction factor of various types of fuels from the cloud database. Substitute the refueling service correction factor, refueling service index of various types of fuels, seasonal refueling service correction factor of various types of fuels, and date refueling service correction factor of various types of fuels of each gas station into the refueling correction service index calculation formula to obtain the refueling correction service index of various types of fuels of each gas station; Record the various types of fuels of each gas station with a refueling correction service index greater than or equal to the preset standard as the various sales preference fuels of each gas station, and thus obtain the fuel sales preferences of each gas station; The calculation formula for the refueling service index is as follows: , where is the refueling service index of Class b oil products at gas station a, a is the number of each gas station, the value of a is a positive integer, b is the number of each type of oil product, and the value of b is a positive integer. , , and are respectively the usage frequency, purchase frequency, average refueling volume, and maximum single refueling volume of Class b oil products at gas station a. , , and are respectively the preset standard usage frequency, standard purchase frequency, standard average refueling volume, and standard maximum single refueling volume. , , and are respectively the weight factors of the preset usage frequency, purchase frequency weight factor, average refueling volume weight factor, and maximum single refueling volume weight factor. , , , , ; The calculation formula for the refueling service correction index is as follows: , where is the refueling service correction index of gas station a, , , and are the refueling frequency, periodic refueling volume, periodic refueling times, and average refueling usage distance of gas station a respectively, , , and are the preset standard refueling frequency, standard periodic refueling volume, standard periodic refueling times, and standard average refueling usage distance respectively, , , and are the preset refueling frequency weight factor, periodic refueling volume weight factor, periodic refueling times weight factor, and average refueling usage distance weight factor respectively, , , , , ; The calculation formula for the refueling correction service index is as follows: , where is the refueling correction service index of Class B oil products at gas station a, and are the seasonal refueling service correction factors and date refueling service correction factors for various oil products respectively, is the refueling service correction factor for each gas station.

3. The refueling service information push method according to claim 2, wherein The analysis of the driving data of the target user is as follows: The driving data of the target user includes the current driving duration, current driving distance, refueling times for each fuel level, and average refueling volume for each fuel level. Substituting these into the refueling preference index calculation formula, the refueling preference index for each fuel level is obtained. Substituting the current fuel consumption times and current fuel consumption frequency of the current path of the target user into the driving preference matching index calculation formula, the refueling matching index of the current path is obtained. The refueling correction factor of the current temperature is obtained from the cloud database. Substituting the refueling preference index for each fuel level, the refueling matching index of the current path, and the refueling correction factor of the current temperature into the refueling timing preference index calculation formula, the refueling timing preference index for each fuel level of the target user is obtained; Collect the fuel quantity change trend of the target user, predict the fuel quantity at each path point of the target user, and then obtain the refueling timing preference index at each path point of the target user. Mark the path points with a refueling timing preference index greater than the preset standard refueling timing preference index of the target user as each refueling demand path point. Obtain each available gas station at each path point from the cloud database, and mark each available gas station at each refueling demand path point of the target user as each preset demand gas station; The calculation formula for the refueling preference index: , where is the refueling preference index for grade c fuel volume, c is the number of the fuel volume interval, and the value of c is a positive integer , , and are the current driving duration, current driving distance, refueling times for grade c fuel volume, and average refueling volume for grade c fuel volume respectively , , and are the preset standard driving duration, standard driving distance, refueling times for standard fuel volume, and refueling volume for standard fuel volume respectively and are the preset refueling times weight factor and refueling volume weight factor respectively , , , and are the preset driving duration weight factor and driving distance weight factor respectively , , ; The calculation formula for the driving preference matching index is as follows: , where is the refueling matching index of the current route, and are respectively the current fuel quantity driving times and the current fuel quantity driving frequency of the current route of the target user, and are respectively the preset standard driving times and the standard driving frequency, and are respectively the preset driving times weight factor and the driving frequency weight factor, , , ; The calculation formula for the refueling timing preference index is as follows: , where is the refueling timing preference index for each fuel level of the target user, is the refueling correction factor for the current temperature.

4. The method for pushing refueling service information according to claim 1, characterized in that The analysis of the usage data of the target user is as follows: The usage data of the target user includes the usage frequency of various types of oil products of the target user, the usage frequency of the current driving path, and the usage frequency of the current temperature. Substituting the usage frequency of various types of oil products of the target user, the usage frequency of the current driving path, and the usage frequency of the current temperature into the refueling preference index calculation formula, the refueling preference index of various types of oil products of the target user is obtained; Mark the various types of oil products of the target user that are greater than or equal to the preset standard refueling preference index as each refueling consumption preference oil product, and thus obtain the refueling consumption preference of the target user; The calculation formula for the refueling preference index is as follows: , where is the refueling preference index of Class B oil products for the target user, , and are respectively the usage frequency of Class B oil products, the usage frequency of the current driving route, and the usage frequency of the current temperature of the target user, , and are respectively the usage frequency of standard oil products, the usage frequency of oil products on the standard driving route, and the usage frequency of oil products at the standard temperature, , and are respectively the weight factor of the usage frequency of oil products, the weight factor of the usage frequency of oil products on the driving route, and the weight factor of the usage frequency of oil products at the temperature, , , , .

5. The method for pushing refueling service information according to claim 4, wherein The setting of the refueling service recommendation plan for the target user is as follows: If a certain type of oil product in the oil product sales preference of a certain preset demand gas station is the same as a certain type of oil product in the refueling consumption preference of various types of oil products of the target user, mark this preset demand gas station as the preset usage gas station of the target user, and thus obtain each preset demand gas station at each refueling demand path point of the target user. Substitute the refueling timing preference index of each refueling demand path point of the target user and the refueling correction service index of each preset usage gas station into the path point usage index calculation formula, and obtain the path point usage index of each refueling demand path point of the target user; Mark the refueling demand path points of the target user that are greater than the preset standard path point usage index as each refueling usage path point, and arrange each preset usage gas station at each refueling usage path point in ascending order of the refueling correction service index to obtain the preset usage gas station sequence of each refueling usage path point; The refueling service recommendation plan for the target user is: when the target user drives to each refueling usage path point, recommend the first preset number of each preset usage gas station in the preset usage gas station sequence of each refueling usage path point; The path point uses the exponential calculation formula as follows: , where is the path point usage index of the refueling demand path point d of the target user, is the refueling timing preference index of the refueling demand path point d of the target user, is the refueling correction service index of the preset refueling gas station e for the refueling demand path point d, e is the number of the preset refueling gas station, and the value of e is a positive integer, is the standard refueling correction service index, is the weight factor of the preset refueling gas station e, , .

6. The refueling service information push method according to claim 4, wherein The upload of the cloud-based basic refueling service recommendation data is as follows: Obtain the recommendation selection rates of each cycle of various unit cycles of the target user from the cloud database, fit the recommendation selection rates of each cycle of various unit cycles of the target user to obtain the recommendation selection rate change curve of the recommendation selection rates of various unit cycles of the target user changing with time, and then obtain the average slope and current slope of the recommendation selection rate change curve of various unit cycles of the target user. Obtain the data effective index corresponding to the slope of each recommendation selection rate change curve from the cloud database to obtain the average data effective index and current data effective index of the recommendation selection rate change curve of various unit cycles of the target user. Substitute the average data effective index and current data effective index of various unit cycles of the target user into the data effective evaluation index calculation formula to obtain the data effective evaluation index of the current refueling service recommendation data of the target user; If the data effective evaluation index of the current refueling service recommendation data of the target user is greater than the preset standard data effective evaluation index, upload the current refueling service recommendation data of the target user to the cloud database; The calculation formula for the data validity evaluation index is as follows: , where is the data validity evaluation index of the current refueling service recommendation data for the target user, and are respectively the average data validity index and the current data validity index of the target user in the t-th type of unit cycle, where t is the number of the types of unit cycles, , , and the value of n is the total number of types of unit cycles, is the preset standard data validity index, and are respectively the weight factors of the preset average data validity index and the current data validity index, , , , is the weight factor of the t-th type of unit cycle, , .

7. A fueling service information push method according to claim 6, characterized in that, The specific analysis process for obtaining each pre-used long-distance path of the target user is as follows: The browsing record data of the target user's refueling communication forum includes the average browsing duration, average browsing times, and maximum single browsing duration of each long-distance path node article of each long-distance path. Substitute the average browsing duration, average browsing times, and maximum single browsing duration of each long-distance path node article of each long-distance path into the path preference index calculation formula to obtain the path preference index of each long-distance path of the target user. Record each long-distance path with a path preference index greater than the preset standard path preference index as each pre-used long-distance path of the target user; The calculation formula for the path preference index is as follows: , where is the path preference index of the long-distance path g of the target user, g is the number of each long-distance path, and the value of g is a positive integer, , and are respectively the average browsing duration, average browsing times, and maximum browsing duration per single visit of the article of the long-distance path node i of the long-distance path h. i is the number of the long-distance path node, , , and the value of v is the total number of long-distance path nodes, , and are respectively the preset standard browsing duration, standard maximum browsing duration, and standard browsing times, and are respectively the weight factors of the preset browsing duration and the weight factor of the browsing times, , , , is the weight factor of each preset long-distance path node, , .

8. The method for pushing refueling service information according to claim 7, wherein The specific analysis process for obtaining the gas station activity push plan is as follows: The refueling service data of the long-distance path includes the recommendation rate, usage rate, and usage amount of various oil products for each distance, and then obtain the recommendation rate, usage rate, and usage amount of various oil products for each pre-used long-distance path of the target user. The refueling consumption preference of the target user is: the refueling preference index of various oil products of the target user. Substitute the recommendation rate, usage rate, usage amount, and refueling preference index of various oil products for each pre-used long-distance path of the target user into the long-distance refueling preference index calculation formula to obtain the long-distance refueling preference index of various oil products for each pre-used long-distance path of the target user. Select the oil product with the maximum long-distance refueling preference index as the pre-used long-distance oil product for each pre-used long-distance path of the target user; Obtain the oil product sales preference of each gas station for each long-distance path from the cloud database. If the pre-used long-distance oil product of the target user belongs to the oil product sales preference of a certain gas station corresponding to the pre-used long-distance path, it indicates that this gas station is the preset long-distance used gas station for this pre-used long-distance path of the target user, and thus obtain each preset long-distance used gas station for each pre-used long-distance path of the target user; Gas Station Activity Push Plan: When the target user uses a gas station for preferential activities during each preset long-distance journey, a push notification is sent to the target user. At the same time, when the target user drives into a certain pre-used long-distance route, the gas stations corresponding to the pre-used long-distance route are pushed; The calculation formula for the long-distance refueling preference index is as follows: , where is the long-distance refueling preference index of the target user for Class B oil products on the long-distance path g to be used, h is the number of each long-distance path to be used by the target user, and the value of h is a positive integer, , and are respectively the recommended rate, usage rate, and usage amount of Class B oil products on the long-distance path h to be used by the target user, , and are respectively the preset standard recommended rate, standard usage rate, and standard usage amount, , and are respectively the preset recommended rate weight factor, usage rate weight factor, and usage amount weight factor, , , , .

9. The fueling service information push method according to claim 1, wherein The process of uploading the recommended data for cloud long-distance refueling services is as follows: Obtain the long-distance route recommendation selection rate of each cycle of various unit cycles of the target user from the cloud database. According to the analysis method of the recommendation selection rate of each cycle of various unit cycles of the target user, analyze the long-distance route recommendation selection rate of each cycle of various unit cycles of the target user to obtain the data effective evaluation index of the target user's current long-distance refueling service recommended data. When the data effective evaluation index of the target user's current long-distance refueling service recommended data is greater than the preset standard data effective evaluation index, upload the target user's current long-distance refueling service recommended data to the cloud.

10. A gas station service system applying the fueling service information push method according to any one of claims 1-9, characterized in that, It includes the following modules: The sales data processing module is used to upload the gas station sales data to the cloud database after the gas station sales, obtain the refueling service data of each gas station from the gas station sales data in the cloud database, and analyze the refueling service data of each gas station to obtain the fuel sales preferences of each gas station; The refueling service push module is used to collect the driving data of the target user, analyze the driving data of the target user to obtain the preset gas stations required by the target user, obtain the usage data of the target user from the cloud database, analyze the usage data of the target user to obtain the refueling consumption preferences of the target user, and then set the refueling service recommendation plan for the target user. At the end of the target user's driving, upload the recommended data for basic cloud refueling services; The gas station activity push module is used to recommend a refueling communication forum based on the record of the target user's cloud refueling service recommended data, and then collect the browsing records of the target user's refueling communication forum, analyze to obtain the pre-used long-distance routes of the target user, obtain the refueling service data of the long-distance routes from the cloud database, and analyze according to the refueling consumption preferences of the target user and the refueling service data of the long-distance routes to obtain the gas station activity push plan. At the end of the target user's long-distance driving, upload the recommended data for cloud long-distance refueling services; The cloud database is used to store the refueling service data of each gas station, the refueling service correction factors corresponding to each refueling service correction index, the seasonal refueling service correction factors of various oil products, the date refueling service correction factors of various oil products, the usage data of the target user, the refueling correction factor of the current temperature, the available gas stations at each path point, the distances between adjacent path points of the current path, the recommendation selection rates of each cycle of various unit cycles of the target user, the data effective index corresponding to the slope of each recommendation selection rate change curve, the refueling service data of the long-distance routes, the fuel sales preferences of the gas stations on each long-distance route, and the long-distance route recommendation selection rates of each cycle of various unit cycles of the target user.

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