A channel site selection method and device, electronic equipment and readable storage medium

Abstract

Embodiments of the present application provide a channel site selection method and device, electronic equipment and readable storage medium, the method comprising: for each target region for channel site selection, obtaining base station parameter information in each target region and user signaling data within the range of the base station. According to the base station parameter information and the signaling data, a feature analysis is performed to obtain a plurality of characteristic factors. The first object channel benefit model is constructed by using the first characteristic factor and the second characteristic factor, and the target channel net point is selected based on the first object channel benefit model, and the first object is channel site selected according to the target channel net point. By using the present scheme, the problem of low efficiency and accuracy of channel site selection caused by manual selection of channel construction site is avoided, which is beneficial to business development. In addition, the second object in competition with the first object is also considered as a factor of the channel benefit of the first object, and the channel site selection of the first object is reliable, which is further beneficial to business development.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a channel location method, apparatus, electronic device, and readable storage medium. Background Technology

[0002] With the continuous development of science and technology, the needs of various industries for business development and competition, as well as the location selection of offline channel outlets, are crucial to business development. For example, the location selection of offline channel outlets for the three major telecom operators directly affects their business development and profits.

[0003] In some scenarios, channel site selection primarily relies on manual methods. This involves first subjectively identifying several general areas, followed by on-site surveys to investigate pedestrian traffic, competition, transportation, and the overall business environment, ultimately selecting the location for channel construction. However, this method is prohibitively expensive in terms of human and material resources and is inherently subjective. The efficiency and accuracy of channel site selection are low, and its limitations are significant, which is detrimental to business development. Summary of the Invention

[0004] The purpose of this invention is to provide a channel location method, apparatus, and electronic device to solve the problems of low efficiency and accuracy and large limitations in channel location selection.

[0005] To solve the above-mentioned technical problems, the embodiments of the present invention are implemented as follows:

[0006] In a first aspect, embodiments of the present invention provide a channel location selection method, including:

[0007] For each target area where channel location is selected, obtain base station parameter information and user signaling data within each target area;

[0008] Based on the base station parameter information and the user signaling data, feature analysis is performed to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object. The first object and the second object are in a competitive relationship.

[0009] Construct a channel benefit model for the first object using the first feature factor and the second feature factor;

[0010] Based on the channel efficiency model of the first object, target channel outlets are selected, and the efficiency of the target channel outlets meets the preset requirements.

[0011] Channel site selection is performed on the first object based on the target channel network.

[0012] Secondly, embodiments of the present invention provide a channel location selection device, the device comprising:

[0013] The acquisition module is used to acquire base station parameter information and user signaling data within each target area for channel location selection.

[0014] The analysis module is used to perform feature analysis based on the base station parameter information and the signaling data to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object, wherein the first object and the second object are in a competitive relationship.

[0015] A construction module is used to construct a channel benefit model for the first object using the first feature factor and the second feature factor.

[0016] The selection module is used to select target channel outlets based on the channel benefit model of the first object, wherein the benefit of the target channel outlets meets preset requirements.

[0017] The site selection module is used to select a channel location for the first object based on the target channel outlets.

[0018] Thirdly, embodiments of the present invention provide an electronic device, including a processor, a communication interface, a memory, and a communication bus; wherein the processor, the communication interface, and the memory communicate with each other via the bus; the memory is used to store computer programs; and the processor is used to execute the programs stored in the memory to implement the channel addressing method steps as described in the first aspect.

[0019] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the channel location method steps as described in the first aspect.

[0020] As can be seen from the technical solutions provided by the above embodiments of the present invention, for each target area for channel site selection, base station parameter information and user signaling data within the base station range of each target area are obtained. Then, feature analysis is performed based on the base station parameter information and signaling data to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object. The first object and the second object are in a competitive relationship. A channel benefit model of the first object is constructed using each feature factor, and target channel outlets are selected based on the channel benefit model of the first object, with the benefit of the target channel outlets meeting preset requirements. Finally, channel site selection is performed for the first object based on the target channel outlets. This solution avoids the problem of low efficiency and accuracy in channel site selection caused by manual selection of channel construction locations, which is beneficial to business development. In addition, the second object, which is in a competitive relationship with the first object, is also considered as a factor in the channel benefit of the first object, resulting in high reliability of channel site selection for the first object, which further benefits business development. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the first process of the channel location selection method provided in an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of a second process for the channel location selection method provided in an embodiment of the present invention;

[0024] Figure 3A This is a schematic diagram of the third process of the channel location selection method provided in the embodiments of the present invention;

[0025] Figures 3B to 3C This is a schematic diagram of the distribution of channel outlets provided in an embodiment of the present invention;

[0026] Figure 4 A schematic diagram of the module composition of the channel location selection device provided in an embodiment of the present invention;

[0027] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0028] This invention provides a channel location selection method, apparatus, and electronic device.

[0029] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0030] In some application scenarios, the needs of various industries for business development and competition, as well as the location selection of offline channel outlets, are crucial to business growth. For example, the location selection of offline channel outlets for the three major telecom operators directly affects their business development and profits. Traditionally, site selection is mainly done manually. First, several areas are subjectively identified, followed by on-site surveys to investigate pedestrian traffic, competition, traffic conditions, and the business environment, ultimately selecting the location for channel construction. However, this method is too costly in terms of manpower and resources, and it also involves a degree of individual subjectivity.

[0031] Furthermore, when selecting locations, the only factors considered are the number of permanent residents, the number of transient residents, and job categories to determine the network of outlets for the channel. However, this method fails to evaluate the selected locations based on user demographic information (such as age and service waiting time), competitor channel network information, and development benefits, resulting in significant limitations.

[0032] like Figure 1 As shown, this embodiment of the invention provides a channel location selection method. This method provides a channel location selection scheme for a first object, which can be at least a mobile operator. The execution entity of this method can be a server, which can be a standalone server or a server cluster composed of multiple servers. Furthermore, the server can be a server capable of performing channel location selection. Specifically, the method may include the following steps:

[0033] In S101, for each target area where channel location is selected, the base station parameter information and user signaling data within each target area are obtained.

[0034] Specifically, when selecting channel locations for a county, city, or province, the entire area can first be divided into multiple regional blocks (as target areas). Then, base station parameter information for each regional block and user signaling data within each base station range in each regional block can be obtained from the national base station parameter information database.

[0035] For example, the national base station parameter information database may include China Mobile's base station parameter information database, China Telecom's base station parameter information database, and China Unicom's base station parameter information database. The base station parameter information database may contain at least the following information: country (MCC), operator (MNC), 0 representing China Mobile, cell code (LAC), base station code (CELL), base station latitude (LNG), base station longitude (LAT), base station coverage area (unit: meters, radius) (PRECISION), and base station address (ADDRESS).

[0036] For example, W represents the i-th region block. i Base station parameter information W of all base stations under its jurisdiction iL Then the i-th region block W i The base station parameter information can be recorded as Among them, l i This represents the number of base stations in the i-th region block. The base station parameter information for each base station includes, but is not limited to, base station code number, base station latitude and longitude, base station coverage area, and the type of area covered (e.g., residential cell, school, commercial area). For example, the base station parameter information for the first base station in the i-th region block can be represented as follows: Where s represents the number of base station parameter information under the first base station.

[0037] Furthermore, user signaling data includes, but is not limited to, the base station number of the user's current network access device (such as a mobile phone), the duration of stay on the same base station number, the location of the current network access device, the Internet data packets generated by the network access device, the latitude and longitude of the base station where the network access device is located, the type of base station where the network access device is located, the services activated by the user, the operator to which the user's network access device belongs, and the user's age.

[0038] Specifically, within the observation period, base station parameter information and signaling data of the user during that period are selected. The observation period can be relatively long, such as three calendar months, to ensure the reliability of the selected data.

[0039] For example, user signaling data can be collected within the observation period. This observation period can be divided into weekday daytime (e.g., 6:00 AM to 7:00 PM), weekday nighttime entertainment hours (e.g., 7:00 PM to 11:00 PM), and weekday nighttime rest hours (e.g., 11:00 PM to 6:00 AM); weekend daytime (e.g., 7:00 AM to 6:00 PM), weekend nighttime entertainment hours (e.g., 6:00 PM to 12:00 AM), and weekend nighttime rest hours (e.g., 12:00 AM to 7:00 AM); and holiday daytime (e.g., 6:00 AM to 6:00 PM), holiday nighttime entertainment hours (e.g., 6:00 PM to 12:00 AM), and weekend nighttime rest hours (e.g., 12:00 AM to 6:00 AM). The observation period is denoted as T = {t1, t2, L, to}, where t o This refers to the 0th time period, where 0 can be 1 to n. n is determined based on the number of time periods divided.

[0040] Furthermore, users within the observation period can be further segmented by age, dividing them into multiple age groups, such as 10-20 years old, 20-30 years old, 30-40 years old, 40-50 years old, etc.

[0041] Furthermore, users within the observation period can be further segmented by gender, dividing them into males and females.

[0042] After classifying the above observation periods into time periods, signaling data of users' network access devices (such as mobile phones) are collected according to the time periods. The signaling data collected by the j-th base station under the i-th area block in the p-th time period is denoted as... The specific formula is as follows:

[0043]

[0044] Where r represents the number of signaling features in the signaling data. This indicates the number of users whose data was collected.

[0045] For example, signaling features include, but are not limited to, collection time, base station identifier, duration of user stay at base station, and type of area covered by base station.

[0046] It is worth noting that the collected signaling data and base station parameter information include not only the data of the first object, but also the data of the second object that competes with the first object.

[0047] In S102, feature analysis is performed based on base station parameter information and signaling data to obtain multiple feature factors. The feature factors include the first feature factor of the first object and the second feature factor of the second object. The first object and the second object are in a competitive relationship.

[0048] Specifically, after obtaining the base station parameter information and signaling data, a hierarchical clustering algorithm can be used to classify users based on the base station parameter information and signaling data of each regional block.

[0049] For example, all signaling data within the observation period of the j-th base station belonging to the i-th region block. Feature analysis is performed. The user types of the j-th base station under the i-th region block within the observation period are categorized into permanent residents, staff, recreational users, and other users. Permanent residents, staff, recreational users, and other users are used as feature factors; each age group is used as a feature factor; and different genders are used as feature factors.

[0050] It is worth noting that the characteristic factors include not only the first characteristic factor of the first object but also the second characteristic factor of the second object. By treating both the first and second characteristic factors as characteristic factors, the second object, as a competitor, is considered as a factor in channel location selection, thus improving the reliability of channel location selection.

[0051] For example, the feature factor of the first proprietary channel of the first object under the i-th region block is denoted as... Where m represents the number of feature factors.

[0052] In S103, the channel benefit model of the first object is constructed using the first characteristic factor and the second characteristic factor.

[0053] For example, in this embodiment of the invention, the first feature factor and the second feature factor are collectively referred to as feature factors. As an optional implementation of S103, S103 includes the following steps:

[0054] Calculate the contribution weight of each characteristic factor to the channel's effectiveness. Use the contribution weight and the channel effectiveness of each characteristic factor to its respective channel as input to construct the channel effectiveness model.

[0055] Specifically, when calculating the contribution weight of each characteristic factor to channel benefits, the costs generated by users corresponding to each characteristic factor within the channel are first calculated. The contribution weight to the channel benefits is determined according to the level of these costs. For characteristic factors generating the same costs, the contribution weight can be equal. In essence, the contribution weight of costs is directly proportional to the contribution weight to channel benefits.

[0056] For example, if the feature factors include permanent residents, staff, entertainers, males, females, children, and adults, and the costs incurred by permanent residents, staff, entertainers, males, females, children, and adults within this channel are 50,000, 30,000, 20,000, 50,000, 40,000, 10,000, and 40,000 respectively, then the feature factors are ranked according to the cost, as follows: permanent residents, males, females, adults, staff, entertainers, and children. The contribution weights for permanent residents, males, females, adults, staff, entertainers, and children can be set to 0.2, 0.2, 0.15, 0.15, 0.1, 0.05, and 0.025 respectively.

[0057] It is worth noting that the contribution weight can be selected as other values ​​according to the actual situation, and this application embodiment does not limit it.

[0058] After calculating the contribution weights, the benefits of each characteristic factor to the channel are used as inputs to construct a channel benefit model, which can be expressed by the following formula:

[0059] y = a0 + a1x1 + a2x2 + ... + a n x n

[0060] Where y is the output of the channel benefit model, a0 is a constant, a1 is the contribution weight of feature factor 1, x1 is the benefit brought to the channel by feature factor 1, a2 is the contribution weight of feature factor 2, and x2 is the benefit brought to the channel by feature factor 2. n The contribution weight of feature factor n, x n Let n be the benefit that characteristic factor brings to the channel. The final benefit of the channel is obtained by summing the benefits brought to the channel by each characteristic factor.

[0061] In step S104, target channel outlets are selected based on the channel efficiency model of the first object. The efficiency of the target channel outlets meets preset requirements. Specifically, the preset requirements can be customized by the first object, and can be set according to the needs of the first object itself. For example, if the preset requirements are set as a threshold, channel outlets whose calculated efficiency exceeds the threshold are selected as target channel outlets that meet the preset requirements.

[0062] Furthermore, the preset requirements of the embodiments of the present invention can also be determined through the following steps:

[0063] A benefit prediction model for the second object is constructed using the second characteristic factor. Preset requirements are determined based on the prediction results of the benefit prediction model.

[0064] Specifically, constructing a benefit prediction model for the second object using the second characteristic factor includes:

[0065] Calculate the contribution weight of each second characteristic factor to the channel benefit. Use the contribution weight and the channel benefit of the second characteristic factor to the channel to which the second object belongs as input to construct the channel benefit model of the second object.

[0066] Specifically, when calculating the contribution weight of each secondary characteristic factor to channel effectiveness, the costs incurred by the users corresponding to each secondary characteristic factor are first calculated. The contribution weight to channel effectiveness is determined according to the level of cost. In particular, the contribution weight of cost to channel effectiveness is directly proportional.

[0067] After calculating the contribution weights, the channel benefit model of the second object is constructed by taking the benefits generated by each second characteristic factor on the channel as input.

[0068] In S105, channel site selection is performed for the first target based on the target channel outlets.

[0069] Specifically, after selecting the target channel outlets, the first target involves channel site selection. Specifically, the locations of the target channel outlets are chosen as the locations for the first target's outlet construction.

[0070] As can be seen from the technical solutions provided by the above embodiments of the present invention, for each target area for channel site selection, base station parameter information and user signaling data within the base station range of each target area are obtained. Then, feature analysis is performed based on the base station parameter information and signaling data to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object. The first object and the second object are in a competitive relationship. A channel benefit model of the first object is constructed using each feature factor, and target channel outlets are selected based on the channel benefit model of the first object, with the benefit of the target channel outlets meeting preset requirements. Finally, channel site selection is performed for the first object based on the target channel outlets. This solution avoids the problem of low efficiency and accuracy in channel site selection caused by manual selection of channel construction locations, which is beneficial to business development. In addition, the second object, which is in a competitive relationship with the first object, is also considered as a factor in the channel benefit of the first object, resulting in high reliability of the first object's site selection, which is also beneficial to business development.

[0071] Furthermore, such as Figure 2 As shown, there are many different ways to process S104. Here is another optional implementation method. For details, please refer to the processing of S1041-S1042 below.

[0072] In S1041, the benefits of the existing channel network of the first object within each target area are calculated using the channel location model of the first object.

[0073] Specifically, after constructing the channel location model, the characteristic factors of the existing channel outlets of the first object in each target area (waiting time for users to handle business, type of business handled by users, user type, gender, etc.) and the benefits of each characteristic factor to their respective channels are used as inputs to the channel location model to calculate the benefits of each existing channel.

[0074] In S1042, the first channel outlet among the existing channel outlets of the first object that meets the preset requirements in terms of efficiency is selected as the target channel outlet.

[0075] Specifically, the preset requirements can be referenced in S104, and will not be repeated here in this embodiment of the invention.

[0076] As can be seen from the technical solutions provided by the above embodiments of the present invention, the efficiency of the channel is used as a condition for selecting the channel. Only channels whose efficiency meets the preset requirements are selected as target channel outlets. This further facilitates business development.

[0077] Furthermore, such as Figure 3A As shown, this embodiment of the invention provides another channel location selection method. The execution subject of this method can be a server, which can be an independent server or a server cluster composed of multiple servers. Moreover, the server can be a server capable of performing channel location selection. Specifically, this method may include the following steps S106-S115:

[0078] In S106, for each target area where channel location is selected, the base station parameter information within each target area, the user signaling data within the range of each base station, the parameter information of the existing channels of the first object, and the channel parameter information of the second object are collected.

[0079] Specifically, the base station parameter information and user signaling data within each target area can be found in the description of the above embodiments.

[0080] The parameter information of the existing channels of the first object refers to the parameter information of the existing proprietary channels of the first object. The parameter information of each channel includes, but is not limited to, channel code, channel latitude and longitude, channel size, business development volume during the observation period, average waiting time for users to handle business, and business revenue.

[0081] For example, the parameter information of all proprietary channels of the first object can be denoted as W. iM , Where, m i This represents the number of proprietary channels in the i-th region block. For example, the parameter information of the first proprietary channel of the first object under the i-th region block can be represented as... m represents the number of parameters collected from our own channels.

[0082] The channel parameter information for the second object refers to the parameter information of the second object's existing proprietary channels. The parameter information for each channel includes, but is not limited to, channel code, channel latitude and longitude, channel size, business development volume during the observation period, average waiting time for users to handle business, and business revenue.

[0083] For example, the parameter information of all proprietary channels of the second object can be denoted as W. iN , Where, n iThis represents the number of proprietary channels of the second object in the i-th region block. For example, the parameter information of the first proprietary channel of the second object in the i-th region block can be represented as... Where n represents the number of parameters of the channel of the second object collected.

[0084] In S107, feature analysis is performed based on base station parameter information, signaling data, and existing channel parameter information of the first object to obtain multiple feature factors. These feature factors include a first feature factor for the first object and a second feature factor for the second object.

[0085] Specifically, the descriptions of the first and second characteristic factors can be found in the above embodiments. The third characteristic factor within the first characteristic factor may include at least the user's waiting time for processing the transaction, the type of transaction processed, etc.

[0086] In S108, a channel benefit model for the first object is constructed using various characteristic factors. These characteristic factors include a first characteristic factor (which contains a third characteristic factor) and a second characteristic factor.

[0087] Specifically, in S103 above, a channel benefit model for the first object is constructed using the first and second feature factors. Based on S103, the number and types of feature factors are expanded. For example, the feature information of the first self-owned channel under the i-th region block is... Become m+m1 represents the number of feature factors. Compared to the number of feature factors in step S103, the number of feature factors in S107 has increased by m1. The feature factors in S107 include, but are not limited to, permanent residents, staff, entertainment personnel and other personnel, each age group, gender, waiting time for users to handle business, and type of business handled by users.

[0088] When constructing the channel benefit model, it can be referred to in conjunction with step S103, and the embodiments of the present invention will not be described in detail here.

[0089] The final channel benefit model for the first object is as follows:

[0090]

[0091] Where y is the output of the channel benefit model, a0 is a constant, a1 is the contribution weight of feature factor 1, x1 is the benefit brought to the channel by feature factor 1, a2 is the contribution weight of feature factor 2, and x2 is the benefit brought to the channel by feature factor 2. n The contribution weight of feature factor n, x n The characteristic factor n represents the benefits brought by the channel. The contribution weights of the feature factor n+m1, Let n+m1 be the benefit brought to the channel by the characteristic factor. The final benefit of the channel is obtained by summing up the benefits brought to the channel by each characteristic factor.

[0092] In S109, the channel benefit model of the first object is used to calculate the benefits of the existing channel network of the first object in each target area.

[0093] In S110, the first channel outlet that meets the preset benefit requirements among the existing channel outlets of the first object is taken as the target channel outlet, and the channel site selection of the first object is carried out according to the target channel outlet.

[0094] The preset requirements can be customized by the first object, and can be set according to the needs of the first object itself. For example, if the preset requirements are set as a threshold, the channel outlets whose calculated benefits exceed the threshold will be the target channel outlets that meet the preset requirements.

[0095] Furthermore, the preset requirements can also be determined based on the prediction results of the benefit prediction model for the second object mentioned in step S104. Specific details can be found in conjunction with S104, and will not be elaborated further in this embodiment of the invention.

[0096] In S111, for the second channel outlet among the existing channel outlets of the first object whose benefits do not meet the preset requirements, the first base station to which the second channel outlet belongs is determined.

[0097] Specifically, the second channel outlet can be denoted as "W". iM The attribution relationship between the second channel outlets and base stations is denoted as W. iML As an optional implementation of S110, the first base station to which the second channel network point belongs can be determined based on the Manhattan distance algorithm, using the second channel network point W”. iM The location information of each base station within the target area and the location information of the second channel outlet determine the first base station to which the second channel outlet belongs.

[0098] The Manhattan distance algorithm for determining the first base station to which the second channel network point belongs involves: calculating the first difference between the longitude coordinates of the second channel network point and the longitude coordinates of all base stations within the target area where the second channel network point is located; calculating the second difference between the latitude coordinates of the second channel network point and the latitude coordinates of all base stations within the target area where the second channel network point is located; taking the absolute values ​​of both the first and second differences and summing the two absolute values; and selecting the base station with the smallest sum as the first base station.

[0099] For example, when determining the first base station to which the second channel network belongs, the proprietary channel W of the first object belonging to the i-th regional block is first calculated.iM The latitude and longitude of the j-th proprietary channel and the base station W of the first object belonging to the i-th regional block. iL The distance between the latitude and longitude of the k-th base station is denoted as . in,

[0100]

[0101] in, Indicates the proprietary channel W under the i-th block. iM The longitude coordinates of the j-th self-owned channel in the middle. Indicates the proprietary channel W under the i-th block. iM The latitude coordinates of the j-th self-owned channel. Indicates the base station W under the i-th region block iL The longitude coordinates of the k-th base station in the middle. Indicates the base station W under the i-th region block iL The latitude coordinates of the k-th base station.

[0102] For each distance calculated using the above formula, take... Therefore, the base station corresponding to the minimum distance is designated as the first base station to which the second channel network belongs.

[0103] In S112, the effective Manhattan coverage distance of the first channel network point is calculated based on the Manhattan distance algorithm.

[0104] Specifically, according to the distance calculation formula of the Manhattan distance algorithm in S110, the latitude and longitude of each base station in the target area where the first channel network point is located are calculated, as well as the absolute value of the difference between the latitude and longitude of the first channel network point. Each absolute value is taken as the distance between the first channel network point and each base station in the target area. The minimum value among all distances is selected as the effective Manhattan coverage distance.

[0105] In S113, virtual channel outlets are established with the first base station as the center and the effective Manhattan coverage distance as the radius.

[0106] For example, with the location of the first base station as the center O and the effective Manhattan coverage distance R as the radius, virtual channel points are set up within the circular area formed by the effective Manhattan distance. For example, when setting up virtual channel points within the circular area, they can be evenly distributed (e.g., Figure 3B The virtual channel outlets shown are 1, 2, 3, and 4. Non-uniform distribution is also possible (e.g., ...). Figure 3C Virtual channel outlets 5, 6, and 7 are shown.

[0107] In S114, the benefits of virtual channel outlets are calculated using the channel benefit model of the first object.

[0108] Specifically, the benefits of virtual channel outlets are calculated according to the model shown in S107.

[0109] In S115, for a target virtual channel outlet whose benefits meet the preset requirements, if the second channel outlet is within the coverage range of the effective Manhattan coverage distance, the target virtual channel outlet is used as the target channel outlet and the second channel outlet is migrated to the target channel outlet; if the second channel outlet is not within the coverage range of the effective Manhattan coverage distance, the target virtual channel outlet is used as the target channel outlet and a new one is created.

[0110] It is worth noting that, Figure 3A The other channel location method provided can be referred to in the same way as the above embodiments, and the embodiments of this application will not be described in detail here.

[0111] As can be seen from the technical solutions provided by the above embodiments of the present invention, for each target area for channel site selection, base station parameter information and user signaling data within the base station range of each target area are obtained. Then, feature analysis is performed based on the base station parameter information and signaling data to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object. The first object and the second object are in a competitive relationship. A channel benefit model of the first object is constructed using each feature factor, and target channel outlets are selected based on the channel benefit model of the first object, with the benefit of the target channel outlets meeting preset requirements. Finally, channel site selection is performed for the first object based on the target channel outlets. This solution avoids the problem of low efficiency and accuracy in channel site selection caused by manual selection of channel construction locations, which is beneficial to business development. In addition, the second object, which is in a competitive relationship with the first object, is also considered as a factor in the channel benefit of the first object, resulting in high reliability of the first object's site selection. This further benefits business development.

[0112] Furthermore, user characteristics are analyzed based on user signaling data, and a channel benefit model is constructed using these user characteristic factors. Channels that meet the benefit requirements are then selected as target channels and established. This improves the reliability of the selected target channels, and since the selection is based on benefit, it is more conducive to business development.

[0113] Corresponding to the channel location method provided in the above embodiments, based on the same technical concept, the present invention also provides a channel location device. Figure 4 This is a schematic diagram of the module composition of a channel location selection device provided in an embodiment of the present invention. The channel location selection device is used to perform... Figures 1 to 3A The described channel location selection method, such as Figure 4As shown, the channel location selection device includes: an acquisition module 401, an analysis module 402, a construction module 403, and a selection module 404.

[0114] The acquisition module 401 is used to acquire base station parameter information and user signaling data within each target area for channel location selection.

[0115] Analysis module 402 is used to perform feature analysis based on base station parameter information and signaling data to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object. The first object and the second object are in a competitive relationship.

[0116] Module 403 is used to construct a channel benefit model for the first object using the first feature factor and the second feature factor;

[0117] The selection module 404 is used to select target channel outlets based on the channel benefit model of the first object, and to select a channel location scheme with the target channel outlets as the first object. The benefits of the target channel outlets meet the preset requirements.

[0118] The location selection module 405 is used to select the channel location for the first object based on the target channel outlets.

[0119] As can be seen from the technical solution provided by the above embodiments of the present invention, for each target area for channel site selection, the acquisition module acquires base station parameter information and user signaling data within the base station range of each target area. Then, the first analysis module performs feature analysis based on the base station parameter information and signaling data to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object. The first object and the second object are in a competitive relationship. The construction module uses each feature factor to construct a channel benefit model for the first object, and the selection module selects target channel outlets based on the channel benefit model of the first object, ensuring that the benefit of the target channel outlets meets preset requirements. The site selection module performs channel site selection for the first object based on the target channel outlets. This solution avoids the problem of low efficiency and accuracy in channel site selection caused by manual selection of channel construction locations, which is beneficial to business development. In addition, the second object, which is in a competitive relationship with the first object, is also considered as a factor in the channel benefit of the first object, resulting in high reliability of the first object's site selection. This further benefits business development.

[0120] Optionally, the analysis module 402 includes: an analysis unit;

[0121] The analysis unit is used to analyze the channel parameter information to obtain the third feature factor, wherein the first feature factor includes the third feature factor.

[0122] Optionally, building module 403 includes:

[0123] The calculation unit is used to calculate the contribution weights of the first characteristic factor and the second characteristic factor to the benefits of the respective channel;

[0124] The building unit is used to construct a channel benefit model by taking the contribution weight and the first and second characteristic factors as inputs to the channel benefit model.

[0125] Optionally, building module 403 includes:

[0126] A building unit is used to construct a benefit prediction model for a second object using the second feature factor;

[0127] The determination unit is used to determine preset requirements based on the prediction results of the benefit prediction model.

[0128] Optionally, module 404 may include:

[0129] The calculation unit uses the channel location model of the first object to calculate the benefits of the existing channel network of the first object in each target area;

[0130] Select the first channel outlet among the existing channel outlets of the first object that meets the preset efficiency requirements as the target channel outlet.

[0131] Optionally, the selection module 404 further includes:

[0132] The determining unit is used to determine the first base station to which the second channel outlet belongs, given that the benefits of the second channel outlet among the existing channel outlets of the first object do not meet the preset requirements.

[0133] The calculation unit is used to calculate the effective Manhattan coverage distance of the first channel network point based on the Manhattan distance algorithm;

[0134] A unit is established to set up virtual channel outlets with the first base station as the center and the effective Manhattan coverage distance as the radius.

[0135] The calculation unit is used to calculate the benefits of virtual channel outlets using the channel benefit model of the first object;

[0136] The migration unit is used to target virtual channel outlets whose benefits meet preset requirements. If the second channel outlet is within the coverage range of the effective Manhattan coverage distance, the target virtual channel outlet is used as the target channel outlet and the second channel outlet is migrated to the target channel outlet.

[0137] A new unit is created to use the target virtual channel point as the target channel point and create a new one if the second channel point is not within the coverage range of the effective Manhattan coverage distance.

[0138] Optionally, the determining unit includes:

[0139] The determination sub-unit is used to determine the first base station to which the second channel network point belongs, based on the Manhattan distance algorithm, using the location information of each base station in the target area where the second channel network point is located and the location information of the second channel network point itself.

[0140] The calculation subunit is used to calculate the effective Manhattan coverage distance based on the location information of the base station in the target area where the first channel network point is located and the location information of the first channel network point, according to the Manhattan distance algorithm.

[0141] The channel location device provided in this embodiment of the invention can realize the various processes in the embodiments corresponding to the above-mentioned channel location method. To avoid repetition, it will not be described again here.

[0142] It should be noted that the channel location device provided in this embodiment of the invention and the channel location method provided in this embodiment of the invention are based on the same inventive concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned channel location method, and the repeated parts will not be described again.

[0143] Corresponding to the channel location method provided in the above embodiments, based on the same technical concept, this embodiment of the invention also provides an electronic device for executing the above-described channel location method. Figure 5 To illustrate the structure of an electronic device according to various embodiments of the present invention, as shown in the schematic diagram... Figure 5 As shown. Electronic devices can vary considerably due to differences in configuration or performance, and may include one or more processors 501 and memory 502. Memory 502 may store one or more application programs or data. Memory 502 may be temporary or persistent storage. The application programs stored in memory 502 may include one or more modules (not shown), each module may include a series of computer-executable instructions for the electronic device. Furthermore, processor 501 may be configured to communicate with memory 502 and execute the series of computer-executable instructions in memory 502 on the electronic device. The electronic device may also include one or more power supplies 503, one or more wired or wireless network interfaces 504, one or more input / output interfaces 505, and one or more keyboards 506.

[0144] Specifically, in this embodiment, the electronic device includes a processor, a communication interface, a memory, and a communication bus; wherein, the processor, the communication interface, and the memory communicate with each other via the bus; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to implement the following method steps:

[0145] For each target area where channel site selection is performed, obtain base station parameter information and user signaling data within each target area;

[0146] Based on the base station parameter information and user signaling data, feature analysis is performed to obtain multiple feature factors. The feature factors include the first feature factor of the first object and the second feature factor of the second object. The first object and the second object are in a competitive relationship.

[0147] A channel benefit model for the first object is constructed using the first and second characteristic factors.

[0148] Target channel outlets are selected based on the channel efficiency model of the first object, and the efficiency of the target channel outlets meets the preset requirements.

[0149] Channel site selection is carried out for the first target based on the target channel network.

[0150] This application embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the following method steps:

[0151] For each target area where channel site selection is performed, obtain base station parameter information and user signaling data within each target area;

[0152] Based on the base station parameter information and user signaling data, feature analysis is performed to obtain multiple feature factors. The feature factors include the first feature factor of the first object and the second feature factor of the second object. The first object and the second object are in a competitive relationship.

[0153] A channel benefit model for the first object is constructed using the first and second characteristic factors.

[0154] Target channel outlets are selected based on the channel efficiency model of the first object, and the efficiency of the target channel outlets meets the preset requirements.

[0155] Channel site selection is carried out for the first target based on the target channel network.

[0156] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0157] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0158] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0159] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0160] In a typical configuration, an electronic device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0161] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0162] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0163] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0164] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0165] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A channel site selection method, characterized in that, The method includes: For each target area where channel location is selected, obtain base station parameter information and user signaling data within each target area; Based on the base station parameter information and the user signaling data, feature analysis is performed to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object. The first object and the second object are in a competitive relationship. A channel benefit model for the first object is constructed using the first feature factor and the second feature factor; Target channel outlets are selected based on the channel efficiency model of the first object, and the efficiency of the target channel outlets meets the preset requirements. Channel site selection is performed for the first object based on the target channel network; The selection of target channel outlets based on the channel efficiency model of the first object includes: The benefits of the existing channel network of the first object within each target area are calculated using the channel location model of the first object. The first channel outlet among the existing channel outlets of the first object that meets the preset requirements is taken as the target channel outlet; The selection of target channel outlets based on the channel efficiency model of the first object also includes: For the second channel outlet in the existing channel network of the first object whose benefits do not meet the preset requirements, determine the first base station to which the second channel outlet belongs; The effective Manhattan coverage distance of the first channel network point is calculated based on the Manhattan distance algorithm; A virtual channel network is established with the first base station as the center and the effective Manhattan coverage distance as the radius; The benefits of the virtual channel outlets are calculated using the channel benefit model of the first object; For a target virtual channel outlet whose benefits meet the preset requirements, if the second channel outlet is within the coverage range of the effective Manhattan coverage distance, then the target virtual channel outlet is designated as the target channel outlet and the second channel outlet is migrated to the target channel outlet; if the second channel outlet is not within the coverage range of the effective Manhattan coverage distance, then the target virtual channel outlet is designated as the target channel outlet and a new one is created.

2. The method according to claim 1, characterized in that, The first feature factor includes: the third feature factor; The third characteristic factor is obtained by analyzing the existing channel parameter information of the first object.

3. The method according to claim 2, characterized in that, The method of constructing the channel benefit model of the first object using the first feature factor and the second feature factor includes: Calculate the contribution weights of the first feature factor and the second feature factor to the benefits of their respective channels; The channel benefit model is constructed by using the contribution weight and the benefits of the first and second feature factors to the channel as inputs.

4. The method according to claim 1, characterized in that, Construct a benefit prediction model for the second object using the second feature factor; The preset requirements are determined based on the prediction results of the aforementioned benefit prediction model.

5. The method according to any one of claims 1-4, characterized in that, Based on the Manhattan distance algorithm, the location information of each base station within the target area where the second channel network point is located, and the location information of the second channel network point itself, are used to determine the first base station to which the second channel network point belongs. The effective Manhattan coverage distance is calculated based on the Manhattan distance algorithm, using the location information of the base station within the target area where the first channel outlet is located and the location information of the first channel outlet itself.

6. A channel location selection device, characterized in that, The device includes: The acquisition module is used to acquire base station parameter information and user signaling data within each target area for channel location selection; The analysis module is used to perform feature analysis based on the base station parameter information and the signaling data to obtain multiple feature factors. The feature factors include a first feature factor of a first object and a second feature factor of a second object, wherein the first object and the second object are in a competitive relationship. A construction module is used to construct a channel benefit model for the first object using the first feature factor and the second feature factor; The selection module is used to select target channel outlets based on the channel efficiency model of the first object, wherein the efficiency of the target channel outlets meets preset requirements; The site selection module is used to select a channel location for the first object based on the target channel outlets; In the selection module, selecting target channel outlets based on the channel benefit model of the first object includes: The benefits of the existing channel network of the first object within each target area are calculated using the channel location model of the first object. The first channel outlet among the existing channel outlets of the first object that meets the preset requirements is taken as the target channel outlet; The selection module, based on the channel benefit model of the first object, further includes selecting target channel outlets, including: For the second channel outlet in the existing channel network of the first object whose benefits do not meet the preset requirements, determine the first base station to which the second channel outlet belongs; The effective Manhattan coverage distance of the first channel network point is calculated based on the Manhattan distance algorithm; A virtual channel network is established with the first base station as the center and the effective Manhattan coverage distance as the radius; The benefits of the virtual channel outlets are calculated using the channel benefit model of the first object; For a target virtual channel outlet whose benefits meet the preset requirements, if the second channel outlet is within the coverage range of the effective Manhattan coverage distance, then the target virtual channel outlet is designated as the target channel outlet and the second channel outlet is migrated to the target channel outlet; if the second channel outlet is not within the coverage range of the effective Manhattan coverage distance, then the target virtual channel outlet is designated as the target channel outlet and a new one is created.

7. An electronic device, characterized in that, The system includes a processor, a communication interface, a memory, and a communication bus; wherein the processor, the communication interface, and the memory communicate with each other via the bus; the memory is used to store computer programs; and the processor is used to execute the programs stored in the memory to implement the channel addressing method steps as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the channel location method steps as described in any one of claims 1-5.

Images