CN110555711A - Data processing method, device, server and computer readable storage medium - Google Patents
Data processing method, device, server and computer readable storage medium Download PDFInfo
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Abstract
The invention provides a data processing method, a data processing device, a server and a computer readable storage medium, wherein the data processing method comprises the following steps: and responding to the information of the orders in the designated time period, and adjusting the estimated service amount of any order according to the constraint condition between the preset service amount and the total amount. By the technical scheme, the accuracy of capacity pricing is improved, the willingness of a driver to pick up orders is improved, the total volume of the operation platform is increased, the amount of the orders is not reduced, and the competitiveness and the market occupancy rate of the operation platform are improved.
Description
Technical Field
The invention relates to the technical field of capacity pricing, in particular to a data processing method, a data processing device, a server and a computer readable storage medium.
Background
The total commodity transaction amount (GMV) is the total transaction amount of a platform in a certain time period, is used as a transaction index, is one of important indexes of an evaluation platform, has the significance of the platform, and can also be used as an index for checking the health degree of transaction.
In the related art, competitive pricing or cost pricing is usually adopted for determining the capacity price so as to enlarge the share of the operation platform in the market, but when the competitive pricing or the cost pricing is adopted, the unit price of the capacity order is usually lower, the order accepting willingness of a capacity driver is further reduced, the total assembly and the payment of the operation platform are not improved, and the benign development of the operation platform is also not facilitated.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art or the related art.
To this end, it is an object of the present invention to provide a data processing method.
Another object of the present invention is to provide a data processing apparatus.
Another object of the present invention is to provide a server.
It is another object of the present invention to provide a computer-readable storage medium.
in order to achieve the above object, according to an embodiment of a first aspect of the present invention, there is provided a data processing method including: and responding to the information of the orders in the designated time period, and adjusting the estimated service amount of any order according to the constraint condition between the preset service amount and the total amount.
According to the technical scheme, the estimated service amount of any order is adjusted according to the constraint condition between the preset service amount and the total amount of the traffic, so that the accuracy of capacity pricing is improved, the willingness of a driver to receive orders is improved, the total amount of the traffic of the operation platform is improved, the amount of the traffic is not reduced, and the competitiveness and the market occupancy rate of the operation platform are improved.
According to an aspect of the second aspect of the present invention, there is provided a data processing apparatus including: and the adjusting unit is used for responding to the information of the orders in the designated time period and adjusting the estimated service amount of any order according to the constraint condition between the preset service amount and the total amount.
According to the technical scheme, the estimated service amount of any order is adjusted according to the constraint condition between the preset service amount and the total amount of the traffic, so that the accuracy of capacity pricing is improved, the willingness of a driver to receive orders is improved, the total amount of the traffic of the operation platform is improved, the amount of the traffic is not reduced, and the competitiveness and the market occupancy rate of the operation platform are improved.
According to a technical solution of a third aspect of the present invention, there is provided a server including: the data processing apparatus defined in any one of the second aspects of the present invention.
According to an aspect of the fourth aspect of the present invention, there is provided a computer-readable storage medium on which a computer program is stored, the computer program, when executed, implementing the data processing method as defined in any one of the aspects of the first aspect.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 shows a schematic flow diagram of a data processing method according to an embodiment of the invention;
FIG. 2 shows a schematic block diagram of a data processing apparatus according to an embodiment of the present invention;
FIG. 3 shows a schematic block diagram of a server according to one embodiment of the present invention;
FIG. 4 shows a schematic flow diagram of a method for platform aggregate volume optimization according to one embodiment of the present invention.
Detailed Description
in order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a schematic flow diagram of a data processing method according to an embodiment of the invention.
as shown in fig. 1, a data processing method according to an embodiment of the present invention includes: step S102, responding to the order information in the appointed time interval, and adjusting the estimated business amount of any order according to the constraint condition between the preset business amount and the total amount.
According to the technical scheme, the estimated service amount of any order is adjusted according to the constraint condition between the preset service amount and the total amount of the traffic, so that the accuracy of capacity pricing is improved, the willingness of a driver to receive orders is improved, the total amount of the traffic of the operation platform is improved, the amount of the traffic is not reduced, and the competitiveness and the market occupancy rate of the operation platform are improved.
In any of the above technical solutions, preferably, the adjusting the estimated transaction amount of any one of the orders according to a constraint condition between a preset transaction amount and a total amount in response to the information of the orders within the specified time period specifically includes: and when the estimated total amount of transaction is greater than or equal to a preset total amount of transaction and the estimated unit amount within the specified time period is greater than or equal to the preset unit amount, determining the value range of the estimated service amount according to the constraint condition, wherein a fitting relation exists between the estimated service amount and the estimated starting distance, the amount within the estimated starting distance and the mileage unit price outside the estimated starting distance, and the fitting relation is determined according to the service amount of a historical order, the historical starting distance, the amount within the historical starting distance and the mileage unit price outside the historical starting distance.
In the technical scheme, after the constraint condition is created, on one hand, the constraint condition is reversely solved through the preset total amount of the transaction, and then the value range of the estimated service amount is determined, wherein the estimated service amount is determined by the estimated starting distance, the amount in the estimated starting distance, the mileage unit price outside the estimated starting distance and the fitting relation, namely the value range of at least one variable of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance is determined, so that the total amount of the transaction can be effectively improved, on the other hand, the estimated unit amount change in a specified time period is considered while the estimated service amount is solved, and the fact is that more orders are stimulated, so that the further popularization and the market share expansion of an operation platform are facilitated.
In any of the above technical solutions, preferably, before responding to the information of the order within the specified time period, the method further includes: analyzing a historical starting distance corresponding to a service amount of a historical order, an amount in the historical starting distance, a driving distance outside the historical starting distance and a mileage unit price outside the historical starting distance; counting and determining the corresponding relation between the service amount of the historical order and the order forming conversion rate; determining a mapping relation between the travel distance of the historical order and the estimated finished order quantity; and determining the historical starting distance, the money amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the order-forming conversion rate determined by the corresponding relation and the mapping relation as the constraint condition of the total amount of the historical orders, wherein the order-forming conversion rate is a numerical value determined according to the proportion of the total amount of the historical orders to the estimated amount of the orders.
In the technical scheme, the historical starting distance, the amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the single conversion rate determined by the corresponding relation and the mapping relation are determined as the constraint conditions of the total sum of the historical orders, the single conversion rate is used as an intermediate variable, the influence trends of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance on the total sum can be determined respectively or comprehensively, the value ranges of any variable of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance can be determined by solving the optimal solution of the output variable (total sum) of the constraint conditions, and further, the value range of any variable can be determined according to the increment of the total sum, for example, the increase of the total amount of the transaction is marked as a% (a is more than or equal to 0), the starting distance, the mileage unit price and the amount of money in the starting distance which meet the increase of a% are determined, the accuracy of determining the starting distance, the mileage unit price and the amount of money in the starting distance is improved, and the increase of the total amount of the transaction and the market occupancy rate of the operation platform are improved while the increase of the total amount of the transaction is met.
Specifically, the service amount is used as an input variable, the form conversion rate is used as an output result, and based on the corresponding relationship between the service amount and the form conversion rate, the constraint condition may be a linear regression model, a naive bayes model, a GBDT (sparse Boost Decision Tree algorithm) model, an XGBOOST (open source iterative Tree algorithm) model, or the like, and the form conversion rate corresponding to the order price is obtained through a specified order price.
Furthermore, by adjusting the price of the order, a reasonable order conversion rate can be obtained, and the increase of the total order quantity and the total amount of the finished product can be facilitated.
It should be noted that the estimated order amount is the amount of all estimated bubbling order information, for example, in the network booking user interface, the user inputs information such as "start point", "end point" and "reserved time", and does not click "confirmation", that is, a bubbling order information is generated.
In any one of the above technical solutions, preferably, the constraint condition includes:GMV characterizes the total amount of traffic, Pi(D) Representing the service amount, Estcnt, of the ith historical capacity order in the corresponding distance intervali(D) Representing the predicted finished single quantity, Ratio, of the ith historical capacity order in the corresponding distance intervali(P (D)) representing the order-forming conversion rate corresponding to the ith historical capacity order, D representing the service distance of the ith historical capacity order, P (D) representing the service amount of the historical capacity order, n representing the total number of the historical capacity orders, wherein n is a positive integer greater than or equal to 1, the distance interval comprises a numerical interval in which the driving distance is less than or equal to the starting distance, and the distance interval further comprises a numerical interval in which the driving distance is greater than the starting distance.
According to the technical scheme, the total amount of the historical capacity order is calculated by determining the service amount of the historical capacity order in each distance interval, estimating the sum of the historical capacity order and the constraint conditions, whether the adjusted service amount can improve the total amount of the sum of the historical capacity order is used as a reference for comparison, and whether the adjusted service amount can improve the total amount of the sum of the historical capacity order is improved, so that the accuracy of judging whether the.
fig. 2 shows a schematic block diagram of a data processing device according to an embodiment of the present invention.
As shown in fig. 2, a data processing apparatus 200 according to an embodiment of the present invention includes: the adjusting unit 202 is configured to adjust the estimated transaction amount of any one of the orders according to a constraint condition between a preset transaction amount and a total amount in response to information of the orders within a specified time period.
According to the technical scheme, the estimated service amount of any order is adjusted according to the constraint condition between the preset service amount and the total amount of the traffic, so that the accuracy of capacity pricing is improved, the willingness of a driver to receive orders is improved, the total amount of the traffic of the operation platform is improved, the amount of the traffic is not reduced, and the competitiveness and the market occupancy rate of the operation platform are improved.
In any of the above technical solutions, preferably, the adjusting unit 202 includes: the determining subunit 2022 is configured to determine a value range of the estimated service amount according to the constraint condition when the estimated total amount of the estimated service is greater than or equal to a preset total amount of the estimated service, and the estimated unit amount in the specified time period is greater than or equal to a preset unit amount, where a fitting relationship exists between the estimated service amount and the estimated starting distance, between the amount in the estimated starting distance, and between the amounts outside the estimated starting distance, and the fitting relationship determines the unit price according to the service amount of a historical order, between the historical starting distance, between the amounts in the historical starting distance, and between the amounts outside the historical starting distance.
In the technical scheme, after the constraint condition is created, on one hand, the constraint condition is reversely solved through the preset total amount of the transaction, and then the value range of the estimated service amount is determined, wherein the estimated service amount is determined by the estimated starting distance, the amount in the estimated starting distance, the mileage unit price outside the estimated starting distance and the fitting relation, namely the value range of at least one variable of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance is determined, so that the total amount of the transaction can be effectively improved, on the other hand, the estimated unit amount change in a specified time period is considered while the estimated service amount is solved, and the fact is that more orders are stimulated, so that the further popularization and the market share expansion of an operation platform are facilitated.
In any of the above technical solutions, preferably, the adjusting unit 202 includes: the analysis subunit 2024 is configured to analyze a historical starting distance corresponding to a service amount of a historical order, an amount within the historical starting distance, a driving distance outside the historical starting distance, and a mileage unit price outside the historical starting distance; the statistic subunit 2026, configured to statistically determine a corresponding relationship between the service amount of the historical order and the order-forming conversion rate; the determining subunit 2022 is further to: and determining the historical starting distance, the money amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the order-forming conversion rate determined by the corresponding relation and the mapping relation as the constraint condition of the total amount of the historical orders, wherein the order-forming conversion rate is a numerical value determined according to the proportion of the total amount of the historical orders to the estimated amount of the orders.
in the technical scheme, the historical starting distance, the amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the single conversion rate determined by the corresponding relation and the mapping relation are determined as the constraint conditions of the total sum of the historical orders, the single conversion rate is used as an intermediate variable, the influence trends of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance on the total sum can be determined respectively or comprehensively, the value ranges of any variable of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance can be determined by solving the optimal solution of the output variable (total sum) of the constraint conditions, and further, the value range of any variable can be determined according to the increment of the total sum, for example, the increase of the total amount of the transaction is marked as a% (a is more than or equal to 0), the starting distance, the mileage unit price and the amount of money in the starting distance which meet the increase of a% are determined, the accuracy of determining the starting distance, the mileage unit price and the amount of money in the starting distance is improved, and the increase of the total amount of the transaction and the market occupancy rate of the operation platform are improved while the increase of the total amount of the transaction is met.
specifically, the service amount is used as an input variable, the form conversion rate is used as an output result, and based on the corresponding relationship between the service amount and the form conversion rate, the constraint condition may be a linear regression model, a naive bayes model, a GBDT (sparse Boost Decision Tree algorithm) model, an XGBOOST (open source iterative Tree algorithm) model, or the like, and the form conversion rate corresponding to the order price is obtained through a specified order price.
furthermore, by adjusting the price of the order, a reasonable order conversion rate can be obtained, and the increase of the total order quantity and the total amount of the finished product can be facilitated.
It should be noted that the estimated order amount is the amount of all estimated bubbling order information, for example, in the network booking user interface, the user inputs information such as "start point", "end point" and "reserved time", and does not click "confirmation", that is, a bubbling order information is generated.
In any one of the above technical solutions, preferably, the constraint condition includes:GMV characterizes the total amount of traffic, Pi(D) Representing the service amount, Estcnt, of the ith historical capacity order in the corresponding distance intervali(D) representing the predicted finished single quantity, Ratio, of the ith historical capacity order in the corresponding distance intervali(P (D)) representing the order-forming conversion rate corresponding to the ith historical capacity order, D representing the service distance of the ith historical capacity order, P (D) representing the service amount of the historical capacity order, n representing the total number of the historical capacity orders, wherein n is a positive integer greater than or equal to 1, the distance interval comprises a numerical interval in which the driving distance is less than or equal to the starting distance, and the distance interval further comprises a numerical interval in which the driving distance is greater than the starting distance.
According to the technical scheme, the total amount of the historical capacity order is calculated by determining the service amount of the historical capacity order in each distance interval, estimating the sum of the historical capacity order and the constraint conditions, whether the adjusted service amount can improve the total amount of the sum of the historical capacity order is used as a reference for comparison, and whether the adjusted service amount can improve the total amount of the sum of the historical capacity order is improved, so that the accuracy of judging whether the.
The adjusting unit 202, the determining subunit 2022, the analyzing subunit 2024, and the counting subunit 2026 in the data processing apparatus 200 may be at least one of a central processing unit CPU, a digital signal processor DSP, a microcontroller MCU, or electronic components with the same functions.
fig. 3 shows a schematic block diagram of a server according to an embodiment of the invention.
as shown in fig. 3, a server 300 according to an embodiment of the present invention includes: such as data processing apparatus 200 shown in fig. 2.
example (b):
FIG. 4 shows a schematic flow diagram of a method for platform aggregate volume optimization according to one embodiment of the present invention.
As shown in fig. 4, the method for optimizing the platform total amount according to one embodiment of the present invention includes: step S402, obtaining historical service money, estimated unit amount and unit amount data.
Specifically, the calculation platform assembly amount is formed by taking a designated driving service in an operation platform as an example, a charging mode in a taxi taking scene of the designated driving service is generally the sum of the amount in the starting distance and the mileage amount, wherein the amount in the starting distance corresponds to a certain starting distance, and a calculation formula is as follows:
GMV＝GMV_s+GMV_n。
finishOrdCnt＝finishOrdCnt_s+finishOrdCnt_n。
Wherein GMV is the transaction total volume, GMV _ s is the total volume within the starting distance, GMV _ n is the total volume outside the starting distance, finshOrdCnt is the unit volume, finshOrdCnt _ s is the unit volume within the starting distance, finshOrdCnt _ n is the unit volume outside the starting distance.
(2) Calculating GMV _ s which is equal to the product of the starting distance single quantity and the amount of money in the starting distance, wherein the starting distance single quantity is equal to the product of the estimated single quantity and the single conversion rate in the starting distance, and the calculation formula is as follows:
GMV_s＝P_s×Estcnt(D_s)×Ratio(P_s)。
finishOrdCnt_s＝Estcnt(D_s)×Ratio(P_s)。
Wherein P _ s is the amount of money in the starting distance, D _ s is the starting distance, Estcnt (D _ s) is the estimated singleton in the starting distance, and Ratio (P _ s) is the singleton conversion rate corresponding to the amount of money P _ s in the starting distance.
(3) Calculating GMV _ n, wherein GMV _ n is equal to the product of the price of each distance interval and the unit amount of the corresponding distance interval, the price of each distance interval is equal to the product of the distance interval and the mileage unit price, and the unit amount of the distance interval is equal to the product of the estimated unit amount of the distance interval and the unit conversion rate, and the calculation formula is as follows:
GMV_n＝(D–D_s)×X×Estcnt(D–D_s)×Ratio((D–D_s)×X)。
finishOrdCnt_n＝Estcnt(D–D_s)×Ratio((D–D_s)×X)。
Wherein D is the distance, X is the mileage unit price, and (D-D _ s) X X is the mileage amount.
The method specifically comprises the following steps: and S404, measuring and calculating the relation between the historical service amount and the bill forming conversion rate.
(4) And (6) estimating the flexibility of the service amount. The prediction of the business amount elasticity, namely the relation measurement of the business amount and the single conversion rate, different business amounts correspond to different single conversion rates, the business amount is used for fitting and predicting the single conversion rate, and the formula is as follows:
Ratio＝F(P)。
The calculation formula of the single conversion rate is as follows: ratio is an amount of units/estimated amount of units.
the F function is a constraint condition, and may be a linear regression model, a naive bayes model, a GBDT model, an XGBOOST model, or the like, but may not be used if the fitting accuracy is not satisfied. And after the fitting is completed, giving a service sum P, and obtaining the bill-to-bill conversion rate corresponding to the service sum P.
(5) an estimate of the single quantity (number of bubbles) is estimated at each distance. When the platform grows to a certain stage or the platform already occupies most of the market, the capacity demand and supply tend to be stable, so that the change of the service amount can be assumed without influencing the total estimated unit amount. Namely, the corresponding estimated single amount in each distance range is assumed to be unchanged, and the calculation formula of the estimated single amount is as follows:
Estcnt＝f(D)。
where f is a fixed mapping relationship.
The method specifically comprises the following steps: step S406, obtaining a distance interval and predicting the distance interval into single data; step S408, the estimated service amount corresponding to each distance is calculated.
The method specifically comprises the following steps: step S410, constructing a platform assembly quota optimization model; step S412, outputting data: starting distance, amount of money in the starting distance and mileage unit price.
(6) and constructing a GMV optimization model, and solving a starting distance, the amount of money in the starting distance and the mileage unit price corresponding to the optimal GMV of the operation platform.
Max GMV。
s.t.GMV＝GMV_s+GMV_n。
GMV_s＝P_s×Estcnt×Ratio。
GMV_n＝(D–D_s)×X×Estcnt×Ratio。
finishOrdCnt＝finishOrdCnt_s+finishOrdCnt_n。
finishOrdCnt_s＝Estcnt(D_s)×Ratio(P_s)。
finishOrdCnt_n＝Estcnt(D–D_s)×Ratio((D–D_s)×X)。
FinishOrdCnt is predicted to be greater than or equal to original finishOrdCnt.
Wherein Ratio is f (P) is the yield, Estcnt is f (D), GMV _ s is the GMV within the starting distance, GMV _ n is the GMV outside the starting distance, s.t. GMV is the transaction total amount, P _ s is the amount within the starting distance, D _ s is the starting distance, P is the business amount, D is the distance, and X is the cost of the unit mileage.
On the premise of ensuring that finishOrdCnt (single amount) is not reduced, when the platform calculates the service amount, the amount of money in the starting distance, the starting distance and the mileage unit price are controlled within a certain range, and cannot be too large or too small, so that the starting distance, the amount of money in the starting distance and the mileage unit price corresponding to the GMV in the optimal state can be searched within a certain range through the GMV optimal model.
In addition, in the GMV optimization model, some limiting conditions may be added, such as: the GMV amplification is larger than a%, then according to the limited condition of amplification, a plurality of groups of data can be obtained, each group of data comprises three variables: starting distance, amount of money in the starting distance and mileage unit price.
According to an embodiment of the present invention, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed, performs the steps of: and responding to the information of the orders in the designated time period, and adjusting the estimated service amount of any order according to the constraint condition between the preset service amount and the total amount.
according to the technical scheme, the estimated service amount of any order is adjusted according to the constraint condition between the preset service amount and the total amount of the traffic, so that the accuracy of capacity pricing is improved, the willingness of a driver to receive orders is improved, the total amount of the traffic of the operation platform is improved, the amount of the traffic is not reduced, and the competitiveness and the market occupancy rate of the operation platform are improved.
In any of the above technical solutions, preferably, the adjusting the estimated transaction amount of any one of the orders according to a constraint condition between a preset transaction amount and a total amount in response to the information of the orders within the specified time period specifically includes: and when the estimated total amount of transaction is greater than or equal to a preset total amount of transaction and the estimated unit amount within the specified time period is greater than or equal to the preset unit amount, determining the value range of the estimated service amount according to the constraint condition, wherein a fitting relation exists between the estimated service amount and the estimated starting distance, the amount within the estimated starting distance and the mileage unit price outside the estimated starting distance, and the fitting relation is determined according to the service amount of a historical order, the historical starting distance, the amount within the historical starting distance and the mileage unit price outside the historical starting distance.
In the technical scheme, after the constraint condition is created, on one hand, the constraint condition is reversely solved through the preset total amount of the transaction, and then the value range of the estimated service amount is determined, wherein the estimated service amount is determined by the estimated starting distance, the amount in the estimated starting distance, the mileage unit price outside the estimated starting distance and the fitting relation, namely the value range of at least one variable of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance is determined, so that the total amount of the transaction can be effectively improved, on the other hand, the estimated unit amount change in a specified time period is considered while the estimated service amount is solved, and the fact is that more orders are stimulated, so that the further popularization and the market share expansion of an operation platform are facilitated.
In any of the above technical solutions, preferably, before responding to the information of the order within the specified time period, the method further includes: analyzing a historical starting distance corresponding to a service amount of a historical order, an amount in the historical starting distance, a driving distance outside the historical starting distance and a mileage unit price outside the historical starting distance; counting and determining the corresponding relation between the service amount of the historical order and the order forming conversion rate; determining a mapping relation between the travel distance of the historical order and the estimated finished order quantity; and determining the historical starting distance, the money amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the order-forming conversion rate determined by the corresponding relation and the mapping relation as the constraint condition of the total amount of the historical orders, wherein the order-forming conversion rate is a numerical value determined according to the proportion of the total amount of the historical orders to the estimated amount of the orders.
In the technical scheme, the historical starting distance, the amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the single conversion rate determined by the corresponding relation and the mapping relation are determined as the constraint conditions of the total sum of the historical orders, the single conversion rate is used as an intermediate variable, the influence trends of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance on the total sum can be determined respectively or comprehensively, the value ranges of any variable of the starting distance, the amount in the starting distance and the mileage unit price outside the starting distance can be determined by solving the optimal solution of the output variable (total sum) of the constraint conditions, and further, the value range of any variable can be determined according to the increment of the total sum, for example, the increase of the total amount of the transaction is marked as a% (a is more than or equal to 0), the starting distance, the mileage unit price and the amount of money in the starting distance which meet the increase of a% are determined, the accuracy of determining the starting distance, the mileage unit price and the amount of money in the starting distance is improved, and the increase of the total amount of the transaction and the market occupancy rate of the operation platform are improved while the increase of the total amount of the transaction is met.
Specifically, the service amount is used as an input variable, the form conversion rate is used as an output result, and based on the corresponding relationship between the service amount and the form conversion rate, the constraint condition may be a linear regression model, a naive bayes model, a GBDT (sparse Boost Decision Tree algorithm) model, an XGBOOST (open source iterative Tree algorithm) model, or the like, and the form conversion rate corresponding to the order price is obtained through a specified order price.
furthermore, by adjusting the price of the order, a reasonable order conversion rate can be obtained, and the increase of the total order quantity and the total amount of the finished product can be facilitated.
It should be noted that the estimated order amount is the amount of all estimated bubbling order information, for example, in the network booking user interface, the user inputs information such as "start point", "end point" and "reserved time", and does not click "confirmation", that is, a bubbling order information is generated.
In any one of the above technical solutions, preferably, the constraint condition includes:GMV characterizes the total amount of traffic, Pi(D) representing the service amount, Estcnt, of the ith historical capacity order in the corresponding distance intervali(D) representing the predicted finished single quantity, Ratio, of the ith historical capacity order in the corresponding distance intervali(P (D)) characterizing the order-forming conversion rate corresponding to the ith historical capacity order, D characterizing the service distance of the ith historical capacity order, P (D) characterizing the service amount of the historical capacity order, and n characterizing the total number of the historical capacity orders,And n is a positive integer greater than or equal to 1, wherein the distance interval comprises a numerical interval in which the running distance is less than or equal to the starting distance, and the distance interval also comprises a numerical interval in which the running distance is greater than the starting distance.
According to the technical scheme, the total amount of the historical capacity order is calculated by determining the service amount of the historical capacity order in each distance interval, estimating the sum of the historical capacity order and the constraint conditions, whether the adjusted service amount can improve the total amount of the sum of the historical capacity order is used as a reference for comparison, and whether the adjusted service amount can improve the total amount of the sum of the historical capacity order is improved, so that the accuracy of judging whether the.
the technical scheme of the invention is explained in detail by combining the drawings, and the invention provides a data processing method, a data processing device, a server and a computer readable storage medium, which can improve the accuracy of capacity pricing, facilitate the promotion of driver order taking willingness, ensure the amount of the order not to be reduced while promoting the total assembly amount of the operation platform and promote the competitiveness and market occupancy rate of the operation platform by adjusting the estimated service amount of any order according to the constraint condition between the preset service amount and the total assembly amount.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A data processing method, comprising:
and responding to the information of the orders in the designated time period, and adjusting the estimated service amount of any order according to the constraint condition between the preset service amount and the total amount.
2. the data processing method according to claim 1, wherein the adjusting the estimated transaction amount of any one of the orders according to a constraint between a preset transaction amount and a total transaction amount in response to the information of the orders within a specified time period specifically comprises:
When the estimated total amount of the total is greater than or equal to the preset total amount of the total and the estimated amount of the predicted single in the appointed time period is greater than or equal to the preset single, determining the value range of the estimated service amount according to the constraint condition,
And fitting relations exist among the estimated service amount, the estimated starting distance, the amount in the estimated starting distance and the mileage unit price outside the estimated starting distance, and the fitting relations are determined according to the service amount of the historical order, the historical starting distance, the amount in the historical starting distance and the mileage unit price outside the historical starting distance.
3. The data processing method according to claim 1 or 2, further comprising, before responding to information of an order within a specified period:
Analyzing a historical starting distance corresponding to a service amount of a historical order, an amount in the historical starting distance, a driving distance outside the historical starting distance and a mileage unit price outside the historical starting distance;
Counting and determining the corresponding relation between the service amount of the historical order and the order forming conversion rate;
Determining a mapping relation between the travel distance of the historical order and the estimated finished order quantity;
determining the historical starting distance, the money amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the order forming conversion rate determined by the corresponding relation and the mapping relation as the constraint condition of the total amount of the historical orders,
And the order forming conversion rate is a numerical value determined according to the ratio of the total order forming amount of the historical orders to the estimated order forming amount.
4. A data processing method according to claim 3, wherein said constraints comprise:
the GMV characterizes the aggregate volume, Pi(D) representing the service amount of the ith historical order in a corresponding distance interval, wherein Estcnt isi(D) Representing the estimated order forming quantity of the ith historical order in the corresponding distance interval, wherein the Ratio isi(P (D)) characterizing the order-forming conversion rate corresponding to the ith historical order, wherein D characterizes the service distance of the ith historical order, P (D) characterizes the service amount of the historical order, n characterizes the total number of the historical orders, and n is a positive integer greater than or equal to 1,
The distance interval comprises a numerical interval with the running distance smaller than or equal to the starting distance, and the distance interval also comprises a numerical interval with the running distance larger than the starting distance.
5. A data processing apparatus, comprising:
And the adjusting unit is used for responding to the information of the orders in the designated time period and adjusting the estimated service amount of any order according to the constraint condition between the preset service amount and the total amount.
6. The data processing apparatus of claim 5, wherein the adjustment unit comprises:
A determining subunit, configured to determine a value range of the estimated service amount according to the constraint condition when the estimated total amount of the transaction is greater than or equal to a preset total amount of the transaction and the estimated amount of the transaction in the specified time period is greater than or equal to a preset amount of the transaction,
And fitting relations exist among the estimated service amount, the estimated starting distance, the amount in the estimated starting distance and the mileage unit price outside the estimated starting distance, and the fitting relations are determined according to the service amount of the historical order, the historical starting distance, the amount in the historical starting distance and the mileage unit price outside the historical starting distance.
7. The data processing apparatus according to claim 5 or 6, wherein the adjusting unit comprises:
The analysis subunit is used for analyzing a historical starting distance corresponding to the service amount of the historical order, the amount in the historical starting distance, the driving distance outside the historical starting distance and the mileage unit price outside the historical starting distance;
The statistical subunit is used for determining the corresponding relation between the service amount of the historical order and the order forming conversion rate in a statistical manner;
the determining subunit is further to: determining the historical starting distance, the money amount in the historical starting distance, the driving distance outside the historical starting distance, the mileage unit price outside the historical starting distance, the order forming conversion rate determined by the corresponding relation and the mapping relation as the constraint condition of the total amount of the historical orders,
and the order forming conversion rate is a numerical value determined according to the ratio of the total order forming amount of the historical orders to the estimated order forming amount.
8. The data processing apparatus of claim 7, wherein the constraint comprises:
The GMV characterizes the aggregate volume, Pi(D) Representing the service amount of the ith historical order in a corresponding distance interval, wherein Estcnt isi(D) Representing the estimated order forming quantity of the ith historical order in the corresponding distance interval, wherein the Ratio isi(P (D)) characterizing the order-forming conversion rate corresponding to the ith historical order, said D characterizing the business distance of the ith historical order, said P (D) characterizing the business amount of the historical order, said n characterizing the total number of the historical orders,N is a positive integer greater than or equal to 1,
The distance interval comprises a numerical interval with the running distance smaller than or equal to the starting distance, and the distance interval also comprises a numerical interval with the running distance larger than the starting distance.
9. a server, characterized in that the server is provided with a memory, a processor and a computer program stored on the memory and executable on the processor,
The steps of a data processing method as claimed in any one of claims 1 to 4 when the processor executes a computer program;
And/or comprising a data processing device according to any of claims 5 to 8.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the data processing method of any one of claims 1 to 4.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
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| CN201810547664.8A CN110555711A (en) | 2018-05-31 | 2018-05-31 | Data processing method, device, server and computer readable storage medium |
| PCT/CN2019/083535 WO2019201344A1 (en) | 2018-04-19 | 2019-04-19 | Systems and methods for transport pricing |
| US17/073,485 US20210035172A1 (en) | 2018-04-19 | 2020-10-19 | Systems and methods for transport pricing |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111126914A (en) * | 2019-12-24 | 2020-05-08 | 拉扎斯网络科技（上海）有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN111489204A (en) * | 2020-04-16 | 2020-08-04 | 浙江同花顺智能科技有限公司 | Data processing method, device, equipment and storage medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111126914A (en) * | 2019-12-24 | 2020-05-08 | 拉扎斯网络科技（上海）有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN111126914B (en) * | 2019-12-24 | 2023-09-26 | 拉扎斯网络科技（上海）有限公司 | Data processing method, device, electronic equipment and storage medium |
| CN111489204A (en) * | 2020-04-16 | 2020-08-04 | 浙江同花顺智能科技有限公司 | Data processing method, device, equipment and storage medium |
| CN111489204B (en) * | 2020-04-16 | 2023-09-12 | 浙江同花顺智能科技有限公司 | Data processing method, device, equipment and storage medium |
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