CN111680904A

CN111680904A - Acquisition method and device of purchase scheme and storage medium

Info

Publication number: CN111680904A
Application number: CN202010491613.5A
Authority: CN
Inventors: 刘永霞; 陶兴源; 沈翀; 李芳媛
Original assignee: Shanghai Minglue Artificial Intelligence Group Co Ltd
Current assignee: Shanghai Minglue Artificial Intelligence Group Co Ltd
Priority date: 2020-06-02
Filing date: 2020-06-02
Publication date: 2020-09-18

Abstract

The invention discloses a method and a device for acquiring a purchase scheme and a storage medium. Wherein, the method comprises the following steps: acquiring purchasing data of a target material, wherein the purchasing data comprises a plurality of groups of purchasing evaluation indexes, and one group of purchasing evaluation indexes is used for indicating the evaluation indexes of purchasing the target material from a material supplier; inputting purchase data into a purchase scheme model; acquiring a purchasing scheme set output by a purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes; and determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating the target material to be purchased from the target supplier in the plurality of material suppliers. The invention solves the technical problem of low acquisition efficiency of the purchase scheme.

Description

Acquisition method and device of purchase scheme and storage medium

Technical Field

The invention relates to the field of catering, in particular to a method and a device for acquiring a purchasing scheme and a storage medium.

Background

In recent years, purchasing requirements in the catering field are increasing, and the requirements on purchasing quality and efficiency are also increasing, such as purchasing cost and quantity. In the related technology, purchasing is mainly realized in a manual mode, so that timeliness and accuracy cannot be guaranteed, and efficiency is not high. Therefore, there is a problem that acquisition efficiency of the purchase solution is low.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The embodiment of the invention provides a method and a device for acquiring a purchase scheme and a storage medium, which are used for at least solving the technical problem of low acquisition efficiency of the purchase scheme.

According to an aspect of an embodiment of the present invention, there is provided a method for acquiring a purchase scheme, including: acquiring purchasing data of a target material, wherein the purchasing data comprises a plurality of groups of purchasing evaluation indexes, and one group of purchasing evaluation indexes is used for indicating the evaluation indexes of purchasing the target material from a material supplier; inputting the purchase data into a purchase scheme model, wherein the purchase scheme model is a neural network model which is obtained by training a plurality of historical purchase data and is used for generating a purchase scheme; acquiring a purchasing scheme set output by the purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes; and determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating the target material to be purchased from a target supplier of the plurality of material suppliers.

As an optional scheme, before the obtaining of the procurement data of the target material, the method includes: determining first supply data of the target material, wherein the target material is purchased at a plurality of material suppliers including a first supplier, in the plurality of historical purchase data, the first supply data being indicative of material quality of the target material purchased at the first supplier; determining second supply data of the first supplier in the plurality of historical procurement data, wherein the second supply data is used for representing process data of the first supplier in the process of supplying the target material; inputting the first supply data and the second supply data into an evaluation index model; acquiring a first evaluation index output by the evaluation index model, wherein the first evaluation index is used for calculating a first priority of the target material purchased at the first supplier; and establishing a first mapping relation among the first evaluation index, the first supplier and the target material.

As an optional solution, the obtaining of the first evaluation index output by the evaluation index model includes at least one of: acquiring a first evaluation index item output by the evaluation index model, wherein the first evaluation index item is used for representing the material quality of the target material purchased at the first supplier; acquiring a second evaluation index item output by the evaluation index model, wherein the second evaluation index item is used for representing process data of the first supplier in the process of supplying the target material; and acquiring a third evaluation index item output by the evaluation index model, wherein the third evaluation index item is used for expressing the matching degree of the first supplier and the target material.

As an optional solution, the acquiring the purchasing scenario set output by the purchasing scenario model includes: determining the first evaluation index in the purchasing data according to the first mapping relation; determining a second evaluation index in the procurement data according to a second mapping relationship, wherein the second mapping relationship is used for determining a second supplier for supplying the target material according to the target material and for calculating a second priority for procurement of the target material at the second supplier, and the plurality of material suppliers include the first supplier and the second supplier; and performing a first weight calculation on the first evaluation index and the second evaluation index, respectively, and obtaining the first priority and the second priority.

As an optional scheme, before the obtaining of the procurement data of the target material, the method includes: acquiring a plurality of material data in the plurality of historical purchasing data; and inputting the plurality of material data into an initial purchasing scheme model to train to obtain the purchasing scheme model.

As an optional scheme, the inputting the plurality of material data into an initial purchasing scheme model to train and obtain the purchasing scheme model includes: repeatedly executing the following steps until the purchasing scheme model is obtained: determining current sample material data from the plurality of material data, determining sample materials, all material suppliers for supplying the sample materials and third evaluation indexes of all the material suppliers in the current sample data, and determining a current purchasing scheme model; executing second weight calculation according to the third evaluation index to obtain a current output result of the current purchasing scheme model; under the condition that the current output result does not reach the output convergence condition, acquiring next sample material data as the current sample material data; and under the condition that the current output result reaches the convergence condition, determining the current purchasing scheme model as the purchasing scheme model.

As an optional scheme, before the obtaining of the procurement data of the target material, the method includes: acquiring a first purchasing demand of the target material; inputting the first purchase demand into a price prediction model, wherein the price prediction model is a neural network model which is obtained by training a plurality of sample price data and is used for generating a predicted price track, and the predicted price track is used for representing the price change track of the target material within the prediction time; obtaining the predicted price track output by the price prediction model; and adjusting the first purchasing requirement according to the predicted price track, and determining a second purchasing requirement of the target material, wherein the purchasing data comprises the second purchasing requirement.

As an optional solution, the determining a target purchasing plan in the purchasing plan set according to the priority includes: determining a sorting basis in the priority, wherein the sorting basis is used for sorting purchasing schemes with the priorities of the same type in the purchasing scheme set; and according to the sorting basis, determining a target purchasing scheme in the purchasing schemes with the same type of priority.

According to another aspect of the embodiments of the present invention, there is also provided a device for acquiring a purchase scheme, including: a first obtaining unit, configured to obtain purchase data of a target material, where the purchase data includes a plurality of sets of purchase evaluation indexes, and a set of purchase evaluation indexes is used to indicate evaluation indexes for purchasing the target material from a material supplier; the system comprises a first input unit, a second input unit and a third input unit, wherein the first input unit is used for inputting the purchasing data into a purchasing scheme model, and the purchasing scheme model is a neural network model which is obtained by training a plurality of historical purchasing data and is used for generating a purchasing scheme; a second obtaining unit, configured to obtain a purchasing scheme set output by the purchasing scheme model, where the purchasing scheme set includes multiple purchasing schemes and priorities of the purchasing schemes; a first determining unit, configured to determine a target purchasing plan from the purchasing plan set according to the priority, where the target purchasing plan is used to instruct to purchase the target material from a target supplier of the plurality of material suppliers.

As an alternative, the second determining unit is configured to determine, in the plurality of historical purchase data, first supply data of the target material, before the obtaining of the purchase data of the target material, where the target material is purchased by a plurality of material suppliers including a first supplier, and the first supply data is used to indicate material quality of the target material purchased by the first supplier; a third determining unit, configured to determine second supply data of the first supplier in the plurality of historical purchase data before the acquisition of the purchase data of the target material, where the second supply data is process data of the first supplier during supply of the target material; a second input unit, configured to input the first supply data and the second supply data into an evaluation index model before the acquisition of the purchase data of the target material; a third obtaining unit, configured to obtain a first evaluation index output by the evaluation index model before obtaining purchase data of the target material, where the first evaluation index is used to calculate a first priority of purchasing the target material at the first supplier; and the establishing unit is used for establishing a first mapping relation between the first evaluation index and the first supplier and the target material before the acquisition of the purchase data of the target material.

As an optional solution, the third obtaining unit includes at least one of: a first obtaining module, configured to obtain a first evaluation index item output by the evaluation index model, where the first evaluation index item is used to indicate material quality of the target material purchased at the first supplier; a second obtaining module, configured to obtain a second evaluation index item output by the evaluation index model, where the second evaluation index item is used to represent process data of the first supplier in a process of supplying the target material; and a third obtaining module, configured to obtain a third evaluation index item output by the evaluation index model, where the third evaluation index item is used to indicate a matching degree between the first supplier and the target material.

As an optional solution, the third obtaining unit includes: a first determining module, configured to determine the first evaluation indicator in the purchase data according to the first mapping relationship; a second determining module, configured to determine a second evaluation indicator in the procurement data according to a second mapping relationship, where the second mapping relationship is used to determine a second supplier for supplying the target material according to the target material, and to calculate a second priority for procurement of the target material at the second supplier, where the plurality of material suppliers include the first supplier and the second supplier; a calculating module, configured to perform a first weight calculation on the first evaluation indicator and the second evaluation indicator, respectively, and obtain the first priority and the second priority.

As an alternative, the method comprises the following steps: a fourth obtaining module, configured to obtain multiple material data in the multiple historical purchasing data before obtaining purchasing data of the target material; the first input module is used for inputting the plurality of material data into an initial purchasing scheme model before the purchasing data of the target material is acquired so as to train and obtain the purchasing scheme model.

As an optional solution, the input module includes: the repeating subunit is used for repeatedly executing the following steps until the purchasing scheme model is obtained: a first determining subunit, configured to determine current sample material data from the multiple material data, determine, in the current sample data, a sample material, all material suppliers that supply the sample material, and third evaluation indexes of all the material suppliers, and determine a current purchasing scheme model; the calculating subunit is used for executing second weight calculation according to the third evaluation index to obtain a current output result of the current purchasing scheme model; an obtaining subunit, configured to obtain next sample material data as the current sample material data when the current output result does not reach an output convergence condition; and a second determining subunit, configured to determine that the current purchasing scheme model is the purchasing scheme model when the current output result reaches the convergence condition.

As an alternative, the method comprises the following steps: a fifth obtaining module, configured to obtain a first purchasing requirement of the target material before obtaining the purchasing data of the target material; a second input module, configured to input the first purchase demand into a price prediction model before the acquisition of the purchase data of the target material, where the price prediction model is a neural network model that is obtained by training using a plurality of sample price data and is used to generate a predicted price trajectory, and the predicted price trajectory is used to represent a price change trajectory of the target material within a prediction time; a sixth obtaining module, configured to obtain the predicted price trajectory output by the price prediction model before obtaining the purchase data of the target material; and an adjusting module, configured to adjust the first purchasing requirement according to the predicted price trajectory before obtaining the purchasing data of the target material, and determine a second purchasing requirement of the target material, where the purchasing data includes the second purchasing requirement.

As an alternative, the first determining unit includes: a third determining module, configured to determine a sorting criterion in the priority, where the sorting criterion is used to sort the purchasing schemes with priorities of the same type in the purchasing scheme set; and the fourth determining module is used for determining a target purchasing scheme in the purchasing schemes with the same type of priority according to the sorting basis.

According to another aspect of the embodiment of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, where the computer program is configured to execute the above-mentioned acquisition method of the purchasing scheme when running.

According to another aspect of the embodiments of the present invention, there is also provided an electronic apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the method for acquiring the purchase solution through the computer program.

In the embodiment of the invention, the purchasing data of the target material is obtained, wherein the purchasing data comprises a plurality of groups of purchasing evaluation indexes, and one group of purchasing evaluation indexes is used for indicating the evaluation indexes of purchasing the target material from a material supplier; inputting the purchase data into a purchase scheme model, wherein the purchase scheme model is a neural network model which is obtained by training a plurality of historical purchase data and is used for generating a purchase scheme; acquiring a purchasing scheme set output by the purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes; and determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating the target material to be purchased from a target supplier of the material suppliers, so that the purpose of generating the optimal purchasing scheme according to multiple information is achieved, the technical effect of improving the acquiring efficiency of the purchasing scheme is achieved, and the technical problem of low acquiring efficiency of the purchasing scheme is solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

FIG. 1 is a schematic diagram of an application environment of an alternative procurement solution acquisition method according to an embodiment of the invention;

FIG. 2 is a schematic diagram of a flow chart of an alternative procurement scenario acquisition method according to an embodiment of the invention;

FIG. 3 is a schematic diagram of an alternative procurement scenario acquisition method according to an embodiment of the invention;

FIG. 4 is a schematic diagram of an alternative procurement scenario acquisition method according to an embodiment of the invention;

FIG. 5 is a schematic diagram of an alternative procurement scenario acquisition method according to an embodiment of the invention;

FIG. 6 is a schematic diagram of an alternative procurement scenario acquisition method according to an embodiment of the invention;

FIG. 7 is a schematic diagram of an alternative procurement arrangement of acquisition devices according to an embodiment of the invention;

FIG. 8 is a schematic diagram of an acquisition device for an alternative procurement arrangement according to an embodiment of the invention;

FIG. 9 is a schematic diagram of an acquisition device for an alternative procurement arrangement according to an embodiment of the invention;

fig. 10 is a schematic structural diagram of an alternative electronic device according to an embodiment of the invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

According to an aspect of the embodiment of the present invention, there is provided a method for acquiring a purchasing scheme, and optionally, as an optional implementation, the method for acquiring a purchasing scheme may be applied to, but is not limited to, an environment as shown in fig. 1. The system may include, but is not limited to, a user equipment 102, a network 110, and a server 112, wherein the user equipment 102 may include, but is not limited to, a display 108, a processor 106, and a memory 104.

The specific process comprises the following steps:

step S102, the user equipment 102 obtains purchasing data of the target material 1022;

step S104-S106, user device 102 sends purchase data to server 112 via network 110;

step S108, the server 112 inputs the purchasing data into the purchasing scheme model through the processing engine 116, so as to generate a purchasing scheme set 1024;

steps S110-S112, server 112 transmits set of procurement solutions 1024 to user device 102 over network 110, processor 106 in user device 102 displaying the set of procurement solutions in display 108, and storing set of procurement solutions 1024 in memory 104;

at step S114, target purchasing plan 1026 is determined in user device 102 by a processor within purchasing plan set 1024.

Optionally, as an optional implementation manner, as shown in fig. 2, the method for acquiring the purchase scheme includes:

s202, acquiring purchasing data of a target material, wherein the purchasing data comprises a plurality of groups of purchasing evaluation indexes, and one group of purchasing evaluation indexes is used for indicating the evaluation indexes of purchasing the target material from a material supplier;

s204, inputting the purchasing data into a purchasing scheme model, wherein the purchasing scheme model is a neural network model which is obtained by training by utilizing a plurality of historical purchasing data and is used for generating a purchasing scheme;

s206, acquiring a purchasing scheme set output by the purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes;

and S208, determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating that target materials are purchased from target suppliers in the plurality of material suppliers.

Optionally, in this embodiment, the obtaining method of the purchasing scheme may be, but is not limited to, applied in a raw material purchasing scenario in the catering industry. The target material can be, but is not limited to, food materials, raw materials, tools, and the like. The procurement data may include, but is not limited to, category information, quantity information, etc. of the target material. The procurement plan may be more limited to the manner in which the target materials are procured by the suppliers, wherein the suppliers in the procurement plan may be, but are not limited to, a combination of one or more. The priority may include, but is not limited to, a purchase cost priority, a purchase time priority, a composite priority, and the like.

Acquiring purchasing data of a target material, wherein the purchasing data includes a plurality of sets of purchasing evaluation indexes, and one set of purchasing evaluation indexes is used for indicating an evaluation index for purchasing the target material from a material supplier; inputting the purchasing data into a purchasing scheme model, wherein the purchasing scheme model is a neural network model which is obtained by training by utilizing a plurality of historical purchasing data and is used for generating a purchasing scheme; acquiring a purchasing scheme set output by a purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes; and determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating the target material to be purchased from the target supplier in the plurality of material suppliers.

For further illustration, optionally, for example, as shown in fig. 3, the procurement plan set 302 includes a plurality of suppliers, such as supplier a, supplier B, and supplier C, and the suppliers are sorted according to priority, wherein the supplier a with the highest priority is selected as the target procurement plan 304.

By the embodiment provided by the application, the purchasing data of the target material is obtained, wherein the purchasing data comprises a plurality of groups of purchasing evaluation indexes, and one group of purchasing evaluation indexes is used for indicating the evaluation indexes of purchasing the target material from one material supplier; inputting the purchasing data into a purchasing scheme model, wherein the purchasing scheme model is a neural network model which is obtained by training by utilizing a plurality of historical purchasing data and is used for generating a purchasing scheme; acquiring a purchasing scheme set output by a purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes; and determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating the target material to be purchased from a target supplier in the plurality of material suppliers, so that the purpose of generating and acquiring the purchasing scheme most suitable for the target material at the highest speed through a purchasing model established by the evaluation index for evaluating the supplier is achieved, and the effect of improving the acquisition efficiency of the purchasing scheme is realized.

As an optional scheme, before acquiring the purchase data of the target material, the method comprises the following steps:

s1, determining first supply data of the target material among the plurality of historical procurement data, wherein the target material is procured at a plurality of material suppliers including the first supplier, the first supply data being indicative of material quality of the target material procured at the first supplier;

s2, determining second supply data of the first supplier in the plurality of historical purchase data, wherein the second supply data is used for representing process data of the first supplier in the process of supplying the target material;

s3, inputting the first supply data and the second supply data into the evaluation index model;

s4, acquiring a first evaluation index output by the evaluation index model, wherein the first evaluation index is used for calculating a first priority of target material purchase at a first supplier;

s5, establishing a first mapping relation between the first evaluation index and the first supplier and the target material.

Alternatively, the material quality may be, but is not limited to, an indication of the supply quality of the target material, such as a material reject ratio. The process data can be used to represent, but not limited to, the supply performance of the target material supplied by the supplier, such as the supply speed, the supply attitude, the supply goodness, and the like. The first priority may be, but is not limited to, representing a comprehensive performance priority of the supplier in supplying the target material, wherein the material quality and the weight of the process data can be flexibly set.

It is noted that, in the plurality of historical procurement data, first supply data of the target material is determined, wherein the target material is procured at a plurality of material suppliers including the first supplier, the first supply data being indicative of material quality of the target material procured at the first supplier; determining second supply data of the first supplier in the plurality of historical purchase data, wherein the second supply data is used for representing process data of the first supplier in the process of supplying the target material; inputting the first supply data and the second supply data into an evaluation index model; acquiring a first evaluation index output by an evaluation index model, wherein the first evaluation index is used for calculating a first priority of target material purchase at a first supplier; and establishing a first mapping relation between the first evaluation index and the first supplier and the target material.

For further example, it is optionally recorded in the historical procurement data, that the material quality of the first supplier is rated a (90 points), the process data is rated B (80 points) in the scenario of supplying the target material, and further according to different weights, for example, the weight of the material quality is 0.6, and the weight of the process data is 0.4, the calculation process of the first evaluation index of the first supplier is 90 times 06, and then 80 times 0.4 is added, and finally the first evaluation index is calculated to be 86 points.

By the embodiment provided by the application, first supply data of a target material is determined in a plurality of historical purchase data, wherein the target material is purchased at a plurality of material suppliers including a first supplier, and the first supply data is used for representing the material quality of the target material purchased at the first supplier; determining second supply data of the first supplier in the plurality of historical purchase data, wherein the second supply data is used for representing process data of the first supplier in the process of supplying the target material; inputting the first supply data and the second supply data into an evaluation index model; acquiring a first evaluation index output by an evaluation index model, wherein the first evaluation index is used for calculating a first priority of target material purchase at a first supplier; the first mapping relation between the first evaluation index and the first supplier and the first mapping relation between the first evaluation index and the target material are established, the purpose of improving the comprehensiveness of evaluation information of the suppliers is achieved, and the effect of improving the accuracy of the suppliers providing the target material is achieved.

As an alternative, obtaining the first evaluation index output by the evaluation index model includes at least one of:

s1, acquiring a first evaluation index item output by the evaluation index model, wherein the first evaluation index item is used for representing the material quality of the target material purchased at the first supplier;

s2, acquiring a second evaluation index item output by the evaluation index model, wherein the second evaluation index item is used for representing process data of the first supplier in the process of supplying the target material;

and S3, acquiring a third evaluation index item output by the evaluation index model, wherein the third evaluation index item is used for expressing the matching degree of the first supplier and the target material.

Alternatively, the degree of matching may be, but is not limited to, indicating how good the supplier is at supplying the target material, e.g., the supplier is best at supplying the target material, as opposed to a higher degree of matching of the supplier to the target material.

It should be noted that a first evaluation index item output by the evaluation index model is obtained, where the first evaluation index item is used to represent material quality of a target material purchased at a first supplier; acquiring a second evaluation index item output by the evaluation index model, wherein the second evaluation index item is used for representing process data of a first supplier in the process of supplying the target material; and acquiring a third evaluation index item output by the evaluation index model, wherein the third evaluation index item is used for expressing the matching degree of the first supplier and the target material.

For further example, the optional item of the first evaluation index indicates that the weight of the material quality is larger and the weight of the process data is smaller in the calculation process of the evaluation index; on the contrary, the second evaluation index item indicates that the weight of the material quality is smaller and the weight of the process data is larger in the calculation process of the evaluation index; and the third evaluation index item indicates that the weight of the material quality and the weight of the process data are relatively close in the calculation process of the evaluation index, for example, both are 0.5.

According to the embodiment provided by the application, a first evaluation index item output by an evaluation index model is obtained, wherein the first evaluation index item is used for representing the material quality of the target material purchased at a first supplier; acquiring a second evaluation index item output by the evaluation index model, wherein the second evaluation index item is used for representing process data of a first supplier in the process of supplying the target material; and acquiring a third evaluation index item output by the evaluation index model, wherein the third evaluation index item is used for representing the matching degree of the first supplier and the target material, so that the purpose of providing a more detailed evaluation index calculation mode is achieved, and the effect of improving the calculation flexibility of the evaluation index is realized.

As an alternative, the acquisition of the purchasing scenario set output by the purchasing scenario model includes:

s1, determining a first evaluation index in the purchasing data according to the first mapping relation;

s2, determining a second evaluation index in the procurement data according to a second mapping relationship, wherein the second mapping relationship is used for determining a second supplier for supplying the target material according to the target material and for calculating a second priority for procurement of the target material at the second supplier, wherein the plurality of material suppliers includes the first supplier and the second supplier;

s3, a first weight calculation is performed on the first evaluation index and the second evaluation index, respectively, to obtain a first priority and a second priority.

Optionally, the plurality of material suppliers includes a first supplier and a second supplier, but in practical applications, there may be more than two suppliers, which is only for clarity of illustration and is not limited herein.

It should be noted that, according to the first mapping relationship, a first evaluation index is determined in the procurement data; determining a second evaluation index in the procurement data according to a second mapping relationship, wherein the second mapping relationship is used for determining a second supplier for supplying the target material according to the target material and for calculating a second priority for procurement of the target material at the second supplier, and the plurality of material suppliers comprise the first supplier and the second supplier; and respectively executing first weight calculation on the first evaluation index and the second evaluation index, and obtaining a first priority and a second priority.

By way of further illustration, and optionally such as shown in FIG. 4, a plurality of suppliers in procurement solutions set 302 display corresponding priority values 402, and it can be seen that the supplier A with the highest priority value 402 is the target procurement solution 304.

According to the embodiment provided by the application, a first evaluation index is determined in the purchasing data according to the first mapping relation; determining a second evaluation index in the procurement data according to a second mapping relationship, wherein the second mapping relationship is used for determining a second supplier for supplying the target material according to the target material and for calculating a second priority for procurement of the target material at the second supplier, and the plurality of material suppliers comprise the first supplier and the second supplier; and respectively executing first weight calculation on the first evaluation index and the second evaluation index, and obtaining a first priority and a second priority, so that the purpose of determining the priority of the purchasing scheme according to more comprehensive data is achieved, and the effect of improving the accuracy of determining the priority of the purchasing scheme is realized.

s1, acquiring a plurality of material data in a plurality of historical purchasing data;

and S2, inputting the multiple material data into the initial purchasing scheme model to train and obtain the purchasing scheme model.

It should be noted that, a plurality of material data in a plurality of historical purchasing data are obtained; and inputting a plurality of material data into the initial purchasing scheme model to train to obtain the purchasing scheme model.

For further example, optionally, for example, a plurality of material data in a plurality of historical purchasing data are obtained, and the plurality of material data are input into the initial purchasing scheme model to train to obtain the purchasing scheme model, specifically, the initial purchasing scheme model includes an initial weight value used for calculating the input plurality of material data, where the training of the purchasing scheme model is optionally equivalent to the training of the purchasing scheme model to obtain a final weight value.

According to the embodiment provided by the application, a plurality of material data in a plurality of historical purchasing data are obtained; a plurality of material data are input into the initial purchasing scheme model to obtain the purchasing scheme model through training, the purpose of training the initial purchasing scheme model through a large amount of historical purchasing data is achieved, and the effect of improving the training comprehensiveness of the purchasing scheme model is achieved.

As an optional scheme, inputting a plurality of material data into the initial purchasing scheme model to train and obtain the purchasing scheme model includes:

s1, repeatedly executing the following steps until the purchasing scheme model is obtained:

s2, determining current sample material data from the multiple material data, determining sample materials, all material suppliers for supplying the sample materials and third evaluation indexes of all the material suppliers in the current sample data, and determining a current purchasing scheme model;

s3, executing second weight calculation through a third evaluation index to obtain a current output result of the current purchasing scheme model;

s4, acquiring next sample material data as the current sample material data under the condition that the current output result does not reach the output convergence condition;

and S5, determining the current purchasing scheme model as the purchasing scheme model under the condition that the current output result reaches the output convergence condition.

It should be noted that, the following steps are repeatedly executed until the purchasing scheme model is obtained: determining current sample material data from the plurality of material data, determining sample materials, all material suppliers for supplying the sample materials and third evaluation indexes of all the material suppliers in the current sample data, and determining a current purchasing scheme model; executing second weight calculation through a third evaluation index to obtain a current output result of the current purchasing scheme model; under the condition that the current output result does not reach the output convergence condition, acquiring next sample material data as the current sample material data; and under the condition that the current output result reaches the output convergence condition, determining that the current purchasing scheme model is the purchasing scheme model.

Further, for example, optionally, a plurality of material data in the plurality of historical purchase data are input into the initial purchase scheme model, where a single material data in a single historical purchase data is used as an example, the historical purchase data records the purchase data of the material a, and the supplier a and the supplier B which can provide the material a, and determine an evaluation index of the supplier a when supplying the material a and an evaluation index of the supplier B when supplying the material a according to the mapping relationship, and then perform weight calculation on the two evaluation indexes, compare the calculation result with the result recorded in the historical data, and adjust the weight distribution of the weight calculation when the convergence condition is not achieved, thereby completing the training process of the single material data in the single historical purchase data on the initial purchase scheme model.

By the embodiment provided by the application, the following steps are repeatedly executed until the purchasing scheme model is obtained: determining current sample material data from the plurality of material data, determining sample materials, all material suppliers for supplying the sample materials and third evaluation indexes of all the material suppliers in the current sample data, and determining a current purchasing scheme model; executing second weight calculation through a third evaluation index to obtain a current output result of the current purchasing scheme model; under the condition that the current output result does not reach the output convergence condition, acquiring next sample material data as the current sample material data; under the condition that the current output result reaches the output convergence condition, the current purchasing scheme model is determined to be the purchasing scheme model, the purpose of continuously adjusting and calculating the weight through training is achieved, and the effect of improving the accuracy of the result output by the purchasing scheme model is achieved.

s1, acquiring a first purchasing demand of the target material;

s2, inputting the first purchase demand into a price prediction model, wherein the price prediction model is a neural network model which is obtained by training a plurality of sample price data and is used for generating a predicted price track, and the predicted price track is used for representing the price change track of the target material within the prediction time;

s3, obtaining a predicted price track output by the price prediction model;

and S4, adjusting the first purchasing requirement according to the predicted price track, and determining a second purchasing requirement of the target material, wherein the purchasing data comprises the second purchasing requirement.

It is to be noted that, a first purchasing requirement of the target material is obtained; inputting the first purchase demand into a price prediction model, wherein the price prediction model is a neural network model which is obtained by training a plurality of sample price data and is used for generating a predicted price track, and the predicted price track is used for expressing the price change track of the target material within the prediction time; obtaining a predicted price track output by a price prediction model; the first procurement requirements are adjusted according to the predicted price track, and second procurement requirements of the target material are determined, wherein the procurement data includes the second procurement requirements. Alternatively, the price prediction model may be, but is not limited to, a Long Short-Term Memory network (LSTM).

For further example, as shown in fig. 5, a graph with the abscissa as time and the ordinate as price is generated to show the price growth of the target material in a preset time in the future. And according to the curve diagram, the purchasing scheme of the target material is adjusted in real time according to the necessary quantity of the target material. For example, if the predicted price of the target material in the next quarter is more greatly increased, the purchase plan of the target material in the current quarter can be adjusted to increase the purchase amount of the target material.

According to the embodiment provided by the application, a first purchasing demand of a target material is obtained; inputting the first purchase demand into a price prediction model, wherein the price prediction model is a neural network model which is obtained by training a plurality of sample price data and is used for generating a predicted price track, and the predicted price track is used for expressing the price change track of the target material within the prediction time; obtaining a predicted price track output by a price prediction model; the first purchasing demand is adjusted according to the predicted price track, and the second purchasing demand of the target material is determined, wherein the purchasing data comprises the second purchasing demand, so that the aim of adjusting the purchasing scheme of the target material in real time according to the price predicted track is fulfilled, and the effect of improving the flexibility of the purchasing scheme is achieved.

As an alternative, determining a target procurement plan in the procurement plan set according to the priority comprises:

s1, determining a sorting basis in the priority, wherein the sorting basis is used for sorting purchasing schemes with the same type of priority in the purchasing scheme set;

and S2, according to the sorting basis, determining a target purchasing scheme in purchasing schemes with the same type of priority.

It should be noted that, according to the priority, determining the target purchasing plan in the purchasing plan set includes: determining a sorting basis in the priority, wherein the sorting basis is used for sorting purchasing schemes with the same type of priority in the purchasing scheme set; and according to the sorting basis, determining a target purchasing scheme in purchasing schemes with the same type of priority. Optionally, the ranking criteria may include, but is not limited to, a priority concept including lower priority, such as price ranking, supply duration ranking, supplier goodness ranking, and the like.

For further example, as shown in fig. 6, in the procurement plan set 302, the suppliers a, B, and C are sequentially ranked from large to small according to the priority values 402, but according to the ranking 602, the target procurement plan 304 should be determined according to the supply duration 604, for example, in the procurement plan set 302, the suppliers B, a, and C are sequentially ranked from short to long according to the supply duration 604, and the supplier B with the shortest supply duration is determined as the target procurement plan 304.

Through the embodiments provided by the present application, determining a target procurement plan in a procurement plan set according to a priority comprises: determining a sorting basis in the priority, wherein the sorting basis is used for sorting purchasing schemes with the same type of priority in the purchasing scheme set; according to the sequencing basis, the target purchasing scheme is determined in the purchasing schemes with the same type of priority, the aim of flexibly selecting the target purchasing scheme is fulfilled, and the effect of improving the acquisition flexibility of the target purchasing scheme is achieved.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.

According to another aspect of the embodiment of the invention, a purchasing scheme acquisition device for implementing the purchasing scheme acquisition method is further provided. As shown in fig. 7, the apparatus includes:

a first obtaining unit 702, configured to obtain purchase data of a target material, where the purchase data includes a plurality of sets of purchase evaluation indexes, and a set of purchase evaluation indexes is used to indicate evaluation indexes for purchasing the target material from a material supplier;

a first input unit 704, configured to input purchase data into a purchase scheme model, where the purchase scheme model is a neural network model that is obtained by training using a plurality of historical purchase data and is used to generate a purchase scheme;

a second obtaining unit 706, configured to obtain a purchasing scheme set output by the purchasing scheme model, where the purchasing scheme set includes a plurality of purchasing schemes and priorities of each purchasing scheme in the plurality of purchasing schemes;

a first determining unit 708 configured to determine a target procurement plan from the procurement plans set according to the priority, wherein the target procurement plan is used for indicating procurement of target materials from target suppliers of the plurality of material suppliers.

Optionally, in this embodiment, the obtaining device of the purchasing scheme may be, but is not limited to, applied in a raw material purchasing scenario of the catering industry. The target material can be, but is not limited to, food materials, raw materials, tools, and the like. The procurement data may include, but is not limited to, category information, quantity information, etc. of the target material. The procurement plan may be more limited to the manner in which the target materials are procured by the suppliers, wherein the suppliers in the procurement plan may be, but are not limited to, a combination of one or more. The priority may include, but is not limited to, a purchase cost priority, a purchase time priority, a composite priority, and the like.

As an alternative, as shown in fig. 8, the method includes:

a second determining unit 802 for determining first supply data of the target material, which is purchased at a plurality of material suppliers including the first supplier, among the plurality of historical purchase data before acquiring purchase data of the target material, the first supply data being used to represent material quality of the target material purchased at the first supplier;

a third determining unit 804, configured to determine second supply data of the first supplier in the plurality of historical purchase data before acquiring the purchase data of the target material, where the second supply data is used to represent process data of the first supplier in a process of supplying the target material;

a second input unit 806, configured to input the first supply data and the second supply data into the evaluation index model before acquiring the purchase data of the target material;

a third obtaining unit 808, configured to obtain a first evaluation index output by the evaluation index model before obtaining purchase data of the target material, where the first evaluation index is used to calculate a first priority of purchase of the target material at the first supplier;

the establishing unit 810 is configured to establish a first mapping relationship between the first evaluation indicator and the first supplier and the target material before acquiring the purchase data of the target material.

As an optional solution, the third obtaining unit includes at least one of:

the first acquisition module is used for acquiring a first evaluation index item output by the evaluation index model, wherein the first evaluation index item is used for representing the material quality of the target material purchased at the first supplier;

the second acquisition module is used for acquiring a second evaluation index item output by the evaluation index model, wherein the second evaluation index item is used for representing process data of the first supplier in the process of supplying the target material;

and the third obtaining module is used for obtaining a third evaluation index item output by the evaluation index model, wherein the third evaluation index item is used for representing the matching degree of the first supplier and the target material.

As an alternative, as shown in fig. 9, the third obtaining unit 808 includes:

a first determining module 902, configured to determine a first evaluation indicator in the procurement data according to the first mapping relationship;

a second determining module 904, configured to determine a second evaluation index in the procurement data according to a second mapping relationship, wherein the second mapping relationship is used to determine a second supplier for supplying the target material according to the target material, and to calculate a second priority for procurement of the target material at the second supplier, wherein the plurality of material suppliers includes the first supplier and the second supplier;

the calculating module 906 is configured to perform a first weight calculation on the first evaluation index and the second evaluation index respectively, and obtain a first priority and a second priority.

As an alternative, the method comprises the following steps:

the fourth acquisition module is used for acquiring a plurality of material data in the plurality of historical purchasing data before acquiring the purchasing data of the target material;

the first input module is used for inputting the data of the plurality of materials into the initial purchasing scheme model before acquiring the purchasing data of the target material so as to train and obtain the purchasing scheme model.

As an alternative, the input module includes:

a repeating subunit for repeatedly performing the following steps until the purchasing scheme model is obtained:

the first determining subunit is used for determining current sample material data from the plurality of material data, determining sample materials, all material suppliers for supplying the sample materials and third evaluation indexes of all the material suppliers in the current sample data, and determining a current purchasing scheme model;

the calculation subunit is used for executing second weight calculation through the third evaluation index to obtain a current output result of the current purchasing scheme model;

the acquisition subunit is used for acquiring next sample material data as the current sample material data under the condition that the current output result does not reach the output convergence condition;

and the second determining subunit is used for determining that the current purchasing scheme model is the purchasing scheme model under the condition that the current output result reaches the output convergence condition.

As an alternative, the method comprises the following steps:

the fifth acquisition module is used for acquiring the first purchasing demand of the target material before acquiring the purchasing data of the target material;

the second input module is used for inputting the first purchasing demand into a price prediction model before acquiring purchasing data of the target material, wherein the price prediction model is a neural network model which is obtained after being trained by utilizing a plurality of sample price data and is used for generating a predicted price track, and the predicted price track is used for representing the price change track of the target material within the prediction time;

the sixth acquisition module is used for acquiring the predicted price track output by the price prediction model before acquiring the purchase data of the target material;

and the adjusting module is used for adjusting the first purchasing demand according to the predicted price track and determining the second purchasing demand of the target material before acquiring the purchasing data of the target material, wherein the purchasing data comprises the second purchasing demand.

As an alternative, the first determining unit includes:

the third determining module is used for determining a sorting basis in the priority, wherein the sorting basis is used for sorting purchasing schemes with the priorities of the same type in the purchasing scheme set;

and the fourth determining module is used for determining a target purchasing scheme in purchasing schemes with the same type of priority according to the sorting basis.

According to another aspect of the embodiment of the present invention, there is also provided an electronic device for implementing the acquiring method of the purchasing scheme, as shown in fig. 10, the electronic device includes a memory 1002 and a processor 1004, the memory 1002 stores a computer program, and the processor 1004 is configured to execute the steps in any one of the method embodiments through the computer program.

Optionally, in this embodiment, the electronic apparatus may be located in at least one network device of a plurality of network devices of a computer network.

Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:

s1, acquiring purchasing data of the target material, wherein the purchasing data comprises a plurality of groups of purchasing evaluation indexes, and one group of purchasing evaluation indexes is used for indicating the evaluation indexes of purchasing the target material from one material supplier;

s2, inputting the purchasing data into a purchasing scheme model, wherein the purchasing scheme model is a neural network model which is obtained by training a plurality of historical purchasing data and is used for generating a purchasing scheme;

s3, acquiring a purchasing scheme set output by the purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes;

and S4, determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating the target material to be purchased from the target supplier in the plurality of material suppliers.

Alternatively, it can be understood by those skilled in the art that the structure shown in fig. 10 is only an illustration, and the electronic device may also be a terminal device such as a smart phone (e.g., an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, a Mobile Internet Device (MID), a PAD, and the like. Fig. 10 is a diagram illustrating a structure of the electronic device. For example, the electronic device may also include more or fewer components (e.g., network interfaces, etc.) than shown in FIG. 10, or have a different configuration than shown in FIG. 10.

The memory 1002 may be configured to store software programs and modules, such as program instructions/modules corresponding to the method and apparatus for acquiring a purchasing scheme in the embodiment of the present invention, and the processor 1004 executes various functional applications and data processing by running the software programs and modules stored in the memory 1002, that is, implementing the above-described method for acquiring a purchasing scheme. The memory 1002 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 1002 may further include memory located remotely from the processor 1004, which may be connected to the terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 1002 may be specifically, but not limited to, used to store information such as purchasing data, a purchasing scheme set, and a target purchasing scheme. As an example, as shown in fig. 10, the memory 1002 may include, but is not limited to, a first obtaining unit 702, a first input unit 704, a second obtaining unit 706, and a first determining unit 708 of the obtaining device of the purchasing scheme. In addition, other module units in the acquisition device of the purchase scheme may also be included, but are not limited to, and are not described in detail in this example.

Optionally, the above-mentioned transmission device 1006 is used for receiving or sending data via a network. Examples of the network may include a wired network and a wireless network. In one example, the transmission device 1006 includes a Network adapter (NIC) that can be connected to a router via a Network cable and other Network devices so as to communicate with the internet or a local area Network. In one example, the transmission device 1006 is a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

In addition, the electronic device further includes: a display 1008 for displaying the above-mentioned purchasing data, purchasing scheme set and target purchasing scheme; and a connection bus 1010 for connecting the respective module parts in the above-described electronic apparatus.

According to a further aspect of an embodiment of the present invention, there is also provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.

Alternatively, in the present embodiment, the above-mentioned computer-readable storage medium may be configured to store a computer program for executing the steps of:

Alternatively, in this embodiment, a person skilled in the art may understand that all or part of the steps in the methods of the foregoing embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

The integrated unit in the above embodiments, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in the above computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be substantially or partially implemented in the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, and including instructions for causing one or more computer devices (which may be personal computers, servers, or network devices) to execute all or part of the steps of the method according to the embodiments of the present invention.

In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a division of a logic function, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims

1. A method for acquiring a purchase scheme is characterized by comprising the following steps:

acquiring purchasing data of a target material, wherein the purchasing data comprises a plurality of groups of purchasing evaluation indexes, and one group of purchasing evaluation indexes is used for indicating the evaluation indexes of purchasing the target material from a material supplier;

inputting the purchasing data into a purchasing scheme model, wherein the purchasing scheme model is a neural network model which is obtained by training by utilizing a plurality of historical purchasing data and is used for generating a purchasing scheme;

acquiring a purchasing scheme set output by the purchasing scheme model, wherein the purchasing scheme set comprises a plurality of purchasing schemes and the priority of each purchasing scheme in the plurality of purchasing schemes;

and determining a target purchasing scheme from the purchasing scheme set according to the priority, wherein the target purchasing scheme is used for indicating the target material to be purchased from a target supplier in the plurality of material suppliers.

2. The method of claim 1, prior to said obtaining procurement data of target materials, comprising:

determining, in the plurality of historical procurement data, first supply data of the target material, wherein the target material is procured at a plurality of material suppliers including a first supplier, the first supply data being indicative of material quality of the target material procured at the first supplier;

determining second supply data of the first supplier in the plurality of historical procurement data, wherein the second supply data is used for representing process data of the first supplier in the process of supplying the target material;

inputting the first supply data and the second supply data into an evaluation index model;

acquiring a first evaluation index output by the evaluation index model, wherein the first evaluation index is used for calculating a first priority of the target material purchase at the first supplier;

and establishing a first mapping relation between the first evaluation index and the first supplier and the target material.

3. The method of claim 2, wherein the obtaining of the first evaluation index output by the evaluation index model comprises at least one of:

acquiring a first evaluation index item output by the evaluation index model, wherein the first evaluation index item is used for representing the material quality of the target material purchased at the first supplier;

acquiring a second evaluation index item output by the evaluation index model, wherein the second evaluation index item is used for representing process data of the first supplier in the process of supplying the target material;

and acquiring a third evaluation index item output by the evaluation index model, wherein the third evaluation index item is used for representing the matching degree of the first supplier and the target material.

4. The method of claim 2, wherein said obtaining a set of procurement solutions output by the procurement solutions model comprises:

determining the first evaluation index in the procurement data according to the first mapping relation;

determining a second evaluation index in the procurement data according to a second mapping relationship, wherein the second mapping relationship is used for determining a second supplier for supplying the target material according to the target material and for calculating a second priority for procurement of the target material at the second supplier, wherein the plurality of material suppliers comprises the first supplier and the second supplier;

and respectively executing first weight calculation on the first evaluation index and the second evaluation index, and obtaining the first priority and the second priority.

5. The method of claim 4, prior to said obtaining procurement data of target materials, comprising:

acquiring a plurality of material data in the plurality of historical purchasing data;

and inputting the plurality of material data into an initial purchasing scheme model to train to obtain the purchasing scheme model.

6. The method of claim 5, wherein said inputting said plurality of material data into an initial purchasing scenario model to train said purchasing scenario model comprises:

repeatedly executing the following steps until the purchasing scheme model is obtained:

determining current sample material data from the plurality of material data, determining sample materials, all material suppliers supplying the sample materials and third evaluation indexes of all the material suppliers in the current sample data, and determining a current purchasing scheme model;

executing second weight calculation according to the third evaluation index to obtain a current output result of the current purchasing scheme model;

under the condition that the current output result does not reach the output convergence condition, acquiring next sample material data as the current sample material data;

and under the condition that the current output result reaches the convergence condition, determining the current purchasing scheme model as the purchasing scheme model.

7. The method of claim 3, prior to said obtaining procurement data of target materials, comprising:

acquiring a first purchasing demand of the target material;

inputting the first purchase demand into a price prediction model, wherein the price prediction model is a neural network model which is obtained by training a plurality of sample price data and is used for generating a predicted price track, and the predicted price track is used for representing the price change track of the target material within the prediction time;

obtaining the predicted price track output by the price prediction model;

adjusting the first procurement requirements according to the predicted price trajectory and determining second procurement requirements of the target material, wherein the procurement data includes the second procurement requirements.

8. The method of claim 1, wherein said determining a target procurement plan within the procurement plan set according to the priority comprises:

determining a sorting basis in the priority, wherein the sorting basis is used for sorting purchasing schemes with the priorities of the same type in the purchasing scheme set;

and according to the sorting basis, determining a target purchasing scheme in the purchasing schemes with the same type of priority.

9. An acquisition device for a purchase solution, comprising:

a first acquisition unit, configured to acquire purchase data of a target material, where the purchase data includes a plurality of sets of purchase evaluation indexes, and a set of purchase evaluation indexes is used to indicate evaluation indexes for purchasing the target material from a material supplier;

the system comprises a first input unit, a second input unit and a third input unit, wherein the first input unit is used for inputting the purchasing data into a purchasing scheme model, and the purchasing scheme model is a neural network model which is obtained by training a plurality of historical purchasing data and is used for generating a purchasing scheme;

a second obtaining unit, configured to obtain a purchasing scheme set output by the purchasing scheme model, where the purchasing scheme set includes multiple purchasing schemes and priorities of the purchasing schemes;

a first determining unit, configured to determine a target procurement plan from the procurement plans according to the priority, wherein the target procurement plan is used to indicate procurement of the target material from a target supplier of the plurality of material suppliers.

10. The apparatus of claim 9, comprising:

a second determination unit configured to determine, in the plurality of historical procurement data, first supply data of a target material that is procured at a plurality of material suppliers including a first supplier, the first supply data being indicative of material quality of the target material procured at the first supplier, before the acquisition of procurement data of the target material;

a third determining unit, configured to determine, in the plurality of historical procurement data, second supply data of the first supplier before the obtaining of the procurement data of the target material, where the second supply data is used to represent process data of the first supplier in a process of supplying the target material;

the second input unit is used for inputting the first supply data and the second supply data into an evaluation index model before the acquisition of the purchase data of the target material;

a third obtaining unit, configured to obtain a first evaluation index output by the evaluation index model before obtaining procurement data of a target material, where the first evaluation index is used to calculate a first priority for procurement of the target material at the first supplier;

the establishing unit is used for establishing a first mapping relation between the first evaluation index and the first supplier and between the first evaluation index and the target material before the acquisition of the purchasing data of the target material.

11. The apparatus of claim 10, wherein the third obtaining unit comprises at least one of:

a first obtaining module, configured to obtain a first evaluation index item output by the evaluation index model, where the first evaluation index item is used to represent material quality of the target material purchased at the first supplier;

a second obtaining module, configured to obtain a second evaluation index item output by the evaluation index model, where the second evaluation index item is used to represent process data of the first supplier in a process of supplying the target material;

12. The apparatus of claim 10, wherein the third obtaining unit comprises:

a first determination module for determining the first evaluation index in the procurement data according to the first mapping relationship;

a second determination module, configured to determine a second evaluation indicator in the procurement data according to a second mapping relationship, wherein the second mapping relationship is used to determine a second supplier for supplying the target material according to the target material, and to calculate a second priority for procurement of the target material at the second supplier, wherein the plurality of material suppliers includes the first supplier and the second supplier;

a calculating module, configured to perform first weight calculation on the first evaluation indicator and the second evaluation indicator, respectively, and obtain the first priority and the second priority.

13. The apparatus of claim 12, comprising:

a fourth obtaining module, configured to obtain multiple material data in the multiple historical purchasing data before obtaining purchasing data of the target material;

the first input module is used for inputting the plurality of material data into an initial purchasing scheme model before the purchasing data of the target material is acquired so as to train and obtain the purchasing scheme model.

14. A computer-readable storage medium, comprising a stored program, wherein the program is operable to perform the method of any one of claims 1 to 8.

15. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 8 by means of the computer program.