CN114997842B - Intelligent evaluation method and system for digital purchase data - Google Patents

Intelligent evaluation method and system for digital purchase data Download PDF

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CN114997842B
CN114997842B CN202210842815.9A CN202210842815A CN114997842B CN 114997842 B CN114997842 B CN 114997842B CN 202210842815 A CN202210842815 A CN 202210842815A CN 114997842 B CN114997842 B CN 114997842B
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information
value
index information
interval
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CN114997842A (en
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王涛
刘畅
胡恺锐
王健国
马宇辉
谭云燕
赵欣
应学斌
章伟勇
吴建锋
吴健超
周耀
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State Grid Zhejiang Electric Power Co Ltd
Jinhua Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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State Grid Zhejiang Electric Power Co Ltd
Jinhua Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/063—Operations research, analysis or management
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
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Abstract

The invention discloses a digital procurement data intelligent review method and a digital procurement data intelligent review system, which comprise: the method comprises the following steps of S1, determining a plurality of historical suppliers in a supplier library based on purchasing demand information, and generating a first index evaluation table based on reference index information; s2, determining a plurality of index information sections corresponding to each piece of reference index information, and establishing a plurality of index information sections corresponding to each index name column in the first index evaluation table to obtain a second index evaluation table; s3, establishing a quantization index value corresponding to each index information segment in the second index evaluation table to obtain a third index evaluation table; s4, generating a calculation function of corresponding reference index information according to the index information interval and the quantization index value, and generating a corresponding intelligent calculation table based on the calculation function and the third index evaluation table; and S5, intelligently evaluating the current index data of the historical supplier or the newly added supplier to obtain a current evaluation result.

Description

Intelligent evaluation method and system for digital purchase data
Technical Field
The invention relates to the technical field of data processing, in particular to a digital procurement data intelligent review method and a digital procurement data intelligent review system.
Background
In the production and operation process of an enterprise, corresponding production and living products need to be purchased externally, in the existing purchasing process, suitable suppliers are selected according to manual assistance of corresponding experts, but the mode ensures that in the selection process of the suppliers, the subjective assumption is strong, and objective suppliers cannot be selected.
Generally, each supplier is relatively complex, so whether the supplier is a suitable supplier needs to be considered from multiple dimensions, and in the current technical scheme, the multi-dimensional indexes of the supplier cannot be automatically collected according to actual requirements, and the index quantization value interval is divided, so that evaluation intelligence of the supplier is low, and efficiency is low.
Disclosure of Invention
The invention overcomes the defects of the prior art, and provides the intelligent evaluation method and the intelligent evaluation system for the digital purchase data, which can automatically collect the multidimensional indexes of the suppliers according to the actual requirements and divide the quantitative value intervals of the indexes, so that the evaluation of a plurality of suppliers is higher in intelligence and efficiency.
In order to solve the technical problems, the technical scheme of the invention is as follows:
the embodiment of the invention provides an intelligent evaluation method for digital procurement data, which comprises the following steps:
step S1, receiving purchase demand information and reference index information input by a purchaser, determining a plurality of historical suppliers in a supplier library based on the purchase demand information, and generating a first index evaluation table based on the reference index information, wherein the first index evaluation table is provided with a plurality of index name columns corresponding to the reference index information;
step S2, calculating according to actual index values corresponding to reference index information of a plurality of historical suppliers, determining a plurality of index information sections corresponding to each reference index information, and establishing a plurality of index information sections corresponding to each index name column in the first index evaluation table to obtain a second index evaluation table;
step S3, calculation is carried out according to the reference weight corresponding to each piece of reference index information, the quantization index value corresponding to each index information section of each piece of reference index information is determined, the quantization index value corresponding to each index information section is established in the second index evaluation table, and a third index evaluation table is obtained;
s4, if judging that a table intelligent request is received, generating a calculation function of corresponding reference index information according to an index information section and a quantitative index value corresponding to each piece of reference index information, and generating a corresponding intelligent calculation table based on the calculation function and a third index evaluation table;
and S5, intelligently reviewing the current index data of the historical suppliers or the newly added suppliers according to the third index evaluation table or the intelligent calculation table to obtain a current review result.
Further, step S1 includes:
determining at least one purchase product according to the purchase demand information, and acquiring a plurality of historical suppliers related to the purchase product according to the purchase product, wherein each historical supplier has at least one corresponding purchase product;
generating header information at a header area of the initial index evaluation table based on the purchased product, the supplier name of the current supplier;
and obtaining an index name column corresponding to each piece of reference index information at a column area of the initial index evaluation table according to all pieces of reference index information, and generating a first index evaluation table.
Further, step S2 includes:
acquiring actual index values corresponding to any reference index information dimension of a plurality of historical suppliers, and extracting the maximum index value and the minimum index value in the actual index values;
generating a corresponding first index interval according to the maximum index value and the minimum index value, and dividing the first index interval into a plurality of first type index information sections according to the number of the historical suppliers;
generating a maximum completion interval according to the maximum index value and a preset maximum value, generating a minimum completion interval according to the minimum index value and a preset minimum value, and taking the maximum completion interval and the minimum completion interval as a second type of index information section;
and summarizing the first type of index information block section and the second type of index information block section, and establishing a plurality of index information block sections corresponding to each index name column in a first index evaluation table.
Further, the generating a corresponding first index interval according to the maximum index value and the minimum index value, and dividing the first index interval into a plurality of first type index information segments according to the number of the history suppliers includes:
performing one-time halving processing on the first index interval to obtain a plurality of index subintervals, and counting the number of historical suppliers in each index subinterval;
if the number of the historical suppliers in at least one index subinterval is judged to be larger than the division stopping number, performing halving processing on all the index subintervals again respectively to obtain a plurality of index subintervals subjected to secondary halving processing;
and after judging that the condition of stopping the equal division processing is reached, stopping performing the equal division processing on all the index subintervals, and taking each index subinterval as an index information interval of a first type.
Further, after it is determined that the condition for suspending the aliquot dividing process is met, stopping performing the aliquot dividing process on all the index subintervals, and using each index subinterval as an index information interval of a first type, includes:
if the number of the historical suppliers in all the index subintervals is judged to be less than or equal to the division stopping number, judging that the condition of stopping the equal division is met; or
And if the number of times of halving the index subinterval is judged to be more than or equal to the first preset number of times, judging that the condition of stopping the halving processing is reached.
Further, step S3 includes:
calculating according to the full score evaluation value input by the user and the reference weight corresponding to each piece of reference index information to obtain an index full score corresponding to each piece of reference index information;
calculating according to the index full score and the number of the first type of index information sections to obtain an index review difference value between every two adjacent index information sections, calculating the index review difference value through the following formula,
Figure 448480DEST_PATH_IMAGE001
wherein, the first and the second end of the pipe are connected with each other,
Figure 805467DEST_PATH_IMAGE002
is as follows
Figure 609475DEST_PATH_IMAGE003
The index evaluation difference of each reference index information,
Figure 541659DEST_PATH_IMAGE004
the full score is the index of the full score,
Figure 89315DEST_PATH_IMAGE005
is as follows
Figure 56134DEST_PATH_IMAGE003
The reference weight corresponding to each piece of reference index information,xthe number of index information segments that are reference index information;
and setting the minimum completion interval corresponding to the value 0 and the maximum completion interval corresponding to the index full score, and sequentially increasing the index review difference value by starting from the minimum completion interval to obtain the quantitative index value corresponding to each index information interval.
Further, step S4 includes:
calling an initialized calculation function, wherein the calculation function comprises an input configuration interface and an output configuration interface;
configuring the input of a calculation function through an input configuration interface, and taking the interval maximum value and the interval minimum value of each index information interval as the input interval of the calculation function;
configuring the output of the calculation function through an output configuration interface, and taking the quantized index value of the index information interval as the output value of the calculation function;
each index name column corresponds to an index input column and a quantization index column respectively, the calculation function is used for monitoring the index input column, determining a corresponding quantization index value according to the input index value of the index input column, and filling the quantization index value into the quantization index column;
and deleting the index information segment and the quantitative index value in the third index evaluation table, and generating an intelligent calculation table according to the processed third index evaluation table and the configured calculation function.
Further, the method also comprises the following steps:
if the encryption request data is judged to be received, determining reference index information to be encrypted according to the encryption request data, establishing an information storage unit corresponding to the reference index information, and establishing a first slot position and a second slot position in the information storage unit;
after the input index value is filled in the index input column corresponding to the reference index information to be encrypted, acquiring an input index value and a corresponding quantization index value, respectively filling the input index value and the quantization index value into a first slot position and a second slot position, and encrypting the information storage unit;
and after the judgment information storage unit carries out encryption processing, displaying the corresponding input index value and the quantization index value in the intelligent calculation table according to preset characters.
Further, after the input index value is filled in the index input column corresponding to the reference index information to be encrypted is judged, the input index value and the corresponding quantization index value are obtained, the input index value and the quantization index value are respectively filled in the first slot position and the second slot position, and the information storage unit is encrypted, including:
performing character processing on the header information in each intelligent calculation table to obtain a corresponding header character string, and performing hash calculation according to the header character string to obtain an automatically generated automatic sub-key;
receiving an actively configured configuration sub-key, and assembling the automatic sub-key and the configuration sub-key to obtain an encryption key of the intelligent calculation table;
after the first slot position and the second slot position in the information storage unit are judged to be filled with the input index value and the quantization index value and the confirmation encryption information is received, the corresponding information storage unit is encrypted based on the encryption key;
and counting the encrypted information storage units to generate a decryption correspondence table, wherein all the encrypted information storage units are arranged in the decryption correspondence table.
Further, the method also comprises the following steps:
configuring corresponding decryption logic for the decryption mapping table;
and the decryption logic is used for calling input index values and quantization index values in all information storage units of the decryption mapping table after receiving the encryption key, filling the input index values into corresponding index input columns, and filling the quantization index values into corresponding quantization index columns.
Further, step S5 includes:
acquiring actual index values of current index data of a historical supplier or a newly added supplier corresponding to each piece of reference index information, and inputting the actual index values into a corresponding third index evaluation table or an intelligent calculation table;
performing quantitative calculation on actual index values based on the third index evaluation table or the intelligent calculation table to obtain quantitative index values corresponding to each piece of reference index information;
and calculating the quantization index values corresponding to all the reference index information to obtain the current evaluation result of the corresponding historical supplier or the newly added supplier.
The embodiment of the invention provides a digital procurement data intelligent review system, which comprises:
the system comprises a receiving module, a storage module and a display module, wherein the receiving module is used for receiving purchase demand information and reference index information input by a purchaser, determining a plurality of historical suppliers in a supplier library based on the purchase demand information, and generating a first index evaluation table based on the reference index information, and the first index evaluation table is provided with a plurality of index name columns corresponding to the reference index information;
the establishment module is used for calculating according to actual index values corresponding to reference index information of a plurality of historical suppliers, determining a plurality of index information sections corresponding to each reference index information, and establishing a plurality of index information sections corresponding to each index name column in the first index evaluation table to obtain a second index evaluation table;
the calculation module is used for calculating according to the reference weight corresponding to each piece of reference index information, determining the quantization index value corresponding to each index information section of each piece of reference index information, and establishing the quantization index value corresponding to each index information section in the second index evaluation table to obtain a third index evaluation table;
the generating module is used for generating a calculation function of corresponding reference index information according to the index information section and the quantitative index value corresponding to each piece of reference index information if judging that the intelligent table request is received, and generating a corresponding intelligent calculation table based on the calculation function and the third index evaluation table;
and the evaluation module is used for intelligently evaluating the current index data of the historical suppliers or the newly added suppliers according to the third index evaluation table or the intelligent calculation table to obtain the current evaluation result.
The invention has the beneficial effects that:
(1) The digital intelligent purchasing data review method and system can determine a plurality of historical suppliers in the supplier library according to the purchasing demand information, calculate by combining actual index values of reference index information of the historical suppliers and determine the index information sections corresponding to the corresponding reference index information, so that the method and system can reasonably determine the corresponding index information sections according to different orders of magnitude of each reference index information. After the index information sections are obtained, the method can carry out comprehensive calculation according to the reference weight of the reference index information and the number of the index information sections to obtain the corresponding quantization index value of each index information section. Moreover, the method can automatically generate the corresponding calculation function, and fuse the calculation function and the third index evaluation table to obtain the intelligent calculation table, so that the method can automatically calculate after acquiring the corresponding actual index value according to the intelligent calculation table to obtain the evaluation result of the corresponding historical supplier or newly added supplier, and has the advantages of automation and high efficiency.
(2) In order to reasonably divide the index subinterval, the first index interval is continuously halved, and the number of the historical suppliers in the index subinterval is respectively less than or equal to the division stopping number, or the number of halving times of the index subinterval is more than or equal to the first preset number, so that the method can continuously divide the index subinterval according to the aggregation condition of the actual index values of the historical suppliers, further ensure that all the historical suppliers carry out differentiated index quantization under the dimension of certain reference index information, further ensure that all the suppliers can determine the proper numerical magnitude of the index subinterval when carrying out quantization processing based on the index subinterval, and ensure that a plurality of suppliers can carry out differentiated division under the reference index information of a certain dimension.
(3) The invention can configure the calculation function according to the corresponding relation between the index information section and the quantization index value, and automatically quantize the actual index value in the intelligent calculation table by combining the calculation function, and the intelligent calculation table does not have the corresponding relation information between the index information section and the quantization index value, so that the evaluation algorithm can be correspondingly hidden in the evaluation process. According to the method, the calculation can be performed through the third index evaluation table or the intelligent calculation table according to different actual use scenes, so that the application scenes in which calculation algorithms need to be presented or are not presented can be realized, and the automatic calculation is performed by combining the calculation functions during the automatic calculation scenes.
(4) The invention can establish an information storage unit corresponding to the reference index information according to the actual encryption requirement, and encrypt and store the corresponding input index value and the quantization index value respectively through a first slot position and a second slot position in the information storage unit. In order to avoid cheating of a buyer according to the automatic sub-key, the method and the system can assemble the sub-key according to the configuration sub-key and the automatic sub-key to obtain the encryption key, so that the hidden input index value and the hidden quantization index value can be displayed by the intelligent calculation table only after the supplier sends the corresponding encryption key.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic flow chart of an intelligent review method for digitized procurement data according to the invention;
FIG. 2 is a schematic view of a first index evaluation table;
FIG. 3 is a diagram of a second index evaluation table;
FIG. 4 is a diagram showing a first embodiment of a third index evaluation table;
FIG. 5 is a diagram showing a second embodiment of a third index evaluation table;
FIG. 6 is a schematic diagram of an intelligent computing table;
fig. 7 is a schematic structural diagram of the digital procurement data intelligent review system provided by the invention.
Detailed Description
In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
The invention provides a digital procurement data intelligent review method, as shown in figure 1, comprising the following steps:
step S1, receiving purchase demand information and reference index information input by a purchaser, determining a plurality of historical suppliers in a supplier base based on the purchase demand information, and generating a first index evaluation table based on the reference index information, wherein the first index evaluation table is provided with a plurality of index name columns corresponding to the reference index information. The invention firstly obtains the purchasing demand information and the reference index information input by the purchaser, wherein the purchasing demand information comprises purchasing power equipment, purchasing intellectual property service and the like, and the reference index information comprises the registered capital of the company, the number of the personnel of the company, the product quotation and the like. The invention firstly determines a plurality of historical suppliers in a supplier base according to the purchasing demand information, so that a company can have the historical suppliers which are pre-recorded in the production and operation activities, and generally speaking, at least a plurality of suppliers are inquired before one supplier is determined (multi-party price inquiry). Both suppliers that have previously provided provisioning services and suppliers that have been queried may be considered historical suppliers. The invention generates the first index evaluation table according to the reference index information, for example, the reference index information respectively comprises the registered capital of the company, the number of the persons in the company and the product quotation, and the first index evaluation table at the moment has columns corresponding to the registered capital of the company, the number of the persons in the company and the product quotation.
In a possible embodiment, the technical solution provided by the present invention, in step S1, includes:
determining at least one purchase product according to the purchase demand information, and acquiring a plurality of historical suppliers associated with the purchase product according to the purchase product, wherein each historical supplier has at least one corresponding purchase product. The invention can determine the associated historical suppliers corresponding to the transformer, namely, the corresponding historical suppliers can provide corresponding purchased products.
Header information is generated at a header area of the initial index evaluation table based on the purchased product, the supplier name of the current supplier. The invention can obtain corresponding header information according to the name of the current supplier and the purchased product which are evaluated at the moment. For example, the supplier name is company a, and the purchased product is a transformer, the header information at this time may be "transformer supply review form of company a".
And obtaining an index name column corresponding to each piece of reference index information at a column area of the initial index evaluation table according to all pieces of reference index information, and generating a first index evaluation table. The method calls a corresponding initial index evaluation table, the initial index evaluation table at least comprises a table head area and a column area, no reference index information exists in the column area of the initial index evaluation table, index name columns corresponding to each reference index information are obtained at the column area of the initial index evaluation table according to all the reference index information, and the index name columns comprise reference index information, such as company registered capital, the number of company personnel, product quotation and the like, as shown in fig. 2.
And S2, calculating by a preset intelligent review model according to actual index values corresponding to reference index information of a plurality of historical suppliers, determining a plurality of index information sections corresponding to each reference index information, and establishing a plurality of index information sections corresponding to each index name column in the first index evaluation table to obtain a second index evaluation table. The invention can preset an intelligent evaluation model, and the intelligent evaluation model can be calculated by combining with the actual index value at the moment, so as to obtain a plurality of index information sections corresponding to the reference index information. The actual index value at this time is the historical actual index value of the history provider.
It can be understood that different reference index information or different index information segments are provided. Taking the reference index information as the registered capital of the company as an example, the index information section at this time may be 0 to 250 ten thousand, 250 ten thousand to 500 ten thousand, 500 ten thousand to 750 ten thousand, and so on. Generally, the minimum value of each index information segment includes its own value, and the maximum value does not include its own value. That is, the index information section is 0 to 250 ten thousands, i.e., greater than or equal to 0 and less than 250 ten thousands.
In the present invention, a plurality of index information sections corresponding to each index name column are established in the first index evaluation table to obtain a second index evaluation table, as shown in fig. 3.
In a possible implementation manner, the technical solution provided by the present invention, step S2 includes:
the method comprises the steps of obtaining actual index values corresponding to any one reference index information dimension of a plurality of historical suppliers, and extracting the maximum index value and the minimum index value in the actual index values. The invention can count the actual index values of all historical suppliers and extract the maximum index value and the minimum index value. For example, the maximum index value may be 1000 million registered capital and the minimum index value may be 100 million registered capital.
And generating a corresponding first index interval according to the maximum index value and the minimum index value, and dividing the first index interval into a plurality of first type index information sections according to the number of the historical suppliers. The method generates a corresponding first index interval according to the maximum index value and the minimum index value, wherein the first index interval is 100 to 900 thousands at the moment, so that the registered capital of all history suppliers at the moment is respectively in the first index interval, and the method divides the first index interval into a plurality of first type index information sections according to the number of the history suppliers, wherein the index information sections are 100 to 500 thousands and 500 to 900 thousands for example.
And generating a maximum completion interval according to the maximum index value and a preset maximum value, generating a minimum completion interval according to the minimum index value and a preset minimum value, and taking the maximum completion interval and the minimum completion interval as a second type of index information section. The present invention generates the maximum completion interval according to the maximum index value and the preset maximum value, for example, if the preset maximum value is infinity, the maximum completion interval at this time is 900 to infinity. The present invention generates the minimum completion interval according to the minimum index value and the preset minimum value, for example, the preset minimum value is 0, and the minimum completion interval at this time is 0 to 100 ten thousand.
And summarizing the first type of index information block section and the second type of index information block section, and establishing a plurality of index information block sections corresponding to each index name column in a first index evaluation table. The invention can collect the first type of index information section and the second type of index information section to obtain a plurality of final index information sections. That is, the index information segment at this time may be 0 to 100 ten thousand, 100 to 500 ten thousand, 500 to 900 ten thousand, 900 to infinity.
In one possible implementation, the generating a corresponding first index section according to the maximum index value and the minimum index value, and dividing the first index section into a plurality of first type index information sections according to the number of the historical suppliers includes:
and performing one-time halving processing on the first index interval to obtain a plurality of index subintervals, and counting the number of historical suppliers in each index subinterval. The present invention first performs a halving process on the first index interval, taking the first index interval as 100 to 900 ten thousand as an example, the halving process at this time obtains a plurality of index subintervals of 2, the 1 st is 100 to 500 ten thousand, and the 2 nd is 500 to 900 ten thousand.
And if the number of the historical suppliers in at least one index subinterval is judged to be larger than the division stopping number, performing halving processing on all the index subintervals again respectively to obtain a plurality of index subintervals subjected to secondary halving processing. If the number of the historical suppliers in one index subinterval is larger than the division stopping number, the number of the suppliers in the corresponding index subinterval is proved to be large, and if the quantization processing is carried out on the index subinterval according to the mode, a plurality of suppliers have corresponding quantization index values, so that effective and transverse differential calculation and comparison cannot be carried out among the suppliers. Therefore, as long as the number of the history suppliers in any index subinterval is larger than the division stopping number, the invention can continuously perform the halving process on all the index subintervals respectively. Taking the process of halving again 100 to 500 ten thousand as an example, the 2 index subintervals at this time may be 100 to 300 ten thousand and 300 to 500 ten thousand, respectively.
And after judging that the condition of stopping the equal division processing is reached, stopping performing the equal division processing on all the index subintervals, and taking each index subinterval as an index information interval of a first type. The method can continuously halve the index subintervals, so that the interval value in each index subinterval is corresponding. And after reaching the condition of stopping the equal division processing, the invention stops the processing of halving the index subinterval, and the default obtained index subinterval meets the requirement of quantifying the index.
In a possible embodiment, the stopping the halving process of all the index subintervals after determining that the condition for stopping the halving process is reached, and taking each index subinterval as an index information interval of a first type includes:
and if the number of the historical suppliers in all the index subintervals is judged to be less than or equal to the division stopping number, judging that the condition of stopping the equal division is met. When the condition for stopping the equal division processing is set, the equal division processing can be stopped when the number of the historical suppliers is respectively less than or equal to the division stopping number, the number of the historical suppliers can be 2, 3 and the like, and the method ensures that a plurality of historical suppliers do not have the same index quantization value when the indexes of the historical suppliers are quantized, thereby realizing the automatic division of the number and the interval value of the index subintervals and ensuring that the subsequent degree of distinction is more realized when the quantization value of the current supplier is calculated.
And if the number of times of halving the index subinterval is judged to be more than or equal to a first preset number of times, judging that the condition of stopping the halving processing is reached. In an actual calculation scenario, some extreme scenarios may occur, for example, the registered capital of a plurality of history providers is the same, and no matter how the halving process is performed, the number of history providers in a certain index sub-interval is large, so the present invention may set the number of halving times, that is, when the number of halving times in the index sub-interval is greater than or equal to the first preset number, the halving process is not performed on the corresponding index sub-interval any more, and it is determined that the condition for suspending the halving process is reached at this time.
And S3, calculating by a preset intelligent review model according to the reference weight corresponding to each piece of reference index information, determining the quantitative index value corresponding to each index information section of each piece of reference index information, and establishing the quantitative index value corresponding to each index information section in the second index evaluation table to obtain a third index evaluation table. According to the technical scheme provided by the invention, the quantitative index value corresponding to each index information segment can be obtained by calculation according to the intelligent review model. In the actual purchasing process, different purchasing demands may have different evaluation requirements for the provider, for example, in some scenarios, the strength of the provider may be required to be more vigorous, and at this time, the indexes such as the registered capital, the number of people, the business volume, the profit amount, etc. of the provider are configured with higher weights, that is, the corresponding evaluation score is higher. For example, in some situations, it may be necessary to reduce the cost, and at this time, the price quoted by the supplier is required to be low, and at this time, a higher weight is set for the price quoted by the supplier, that is, the evaluation score corresponding to the price quoted by the supplier is higher. After the quantization index value corresponding to each index information segment is obtained, the quantization index value corresponding to each index information segment is established in the second index evaluation table, and a third index evaluation table is obtained according to the quantization index value corresponding to the index information segment, as shown in fig. 4.
In a possible implementation manner, the technical solution provided by the present invention, in step S3, includes:
and calculating according to the full score review value input by the user and the reference weight corresponding to each piece of reference index information to obtain the full score of the index corresponding to each piece of reference index information. The full-scale evaluation value and the reference weight corresponding to each piece of reference index information are combined to calculate, for example, the full-scale evaluation value is 100 points, the reference weight can be a decimal number smaller than 1 and larger than 0, the sum of all the reference weights can be 1, for example, the reference weight corresponding to the registered asset is 0.2, and then the index full-scale value corresponding to the registered asset is 20 points.
Calculating according to the index full score and the number of the first type of index information sections to obtain an index review difference value between every two adjacent index information sections, calculating the index review difference value through the following formula,
Figure 296622DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 450523DEST_PATH_IMAGE002
is as follows
Figure 300405DEST_PATH_IMAGE003
The index evaluation difference of each reference index information,
Figure 121731DEST_PATH_IMAGE004
the full score is the index of the full score,
Figure 267541DEST_PATH_IMAGE005
is as follows
Figure 174317DEST_PATH_IMAGE003
The reference weight corresponding to each piece of reference index information,xthe number of index information sections that are reference index information. By passing
Figure 63776DEST_PATH_IMAGE006
Index full score of corresponding reference index information can be obtained by
Figure 5187DEST_PATH_IMAGE007
An average score corresponding to each index information segment can be obtained, and the average score can be regarded as an index review difference value of the reference index information. For example, if the number of the index information sections is 4, and the index full score is 20, the index review difference at this time is 5, the reference index information corresponding to the 1 st first-type index information section is 5, the reference index information corresponding to the 2 nd first-type index information section is 10, the reference index information corresponding to the 3 rd first-type index information section is 15, and the reference index information corresponding to the 4 th first-type index information section is 20.
And setting the minimum completion interval corresponding to the value 0 and the maximum completion interval corresponding to the index full score, and sequentially increasing the index review difference value by starting from the minimum completion interval to obtain the quantitative index value corresponding to each index information interval. In an actual use scenario, indexes of a current supplier and indexes of a historical supplier may have a certain difference, so that the first index section needs to be correspondingly supplemented through the minimum supplementation section and the maximum supplementation section, all formed sections can cover index situations of all current suppliers, and all index ranges can have corresponding quantization index values.
At this time, on the basis of the previous 4 first-type index information sections, a maximum padding section and a minimum padding section are added, the quantization index value corresponding to the maximum padding section is 20, and the quantization index value corresponding to the minimum padding section is 0. At this time, there are 6 index information sections, and the quantization index values corresponding to the 6 index information sections are shown in table 1:
Figure 321899DEST_PATH_IMAGE008
TABLE 1
And S4, if the intelligent form request is judged to be received, generating a calculation function of corresponding reference index information according to the index information section and the quantitative index value corresponding to each piece of reference index information, and generating a corresponding intelligent calculation table based on the calculation function and the third index evaluation table. The method and the device consider that the third index evaluation table needs to be processed intelligently at the moment after judging that the intelligent table request is received, so the method and the device generate corresponding calculation functions according to the corresponding relation between the index information section and the quantized index value at the moment, and obtain the final intelligent calculation table by combining the calculation functions and the third index evaluation table.
In a possible implementation manner, the technical solution provided by the present invention, in step S4, includes:
and calling an initialized calculation function, wherein the calculation function comprises an input configuration interface and an output configuration interface. The invention firstly calls a calculation function which can be realized based on codes, the function is provided with at least two configuration interfaces, and the corresponding relation between the input value and the output value of the codes is respectively obtained through the two configuration interfaces.
And configuring the input of the calculation function through an input configuration interface, and taking the interval maximum value and the interval minimum value of each index information interval as the input interval of the calculation function. The input configuration interface configures the input of the calculation function, and the input configuration at this time can be regarded as compartmentalization, for example, 0 to 100 ten thousand, 100 ten thousand to 200 ten thousand, and the like. Namely 0 ten thousand are respectively used as the interval maximum value and the interval minimum value of the corresponding index information interval, and the 0 ten thousand are used as the input interval of one index information interval.
And configuring the output of the calculation function through an output configuration interface, and taking the quantization index value of the index information interval section as the output value of the calculation function. The invention can configure the output of the calculation function through the output configuration interface, and the corresponding quantization index value is taken as an output value at the moment. Each input interval will correspond to a different output value.
Through the mode, the method can automatically calculate according to the configured calculation function, and determine the corresponding output value according to the input interval where the input current index information is located, namely the corresponding quantitative index value.
Each index name column corresponds to an index input column and a quantization index column respectively, the calculation function is used for monitoring the index input column, determining a corresponding quantization index value according to the input index value of the index input column, and filling the quantization index value into the quantization index column. In an actual scenario, each index name column corresponds to an index input column and a quantization index column, as shown in fig. 5. The index input column can enable a supplier or a buyer to input current index data corresponding to the current supplier participating in supply and service, and the calculated quantitative index value can be displayed through the quantitative index column. So that the invention automatically generates the corresponding quantization index value.
And deleting the index information interval and the quantization index value in the third index evaluation table, and generating an intelligent calculation table according to the processed third index evaluation table and the configured calculation function. In some scenarios, the logic of quantization and the algorithm of review need to be hidden, so the present invention deletes the index information segment and the quantization index value to obtain an intelligent calculation table having an index input column and a quantization index column, as shown in fig. 6.
In a possible embodiment, the technical solution provided by the present invention further includes:
if the encryption request data is judged to be received, determining reference index information to be encrypted according to the encryption request data, establishing an information storage unit corresponding to the reference index information, and establishing a first slot position and a second slot position in the information storage unit. In the actual bidding, supplier's supply process, some indicators need to be kept secret, such as quotations, before opening the bid. In order to guarantee fairness, when all suppliers are opened, all suppliers need to be opened at the same time, further certain key and dynamic change factors in the process of opening the bids can be displayed at the same time, fairness of the bidding is guaranteed, and therefore certain reference index information needs to be encrypted before opening the bids, an information storage unit corresponding to the reference index information is established, and a first slot position and a second slot position are established in the corresponding information storage unit.
After the input index value is filled in the index input column corresponding to the reference index information to be encrypted, the input index value and the corresponding quantization index value are obtained, the input index value and the quantization index value are respectively filled in the first slot position and the second slot position, and the information storage unit is encrypted. The invention can respectively fill the input index value and the quantization index value into the first slot position and the second slot position, thereby realizing the storage of the input index value and the quantization index value, and then carry out encryption processing on the information storage unit, so that the input index value and the quantization index value positioned in the first slot position and the second slot position are encrypted.
And after the judgment information storage unit carries out encryption processing, displaying the corresponding input index value and the quantization index value in the intelligent calculation table according to preset characters. After the input index value and the quantization index value are encrypted and stored by the information storage unit, at this time, the real input index value and the real quantization index value in the intelligent calculation table need to be hidden, that is, the input index value and the real quantization index value are displayed according to a preset character, which may be XXXX, and the like.
In a possible embodiment, the technical solution provided by the present invention, after the input index value is filled in the index input column corresponding to the reference index information to be encrypted, acquiring an input index value and a corresponding quantization index value, respectively filling the input index value and the quantization index value into the first slot position and the second slot position, and encrypting the information storage unit, includes:
and performing character processing on the header information in each intelligent calculation table to obtain a corresponding header character string, and performing hash calculation according to the header character string to obtain an automatically generated automatic sub-key. The invention firstly carries out the character processing on the header information to obtain the corresponding header character string, and because the name of each supplier is different, the header information in each intelligent calculation table is also different, thereby leading the automatic sub-secret keys in each intelligent calculation table to be different at the moment.
And receiving the actively configured configuration sub-key, and assembling the automatic sub-key and the configuration sub-key to obtain the encryption key of the intelligent calculation table. Since the generation mode of the automatic sub-key is fixed, in order to make only the supplier know the encryption key, the supplier needs to input the corresponding configuration sub-key, and then assemble the automatic sub-key and the configuration sub-key to obtain the final encryption key. The automatic sub-key and the configuration sub-key can be assembled in a way that the automatic sub-key is configured before the configuration sub-key, and the final encryption key is obtained after the configuration sub-key is configured.
And after the first slot position and the second slot position in the information storage unit are judged to be filled with the input index value and the quantization index value and the confirmation encryption information is received, encrypting the corresponding information storage unit based on the encryption key. According to the technical scheme provided by the invention, when the reference index information of each dimension is encrypted, the reference index information is encrypted in steps, namely only when a first slot position and a second slot position corresponding to the reference index information are filled with an input index value and a quantization index value and two conditions for confirming the encryption information are received and reached simultaneously, the information storage unit of the reference index information of the corresponding dimension is encrypted, so that the input index value and the quantization index value after each encryption processing are complete and confirmed.
And counting the encrypted information storage units to generate a decryption correspondence table, wherein all the encrypted information storage units are in the decryption correspondence table. The invention can count all the encrypted information storage units to obtain the corresponding decryption correspondence table.
In a possible embodiment, the technical solution provided by the present invention further includes:
and configuring corresponding decryption logic for the decryption correspondence table.
And the decryption logic is used for calling input index values and quantization index values in all information storage units of the decryption correspondence table after receiving the decryption key corresponding to the encryption key, filling the input index values into corresponding index input columns, and filling the quantization index values into corresponding quantization index columns. Wherein the encryption key and the decryption key are corresponding. After receiving the decryption key corresponding to the encryption key, the invention fills the input index values and the quantization index values in all encrypted information storage units in the decryption correspondence table into the corresponding index input columns and fills the quantization index values into the corresponding quantization index columns, thereby realizing the uniform display of the input index values and the quantization index values.
Through the method, when the intelligent calculation table is filled in by a supplier, the supplier needs to fill in and confirm encryption one by one, and the accuracy of the filled numerical value is further ensured. When the invention is used for bidding, all the encrypted input index values and the encrypted quantization index values are simultaneously decrypted and correspondingly displayed, so that the bidding efficiency and the reviewing efficiency are improved.
And S5, intelligently reviewing the current index data of the historical suppliers or the newly added suppliers according to the third index evaluation table or the intelligent calculation table to obtain a current review result. According to different use requirements, the invention can carry out intelligent evaluation on the current index data of the historical suppliers or the newly-added suppliers needing to participate in bidding through the third index evaluation table or the intelligent calculation table so as to obtain a final current evaluation result, and the larger the numerical value in the current evaluation result is, the more the corresponding historical suppliers or the newly-added suppliers accord with the current bidding requirements.
In a possible implementation manner of the technical solution provided by the present invention, step S5 includes:
and acquiring an actual index value corresponding to the current index data of the historical supplier or the newly added supplier in each piece of reference index information, and inputting the actual index value into a corresponding third index evaluation table or an intelligent calculation table. The invention can obtain the current index data of the historical supplier or the newly added supplier, and inputs the actual index value of the current index data corresponding to the reference index information into the corresponding third index evaluation table or the intelligent calculation table for corresponding calculation.
And carrying out quantitative calculation on the actual index value based on the third index evaluation table or the intelligent calculation table to obtain the quantitative index value corresponding to each piece of reference index information. The invention can carry out quantization processing and calculation on the current actual index value of the supplier to obtain the corresponding quantization index value.
And calculating the quantitative index values corresponding to all the reference index information to obtain the current evaluation result of the corresponding historical supplier or the newly added supplier. And then, calculating the quantitative index values corresponding to all the reference index information, wherein the calculation mode can be summation calculation to obtain the current evaluation result of the corresponding historical supplier or the newly added supplier.
After the current evaluation results of all history suppliers or newly-added suppliers are obtained, the descending order can be carried out according to the numerical value of the current evaluation results, the history suppliers or the newly-added suppliers arranged at the front part can be regarded as suppliers meeting the requirements, and the history suppliers or the newly-added suppliers with the first name can be used as the next actual suppliers.
It should be noted that the history provider may be considered as a provider that has previously cooperated with the buyer and has entered the provider base, the new provider is a provider that has not cooperated previously and has entered the provider base, and in the actual bidding and bidding process, a new provider may participate in the corresponding bidding and bidding.
In order to implement the intelligent review method for digital procurement data provided by the invention, the invention also provides an intelligent review system for digital procurement data, as shown in fig. 7, comprising:
the system comprises a receiving module, a storage module and a display module, wherein the receiving module is used for receiving purchase demand information and reference index information input by a purchaser, determining a plurality of historical suppliers in a supplier library based on the purchase demand information, and generating a first index evaluation table based on the reference index information, and the first index evaluation table is provided with a plurality of index name columns corresponding to the reference index information;
the system comprises a building module, a first index evaluation table and a second index evaluation table, wherein the building module is used for calculating a preset intelligent review model according to actual index values corresponding to reference index information of a plurality of historical suppliers, determining a plurality of index information sections corresponding to each reference index information, and building a plurality of index information sections corresponding to each index name column in the first index evaluation table to obtain the second index evaluation table;
the calculation module is used for enabling a preset intelligent review model to calculate according to the reference weight corresponding to each piece of reference index information, determining the quantization index value corresponding to each index information section of each piece of reference index information, and establishing the quantization index value corresponding to each index information section in the second index evaluation table to obtain a third index evaluation table;
the generating module is used for generating a calculation function of corresponding reference index information according to the index information section and the quantitative index value corresponding to each piece of reference index information if the intelligent request of the table is judged to be received, and generating a corresponding intelligent calculation table based on the calculation function and the third index evaluation table;
and the evaluation module is used for intelligently evaluating the current index data of the historical suppliers or the newly added suppliers according to the third index evaluation table or the intelligent calculation table to obtain the current evaluation result.
In addition to the above embodiments, the present invention may have other embodiments; all technical solutions formed by adopting equivalent substitutions or equivalent transformations fall within the protection scope of the claims of the present invention.

Claims (9)

1. An intelligent review method for digital procurement data is characterized by comprising the following steps:
the method comprises the steps of S1, receiving purchase demand information and reference index information input by a purchaser, determining a plurality of historical suppliers in a supplier library based on the purchase demand information, and generating a first index evaluation table based on the reference index information, wherein the first index evaluation table is provided with a plurality of index name columns corresponding to the reference index information;
s2, calculating according to actual index values corresponding to reference index information of a plurality of historical suppliers, determining a plurality of index information sections corresponding to each reference index information, and establishing a plurality of index information sections corresponding to each index name column in the first index evaluation table to obtain a second index evaluation table;
s3, calculating according to the reference weight corresponding to each reference index information, determining the quantization index value corresponding to each index information section of each reference index information, and establishing the quantization index value corresponding to each index information section in the second index evaluation table to obtain a third index evaluation table;
s4, if judging that a table intelligent request is received, generating a calculation function of corresponding reference index information according to an index information section and a quantitative index value corresponding to each piece of reference index information, and generating a corresponding intelligent calculation table based on the calculation function and a third index evaluation table;
s5, intelligently reviewing the current index data of the historical suppliers or the newly added suppliers according to the third index evaluation table or the intelligent calculation table to obtain a current review result;
the step S2 comprises the following steps:
acquiring actual index values corresponding to any one reference index information dimension of a plurality of historical suppliers, and extracting the maximum index value and the minimum index value in the plurality of actual index values;
generating a corresponding first index interval according to the maximum index value and the minimum index value, and dividing the first index interval into a plurality of first type index information sections according to the number of the historical suppliers;
generating a maximum completion interval according to the maximum index value and a preset maximum value, generating a minimum completion interval according to the minimum index value and a preset minimum value, and taking the maximum completion interval and the minimum completion interval as a second type of index information section;
summarizing the first type of index information block section and the second type of index information block section, and establishing a plurality of index information block sections corresponding to each index name column in a first index evaluation table;
the generating a corresponding first index section according to the maximum index value and the minimum index value, and dividing the first index section into a plurality of first type index information sections according to the number of the historical suppliers includes:
performing first halving processing on the first index interval to obtain a plurality of index subintervals, and counting the number of historical suppliers in each index subinterval;
if the number of the historical suppliers in at least one index subinterval is judged to be larger than the dividing termination number, performing halving processing on all the index subintervals again respectively to obtain a plurality of secondary halved index subintervals;
stopping halving all the index subintervals after judging that the condition for terminating the halving processing is reached, and taking each index subinterval as a first type of index information interval;
after judging that the condition for terminating the equal dividing processing is reached, stopping performing the equal dividing processing on all the index subintervals, and taking each index subinterval as an index information interval of a first type, the method comprises the following steps:
if the number of the historical suppliers in all the index subintervals is judged to be less than or equal to the dividing termination number, judging that the condition of terminating the equal division is achieved; or
And if the number of times of halving the index subinterval is judged to be more than or equal to a first preset number of times, judging that the condition of ending the halving processing is reached.
2. The intelligent review method for digitized procurement data according to claim 1, characterized by that, step S1 comprises:
determining at least one purchase product according to the purchase demand information, and acquiring a plurality of historical suppliers related to the purchase product according to the purchase product, wherein each historical supplier has at least one corresponding purchase product;
generating header information at a header area of the initial index evaluation table based on the purchased product, the supplier name of the current supplier;
and obtaining an index name column corresponding to each piece of reference index information at a column area of the initial index evaluation table according to all pieces of reference index information, and generating a first index evaluation table.
3. The intelligent review method for digitized procurement data according to claim 1 characterized by that, step S3 comprises:
calculating according to the full score review value input by the user and the reference weight corresponding to each piece of reference index information to obtain the full score value of the index corresponding to each piece of reference index information;
calculating according to the index full score and the number of the first type of index information sections to obtain an index review difference value between every two adjacent index information sections, calculating the index review difference value through the following formula,
Figure 995704DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 978704DEST_PATH_IMAGE002
is as follows
Figure 560864DEST_PATH_IMAGE003
The index evaluation difference of each reference index information,
Figure 47340DEST_PATH_IMAGE004
the full score is the index of the full score,
Figure 823797DEST_PATH_IMAGE005
is as follows
Figure 28513DEST_PATH_IMAGE003
The reference weight corresponding to each piece of reference index information,
Figure 430676DEST_PATH_IMAGE006
the number of index information segments that are reference index information;
and setting the minimum completion interval corresponding to the value 0, and setting the maximum completion interval corresponding to the index full score, and sequentially increasing the index review difference value by starting from the minimum completion interval to obtain the quantization index value corresponding to each index information segment.
4. The intelligent review method for digitized procurement data of claim 3 wherein, step S4 comprises:
calling an initialized calculation function, wherein the calculation function comprises an input configuration interface and an output configuration interface;
configuring the input of a calculation function through an input configuration interface, and taking the interval maximum value and the interval minimum value of each index information interval as the input interval of the calculation function;
configuring the output of the calculation function through an output configuration interface, and taking the quantized index value of the index information interval as the output value of the calculation function;
each index name column corresponds to an index input column and a quantization index column respectively, the calculation function is used for monitoring the index input column, determining a corresponding quantization index value according to the input index value of the index input column, and filling the quantization index value into the quantization index column;
and deleting the index information interval and the quantization index value in the third index evaluation table, and generating an intelligent calculation table according to the processed third index evaluation table and the configured calculation function.
5. The intelligent review method for digitized procurement data of claim 4, characterized by further comprising:
if the encryption request data is judged to be received, determining reference index information to be encrypted according to the encryption request data, establishing an information storage unit corresponding to the reference index information, and establishing a first slot position and a second slot position in the information storage unit;
after the input index value is filled in the index input column corresponding to the reference index information to be encrypted, acquiring an input index value and a corresponding quantization index value, respectively filling the input index value and the quantization index value into a first slot position and a second slot position, and encrypting the information storage unit;
and after the judgment information storage unit carries out encryption processing, displaying the corresponding input index value and the quantization index value in the intelligent calculation table according to preset characters.
6. The intelligent review method for digitized procurement data according to claim 5,
after the input index value is filled in the index input column corresponding to the reference index information to be encrypted, the input index value and the corresponding quantization index value are obtained, the input index value and the quantization index value are respectively filled into the first slot position and the second slot position, and the information storage unit is encrypted, wherein the method comprises the following steps:
performing character processing on the header information in each intelligent calculation table to obtain a corresponding header character string, and performing hash calculation according to the header character string to obtain an automatically generated automatic sub-key;
receiving an actively configured configuration sub-key, and assembling the automatic sub-key and the configuration sub-key to obtain an encryption key of the intelligent calculation table;
after the first slot position and the second slot position in the information storage unit are judged to be filled with the input index value and the quantization index value and the confirmation encryption information is received, the corresponding information storage unit is encrypted based on the encryption key;
and counting the encrypted information storage units to generate a decryption correspondence table, wherein all the encrypted information storage units are arranged in the decryption correspondence table.
7. The intelligent review method for digitized procurement data of claim 6, characterized by further comprising:
configuring corresponding decryption logic for the decryption mapping table;
and the decryption logic is used for calling input index values and quantization index values in all information storage units of the decryption correspondence table after receiving the encryption key, filling the input index values in corresponding index input columns and filling the quantization index values in corresponding quantization index columns.
8. The intelligent review method for digitized procurement data according to claim 6, characterized by step S5 comprising:
acquiring actual index values of current index data of a historical supplier or a newly added supplier corresponding to each piece of reference index information, and inputting the actual index values into a corresponding third index evaluation table or an intelligent calculation table;
performing quantitative calculation on actual index values based on the third index evaluation table or the intelligent calculation table to obtain quantitative index values corresponding to each piece of reference index information;
and calculating the quantitative index values corresponding to all the reference index information to obtain the current evaluation result of the corresponding historical supplier or the newly added supplier.
9. An intelligent review system for digitized purchase data, comprising:
the system comprises a receiving module, a storage module and a display module, wherein the receiving module is used for receiving purchase demand information and reference index information input by a purchaser, determining a plurality of historical suppliers in a supplier library based on the purchase demand information, and generating a first index evaluation table based on the reference index information, and the first index evaluation table is provided with a plurality of index name columns corresponding to the reference index information;
the establishment module is used for calculating according to actual index values corresponding to reference index information of a plurality of historical suppliers, determining a plurality of index information sections corresponding to each reference index information, and establishing a plurality of index information sections corresponding to each index name column in the first index evaluation table to obtain a second index evaluation table;
the calculation module is used for calculating according to the reference weight corresponding to each piece of reference index information, determining the quantization index value corresponding to each index information section of each piece of reference index information, and establishing the quantization index value corresponding to each index information section in the second index evaluation table to obtain a third index evaluation table;
the generating module is used for generating a calculation function of corresponding reference index information according to the index information section and the quantitative index value corresponding to each piece of reference index information if judging that the intelligent table request is received, and generating a corresponding intelligent calculation table based on the calculation function and the third index evaluation table;
the evaluation module is used for intelligently evaluating the current index data of the historical suppliers or the newly increased suppliers according to the third index evaluation table or the intelligent calculation table to obtain a current evaluation result;
calculating according to actual index values corresponding to reference index information of a plurality of historical suppliers, determining a plurality of index information sections corresponding to each reference index information, establishing a plurality of index information sections corresponding to each index name column in the first index evaluation table, and obtaining a second index evaluation table, wherein the method specifically comprises the following steps:
acquiring actual index values corresponding to any one reference index information dimension of a plurality of historical suppliers, and extracting the maximum index value and the minimum index value in the plurality of actual index values;
generating a corresponding first index interval according to the maximum index value and the minimum index value, and dividing the first index interval into a plurality of first type index information sections according to the number of the historical suppliers;
generating a maximum completion interval according to the maximum index value and a preset maximum value, generating a minimum completion interval according to the minimum index value and a preset minimum value, and taking the maximum completion interval and the minimum completion interval as a second type of index information interval;
summarizing the first type of index information block section and the second type of index information block section, and establishing a plurality of index information block sections corresponding to each index name column in a first index evaluation table;
the generating a corresponding first index section according to the maximum index value and the minimum index value, and dividing the first index section into a plurality of first type index information sections according to the number of the historical suppliers includes:
performing first halving processing on the first index interval to obtain a plurality of index subintervals, and counting the number of historical suppliers in each index subinterval;
if the number of the historical suppliers in at least one index subinterval is judged to be larger than the division termination number, performing halving processing on all the index subintervals again respectively to obtain a plurality of index subintervals subjected to secondary halving processing;
stopping halving all the index subintervals after judging that the condition for terminating the halving processing is reached, and taking each index subinterval as a first type of index information interval;
after judging that the condition of ending the equal division processing is reached, stopping performing the equal division processing on all the index subintervals, and taking each index subinterval as an index information interval of a first type, comprising the following steps of:
if the number of the historical suppliers in all the index subintervals is judged to be less than or equal to the division termination number, judging that the condition of termination equal division processing is achieved; or
And if the number of times of halving the index subinterval is judged to be more than or equal to the first preset number of times, judging that the condition of ending the halving processing is reached.
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