CN114926126A - Multi-channel information data analysis system and method based on artificial intelligence - Google Patents

Multi-channel information data analysis system and method based on artificial intelligence Download PDF

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CN114926126A
CN114926126A CN202210606265.0A CN202210606265A CN114926126A CN 114926126 A CN114926126 A CN 114926126A CN 202210606265 A CN202210606265 A CN 202210606265A CN 114926126 A CN114926126 A CN 114926126A
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涂长青
赵小春
周正
刘晓静
左向群
肖晓莉
黄丹凤
杨俊�
张小波
刘振亮
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Hunan New Changhai Technology Industry Development Co Ltd
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Abstract

The invention relates to a multi-channel information data analysis system and a method based on artificial intelligence, wherein the system comprises a receiving module, a first processing module and a second processing module, wherein the receiving module is used for receiving required product information of a user enterprise, and the required product information comprises a required product name, a first required quantity and an enterprise name; the acquisition module is used for acquiring information of a plurality of production projects of the enterprise at the current time according to the name of the enterprise; an evaluation module for evaluating the potential demand of the demand product name based on the production project information; the comparison module compares the first demand quantity with the potential demand quantity to obtain a comparison result; the correction module corrects the reference quotation according to the comparison result to form corrected quotation information; and the sending module is used for sending the corrected quotation information to a user enterprise. The acceptance degree of the enterprise user to correct the quotation information of the required product is improved, and the purchasing success rate is improved.

Description

Multi-channel information data analysis system and method based on artificial intelligence
Technical Field
The invention relates to the technical field of data processing, in particular to a multi-channel information data analysis system and method based on artificial intelligence.
Background
In the actual production cycle, the purchasing personnel needs to purchase the elements required in the production process on the purchasing platform so as to complete the production processing of the produced product. When a buyer purchases on the purchasing platform, a waiter corresponding to the purchasing platform needs to quote the elements, so that after the buyer pays, the transaction between the waiter and the manufacturer based on the purchasing platform is completed.
Patent document with publication number CN114331629A discloses a project type cloud quotation method, which includes building a cloud quotation platform based on SAAS at the cloud end, and assembling a PC end, a mobile end and a cloud storage interface; the cloud quotation platform inputs corresponding merchant information data in a product library, a price library and a scheme library of a cloud quotation background management system in advance, a user selects preset industries, scenes and configurations at mobile end and PC end inlets according to requirements, and a multi-person collaborative quotation interface is created to realize a user inlet of cloud quotation; the cloud quotation platform is connected with a merchant website and a mobile terminal of a project scheme through an API (application programming interface), receives a user request of a merchant, matches a preset product library, a preset price library and a preset scheme library based on the option requirement of a user, and outputs a project quotation and a project solution through an intelligent algorithm; a user of the system can inquire and operate a website and a mobile terminal of a merchant of the project scheme on line through the Internet to obtain quoted prices, and the functions of forwarding, downloading, inquiring and modifying are realized to finish the project quoted prices and the scheme output.
However, the existing quotation method is based on the option requirement of the user, so as to form a product library based on the option requirement of the user, if the option of the user is unique, the quotation is constant over time, so that the quotation of the product cannot be dynamically adjusted.
Disclosure of Invention
Therefore, the invention provides a multi-channel information data analysis system and method based on artificial intelligence, which can solve the problem that the quotation based on products in the prior art can not be dynamically adjusted.
In order to achieve the above object, the present invention provides an artificial intelligence-based multi-channel information data analysis system, comprising:
the system comprises a receiving module, a processing module and a display module, wherein the receiving module is used for receiving required product information of a user enterprise, and the required product information comprises a required product name, a first required quantity and an enterprise name to which the required product information belongs;
the acquisition module is used for acquiring information of a plurality of production projects of the enterprise at the current time according to the name of the enterprise;
the evaluation module is used for evaluating the potential demand of the demand product name based on the production project information;
the comparison module is used for comparing the first demand with the potential demand to obtain a comparison result;
the correction module corrects the reference quotation according to the comparison result to form corrected quotation information;
and the sending module is used for sending the corrected quotation information to a user enterprise.
Further, the obtaining, by the obtaining module, information of a plurality of production items of the enterprise currently running at the time according to the name of the enterprise includes:
the method comprises the steps of obtaining a plurality of items of information according to names of enterprises, wherein the items of information are historical item types, item amounts and item periods, finished items and ongoing items exist in the historical item types, the item amounts and the item periods of the finished items are used for evaluating the ongoing item periods, the actual completion conditions of the ongoing items influence the progress of the items, and the required product amount in ongoing production is evaluated according to the occupation ratio of the finished item types of the historical item types and the item types of the ongoing production item information in all the item information from the obtained plurality of items of information according to the names of the enterprises.
Further, if the ratio of the quantity of the finished items in the historical item types to the quantity of the items in the ongoing production item information is less than or equal to 20%, the ongoing items belong to novel items in the enterprise, the future demand is large, and a first evaluation coefficient k1 is set;
if the ratio of the quantity of the items with the completed item type being equal to the item type of the on-going production item information in the historical item type of more than or equal to 90% to the quantity of all the items information is more than 20%, indicating that the on-going item belongs to a conversion item in the enterprise, the future demand is medium, and the like, setting a second evaluation coefficient k 2;
if the ratio of the quantity of the finished items in the historical item types to the quantity of the items of the on-going production item information is more than 90%, the on-going items belong to the traditional items in the enterprise, the future demand is small, and a third evaluation coefficient k3 is set.
Further, if the number of the history items is n1, there are three item types of a type, B type and C type, wherein the number of the items of a type in the history items is a1, the number of the items of B type is B1, the number of the items of C type is C1, obviously a1+ B1+ C1= n1, the current ongoing item is of a type, the position of the ongoing item in the enterprise is determined, and an evaluation coefficient is set according to the role of the item in the enterprise, if a1/n1>90%, the ongoing item is represented as a traditional item;
if 90% ≧ a1/n1>20%, this indicates that the item in progress belongs to the conversion item;
if a1/n1 is less than or equal to 20%, it indicates that the ongoing item belongs to a new type item.
Further, the potential demand of the required product name is evaluated based on the production project information, and when an evaluation coefficient of a project currently in progress is obtained, the potential demand of the required product name is obtained by combining the evaluation coefficient on the basis of the demand of the user.
Further, the step of obtaining the potential demand quantity of the name of the demand product by combining the evaluation coefficient on the basis of the demand quantity of the user comprises the following steps:
setting the first demand output by the user to be Q1, and combining the first evaluation coefficient k1 on the basis of the demand output by the user to obtain a first potential demand Q11 as follows: q11= Q1 × (
Figure 816629DEST_PATH_IMAGE001
) ；
When the second evaluation coefficient k2 is combined on the basis of the user demand, the obtained first potential demand Q21 is: q21= Q1 × (
Figure 166839DEST_PATH_IMAGE002
) ；
When the third evaluation coefficient k3 is combined on the basis of the user demand, the obtained first potential demand Q31 is: q31= Q1 × (
Figure 725996DEST_PATH_IMAGE003
)。
Further, by setting the standard deviation value Δ Q0;
if the absolute value delta Q of the actual difference between the new first demand and the potential demand is less than or equal to delta Q0, the difference between the new first demand and the potential demand is small, and the reference quotation does not need to be corrected;
if the absolute value Δ Q > Δ Q0 of the actual difference between the new first demand and the potential demand indicates that the magnitude of the difference between the new first demand and the potential demand is large, the reference quote is corrected.
Furthermore, when the reference quotation is corrected according to the comparison result, a reference quotation M0 is preset, when the correction is not needed, the reference quotation M0 is directly used as correction quotation information and sent to a user enterprise, and when the correction is needed, the reference quotation M0 is increased or decreased;
if the new first demand is greater than the potential demand, raising the base quote M0;
if the new first demand is < the potential demand, the base quote M0 is lowered.
In another aspect, the present invention further provides an artificial intelligence-based multi-channel information data analysis method using the artificial intelligence-based multi-channel information data analysis system as described above, including:
receiving required product information of a user enterprise, wherein the required product information comprises a required product name, a first required quantity and an enterprise name to which the required product information belongs;
the acquisition module is used for acquiring information of a plurality of production projects of the enterprise at the current time according to the name of the enterprise;
evaluating a potential demand amount of the demand product name based on the production project information;
comparing the first demand quantity with the potential demand quantity to obtain a comparison result;
correcting the reference quotation according to the comparison result to form corrected quotation information;
and sending the corrected quotation information to a user enterprise.
Further, the obtaining of the information of the plurality of production items of the enterprise currently running at the time according to the name of the enterprise includes:
the method comprises the steps of obtaining a plurality of items of information according to names of enterprises, wherein the items of information are historical item types, item amounts and item periods, finished items and ongoing items exist in the historical item types, the item amounts and the item periods of the finished items are used for evaluating the ongoing item periods, the actual completion conditions of the ongoing items influence the progress of the items, and the required product amount in ongoing production is evaluated according to the occupation ratio of the finished item types of the historical item types and the item types of the ongoing production item information in all the item information from the obtained plurality of items of information according to the names of the enterprises.
Compared with the prior art, the method has the advantages that the received name of the required product, the first demand and the enterprise name are used as the information of the required product, so that three pieces of information are effectively extracted from the received information, the information of the required product can be quickly received, the receiving time is greatly saved, and the receiving efficiency is improved.
Particularly, the potential demand of the enterprise is predicted based on the name of a required product and the item information generated by the enterprise in the process of generating the item information, the reference quotation information is corrected according to the potential demand and the first demand actually input by the user, and the corrected quotation information matched with the current state of the enterprise is formed.
Particularly, the type of the ongoing project is judged, and the actual demand of the user is evaluated based on the judgment result, so that the quantity of the obtained potential demand is more accurate, more reasonable quotation can be conveniently obtained according to the potential demand, and the transaction success rate is improved.
Particularly, whether the reference quotation needs to be corrected or not is determined according to the difference relation between the new first demand and the potential demand, so that multiple items of information based on enterprise users are effectively analyzed, the quotation information of the enterprise users is more accurate, and compared with the quotation according to the user value in the prior art, the quotation information of the user enterprises in the embodiment of the invention can reflect the operation conditions and project conditions of the user enterprises, the effective adjustment of the quotation information is realized, the individual demands of the quotation of different enterprise users are improved, the different quotation information is provided for different enterprise users, and the user stickiness is improved.
Particularly, by setting the reference quotation M0, the relation between the new first demand and the potential demand is compared, and the reference quotation is determined to be increased or decreased according to different relations, so that the information of the reference quotation is more accurate, the quotation information of the enterprise user is more accurate, the viscosity between the enterprise user and the purchasing platform is increased, the quotation information of the user enterprise is more accurate, and the enterprise user is more satisfied.
Drawings
Fig. 1 is a schematic structural diagram of an artificial intelligence-based multi-channel information data analysis system according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described in conjunction with the following examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, the system for analyzing multi-channel information data based on artificial intelligence according to an embodiment of the present invention includes:
the system comprises a receiving module 10, a processing module and a display module, wherein the receiving module is used for receiving required product information of a user enterprise, and the required product information comprises a required product name, a first required amount and an affiliated enterprise name;
the acquisition module 20 acquires information of a plurality of production projects of the enterprise currently in progress according to the name of the enterprise to which the enterprise belongs;
an evaluation module 30 for evaluating a potential demand amount of the demand product name based on the production project information;
the comparison module 40 is used for comparing the first demand with the potential demand to obtain a comparison result;
the correction module 50 corrects the reference quotation according to the comparison result to form corrected quotation information;
and the sending module 60 is used for sending the corrected quotation information to the user enterprises.
Specifically, in the process of receiving the required product information of the user enterprise, the receiving module is provided with the key-in boxes so that the enterprise user inputs the required product information in the key-in boxes according to the requirement of the enterprise user, in the practical application, the plurality of key-in boxes are arranged, the required product information is received in a sequential mode, and in the practical application, the information input by the user can be more.
Specifically, according to the embodiment of the invention, the potential demand of the enterprise is predicted based on the name of the required product and the item information generated by the enterprise in progress, the reference quotation information is corrected according to the potential demand and the first demand actually input by the user, and the corrected quotation information matched with the current state of the enterprise is formed.
Specifically, the step of acquiring information of a plurality of ongoing production projects of the enterprise at the current time according to the name of the enterprise comprises the following steps:
the method comprises the steps of obtaining a plurality of items of information according to names of enterprises, wherein the items of information are historical item types, item amounts and item periods, finished items and ongoing items exist in the historical item types, the item amounts and the item periods of the finished items are used for evaluating the ongoing item periods, the actual completion conditions of the ongoing items influence the progress of the items, and the required product amount in ongoing production is evaluated according to the occupation ratio of the finished item types of the historical item types and the item types of the ongoing production item information in all the item information from the obtained plurality of items of information according to the names of the enterprises.
If the proportion of the quantity of the finished items in the historical item types to the quantity of the items in the same item types as the quantity of the items in the ongoing production item information in all the item information is less than or equal to 20 percent, the ongoing items belong to novel items in the enterprise, the future demand is large, and a first evaluation coefficient k1 is set;
if the proportion of the quantity of the items with the types of the items which are more than or equal to 90% and more than or equal to the type of the items of the historical item information and the type of the items of the ongoing production item information in all the item information quantities is more than 20%, the ongoing items belong to conversion items in enterprises, the future demand is medium, and the like, a second evaluation coefficient k2 is set;
if the proportion of the quantity of the finished items in the historical item types to the quantity of the items of the on-going production item information is more than 90 percent of the quantity of all the items of the on-going production item information, the on-going items belong to the traditional items in the enterprise, the future demand is small, and a third evaluation coefficient k3 is set.
Specifically, in the embodiment of the present invention, by taking the ratio of the type of the current item in the history items into account, in practical applications, if the number of the history items is n1, there are three item types, i.e., a type, B type and C type, where the number of the items of the a type in the history items is a1, the number of the items of the B type is B1, and the number of the items of the C type is C1, it is obvious that a1+ B1+ C1= n1, if the currently ongoing item is the a type, the position of the ongoing item in the enterprise is determined, and an evaluation coefficient is set according to the role of the item in the enterprise, and if a1/n1>90%, the ongoing item is represented as a traditional item;
if 90% ≧ a1/n1>20%, this indicates that the item in progress belongs to the conversion item;
if a1/n1 is 20% or less, it means that the item being processed belongs to the new type item.
Specifically, the potential demand of the demand product name is evaluated based on the production project information, and when an evaluation coefficient of a project currently in progress is acquired, the potential demand of the demand product name is acquired by combining the evaluation coefficient on the basis of the demand of the user.
Specifically, the method and the device for evaluating the actual demand of the user based on the judgment result judge the type of the ongoing project, so that the obtained number of the potential demand is more accurate, more reasonable quotation can be obtained conveniently according to the potential demand, and the transaction success rate is improved.
Specifically, the step of obtaining the potential demand of the product name by combining the evaluation coefficient on the basis of the demand of the user comprises the following steps:
setting the first demand output by the user to be Q1, and combining the first evaluation coefficient k1 on the basis of the demand output by the user to obtain a first potential demand Q11 as follows: q11= Q1 × (
Figure 314104DEST_PATH_IMAGE001
) ；
When the second evaluation coefficient k2 is combined on the basis of the user demand, the obtained first potential demand Q21 is: q21= Q1 × (
Figure 769356DEST_PATH_IMAGE002
) ；
When the third evaluation coefficient k3 is combined on the basis of the user demand, the obtained first potential demand Q31 is: q31= Q1 × (
Figure 72774DEST_PATH_IMAGE003
)。
Specifically, the embodiment of the invention adjusts the first demand output by the user, so that the quantity determination of the potential demand is more accurate, the quotation information obtained based on the demand and the enterprise project information is more accurate, the transaction success rate of the enterprise user and the purchasing platform is effectively improved, and the viscosity of the enterprise user is effectively increased.
Specifically, when the first demand is compared with the potential demand, the new first demand is formed after the coupon dynamics coefficient c is increased on the basis of the first demand.
In practical application, when a user is quoted, a discount strength coefficient is set according to the name of an enterprise user and the industry comment, the discount strength coefficient is a coefficient set for the user enterprise, in actual life, if the credit of the user enterprise is better, the network comment is good, and the discount strength coefficient given to the user enterprise is larger, so that the quoted price for the user enterprise is higher than the price corresponding to the actual quantity based on the quantity also required by the user enterprise, the discount strength coefficient is increased on the basis of the first demand, the new first demand is slightly higher than the first demand input by the actual user enterprise, and the difference between the new first demand and the potential demand is not much, and in the process of obtaining a comparison result, the embodiment of the invention sets a standard difference delta Q0;
if the absolute value delta Q of the actual difference value of the two is less than or equal to delta Q0, the difference amplitude between the new first demand quantity and the potential demand quantity is small, and the reference quotation is not required to be corrected;
if the absolute value Δ Q of the actual difference between the two is greater than Δ Q0, which indicates that the difference between the new first demand and the potential demand is large, the reference quote needs to be corrected.
Specifically, according to the embodiment of the invention, whether the reference quotation needs to be corrected is determined according to the difference relationship between the new first demand and the potential demand, so that the effective analysis is performed on the multiple items of information based on the enterprise users, and the quotation information of the enterprise users is more accurate.
Specifically, when the reference quoted price is corrected according to the comparison result, the reference quoted price M0 is preset, when the correction is not needed, the reference quoted price M0 is directly used as the corrected quoted price information and is sent to the user enterprise, and when the correction is needed, the reference quoted price M0 is increased or decreased;
if the new first demand > the potential demand, then the base quote M0 is raised;
if the new first demand is < the potential demand, the base quote M0 is lowered.
Specifically, by setting the reference quotation M0, the embodiment of the present invention compares the relationship between the new first demand and the potential demand, and determines to increase or decrease the reference quotation according to different relationships, so that the information of the reference quotation is more accurate, the quotation information for the enterprise user is more accurate, the stickiness between the enterprise user and the purchasing platform is improved, and the quotation information for the user enterprise is more accurate and more suitable for the enterprise user.
Specifically, the multi-channel information data analysis method based on artificial intelligence provided by the embodiment of the invention comprises the following steps: receiving required product information of a user enterprise, wherein the required product information comprises a required product name, a first required quantity and an enterprise name to which the required product information belongs;
acquiring information of a plurality of production projects of the enterprise currently at the time according to the name of the enterprise to which the enterprise belongs;
evaluating a potential demand amount of the demand product name based on the production project information;
comparing the first demand quantity with the potential demand quantity to obtain a comparison result;
correcting the reference quotation according to the comparison result to form corrected quotation information;
and sending the corrected quotation information to a user enterprise.
Specifically, the obtaining of information of a plurality of production items of the enterprise currently running at the time according to the name of the enterprise includes:
the method comprises the steps of obtaining a plurality of items of information according to names of enterprises, wherein the items of information are historical item types, item amounts and item periods, finished items and ongoing items exist in the historical item types, the item amounts and the item periods of the finished items are used for evaluating the ongoing item periods, the actual completion conditions of the ongoing items influence the progress of the items, and the required product amount in ongoing production is evaluated according to the occupation ratio of the finished item types of the historical item types and the item types of the ongoing production item information in all the item information from the obtained plurality of items of information according to the names of the enterprises.
If the proportion of the quantity of the finished items in the historical item types to the quantity of the items in the same item types as the quantity of the items in the ongoing production item information in all the item information is less than or equal to 20 percent, the ongoing items belong to novel items in the enterprise, the future demand is large, and a first evaluation coefficient k1 is set;
if the proportion of the quantity of the items with the types of the items which are more than or equal to 90% and more than or equal to the type of the items of the historical item information and the type of the items of the ongoing production item information in all the item information quantities is more than 20%, the ongoing items belong to conversion items in enterprises, the future demand is medium, and the like, a second evaluation coefficient k2 is set;
if the proportion of the quantity of the finished items in the historical item types to the quantity of the items of the on-going production item information is more than 90 percent of the quantity of all the items of the on-going production item information, the on-going items belong to the traditional items in the enterprise, the future demand is small, and a third evaluation coefficient k3 is set.
Specifically, the multi-channel information data analysis method based on artificial intelligence provided in the embodiment of the present invention has the same technical solution as that of the multi-channel information data analysis system based on artificial intelligence, and can achieve the same technical effect, which is not described herein again.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is apparent to those skilled in the art that the scope of the present invention is not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention; various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A multi-channel information data analysis system based on artificial intelligence, comprising:
the system comprises a receiving module, a processing module and a display module, wherein the receiving module is used for receiving required product information of a user enterprise, and the required product information comprises a required product name, a first required quantity and an enterprise name to which the required product information belongs;
the acquisition module is used for acquiring information of a plurality of production projects of the enterprise at the current time according to the name of the enterprise;
the evaluation module is used for evaluating the potential demand of the demand product name based on the production project information;
the comparison module compares the first demand quantity with the potential demand quantity to obtain a comparison result;
the correction module corrects the reference quotation according to the comparison result to form corrected quotation information;
and the sending module is used for sending the corrected quotation information to a user enterprise.
2. The artificial intelligence based multi-channel information data analysis system of claim 1,
the acquiring module acquires information of a plurality of production projects of the enterprise currently in progress according to the name of the enterprise, and the acquiring module comprises the following steps:
the method comprises the steps of obtaining a plurality of items of information according to names of enterprises, wherein the items of information are historical item types, item amounts and item periods, finished items and ongoing items exist in the historical item types, the item amounts and the item periods of the finished items are used for evaluating the ongoing item periods, the actual completion conditions of the ongoing items influence the progress of the items, and the required product amount in ongoing production is evaluated according to the occupation ratio of the finished item types of the historical item types and the item types of the ongoing production item information in all the item information from the obtained plurality of items of information according to the names of the enterprises.
3. The artificial intelligence based multi-channel informational data analysis system of claim 2,
if the ratio of the quantity of the finished items in the historical item types to the quantity of the items in the ongoing production item information is less than or equal to 20%, indicating that the ongoing items belong to a novel item in the enterprise and the future demand is large, and setting a first evaluation coefficient k 1;
if the proportion of the quantity of the items with the types of the items which are more than or equal to 90% and more than or equal to the type of the items of the historical item information and the type of the items of the ongoing production item information in all the item information quantities is more than 20%, the ongoing items belong to conversion items in enterprises, the future demand is medium, and the like, a second evaluation coefficient k2 is set;
if the ratio of the quantity of the finished items in the historical item types to the quantity of the items of the on-going production item information is more than 90%, the on-going items belong to the traditional items in the enterprise, the future demand is small, and a third evaluation coefficient k3 is set.
4. The artificial intelligence based multi-channel information data analysis system of claim 3,
if the number of the history items is n1, three item types are respectively of A type, B type and C type, wherein the number of the items of the A type in the history items is a1, the number of the items of the B type is B1, the number of the items of the C type is C1, a1+ B1+ C1= n1, the currently ongoing item is of the A type, the position of the ongoing item in the enterprise is determined, an evaluation coefficient is set according to the role of the item in the enterprise, and if a1/n1>90%, the ongoing item is represented as a traditional item;
if 90% ≧ a1/n1>20%, this indicates that the item in progress belongs to the conversion item;
if a1/n1 is less than or equal to 20%, it indicates that the ongoing item belongs to a new type item.
5. The artificial intelligence based multi-channel informational data analysis system of claim 4 further including,
and evaluating the potential demand of the required product name based on the production project information, and combining the evaluation coefficient on the basis of the user demand to obtain the potential demand of the required product name when obtaining the evaluation coefficient of the project currently in progress.
6. The artificial intelligence based multi-channel information data analysis system of claim 5,
the method for obtaining the potential demand quantity of the product name based on the user demand quantity by combining the evaluation coefficient comprises the following steps:
setting the first demand output by the user as Q1, and when the first evaluation coefficient k1 is combined on the basis of the user demand, obtaining a first potential demand Q11 as: q11= Q1 × (
Figure 897062DEST_PATH_IMAGE001
) ；
When the second evaluation coefficient k2 is combined on the basis of the user demand, the obtained first potential demand Q21 is: q21= Q1 × (
Figure 470126DEST_PATH_IMAGE002
) ；
When the third evaluation coefficient k3 is combined on the basis of the user demand, the obtained first potential demand Q31 is: q31= Q1 × (
Figure 829563DEST_PATH_IMAGE003
)。
7. The artificial intelligence based multi-channel information data analysis system of claim 5, wherein the channel quality is determined by setting a standard deviation value Δ Q0;
if the absolute value delta Q of the actual difference between the new first demand and the potential demand is less than or equal to delta Q0, the difference between the new first demand and the potential demand is small, and the reference quotation does not need to be corrected;
if the absolute value Δ Q > Δ Q0 of the actual difference between the new first demand amount and the potential demand amount indicates that the difference between the new first demand amount and the potential demand amount is large, the reference bid amount needs to be corrected.
8. The artificial intelligence based multi-channel information data analysis system according to claim 7, wherein when the reference quotation is corrected according to the comparison result, a reference quotation M0 is previously set, when the correction is not required, the reference quotation M0 is directly transmitted to the user's enterprise as corrected quotation information, and when the correction is required for the reference quotation M0, the reference quotation is increased or decreased;
if the new first demand is greater than the potential demand, increasing the reference quote M0;
if the new first demand is < the potential demand, the base quote M0 is lowered.
9. An artificial intelligence based multi-channel information data analyzing method applying the artificial intelligence based multi-channel information data analyzing system according to any one of claims 1 to 8,
receiving required product information of a user enterprise, wherein the required product information comprises a required product name, a first required quantity and an enterprise name to which the required product information belongs;
the acquisition module is used for acquiring information of a plurality of production projects of the enterprise at the current time according to the name of the enterprise;
evaluating a potential demand amount of the demand product name based on the production project information;
comparing the first demand with the potential demand to obtain a comparison result;
correcting the reference quotation according to the comparison result to form corrected quotation information;
and sending the corrected quotation information to a user enterprise.
10. The artificial intelligence based multi-channel information data analysis method of claim 9,
the method for acquiring information of a plurality of production projects of the enterprise currently running according to the name of the enterprise comprises the following steps:
the method comprises the steps of obtaining a plurality of items of information according to names of enterprises, wherein the items of information are historical item types, item amounts and item periods, finished items and ongoing items exist in the historical item types, the item amounts and the item periods of the finished items are used for evaluating the ongoing item periods, the actual completion conditions of the ongoing items influence the progress of the items, and the required product amount in ongoing production is evaluated according to the occupation ratio of the finished item types of the historical item types and the item types of the ongoing production item information in all the item information from the obtained plurality of items of information according to the names of the enterprises.
CN202210606265.0A 2022-05-31 2022-05-31 Multi-channel information data analysis system and method based on artificial intelligence Pending CN114926126A (en)

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