Complex product matching and automatic quotation system based on intelligent AI

Abstract

The invention discloses a complex product matching and automatic quotation system based on intelligent AI, which relates to the technical field of automatic quotation and comprises a product query unit, a pricing mode determination unit, a price approval unit and a purchased product recommendation unit. The product information is subjected to fuzzy query through the product query unit, the bill of material corresponding to the current product is determined according to the content in the product list, and the form of the product is analyzed by using the bill of material, so that all sub-products contained in the product purchased by the user can be accurately identified through the design, and the user experience is improved. The method comprises the following steps of: selecting a plurality of sub-products, further refining a production mode and a pricing mode of each sub-product, executing corresponding operations for different pricing modes by utilizing a pricing mode determination unit, ensuring that each product is configured with a more reasonable price, and calculating a total authorization price corresponding to each product by utilizing a price approval unit, and the output price of the product is flexibly adjusted according to the discount rate corresponding to the transaction user, thereby ensuring smooth development of the business.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic quotation, and in particular to a complex product selection and automatic quotation system based on intelligent AI. Background Art

[0002] The complex product selection and automatic quotation system based on intelligent AI can help enterprises quickly and accurately improve product configuration and quotation, so that the sales team can quickly generate customized price plans according to customer needs. The invention patent with application number 202310589474.3 discloses "an intelligent quotation system and method, which belongs to the field of Internet application system technology and is used to solve the technical problem of low efficiency of existing quotation plans. The system includes: a product adding unit, which automatically identifies product information and product accessories information based on the three views of the product input by the administrator, and adds products; a quotation generation unit, which automatically generates a quotation based on the product transaction information input by the salesperson; a quotation output unit, which outputs the quotation to the customer based on the salesperson's selection. The present application automatically adds products through the above-mentioned system, reduces product adding time and accessories configuration time, and can automatically generate quotations based on product transaction information, thereby improving quotation work efficiency."

[0003] The above-mentioned existing technology solves the problems of low quotation efficiency and sales personnel spending a lot of time to prepare product lists. However, during the operation of the system, since the form of each product is not analyzed, each product may contain different sub-products, and the pricing methods of these sub-products may also be different. Relying entirely on manual calculation of the cost price increases the probability of errors, and the system cannot evaluate different products of the same type and cannot help users make more favorable decisions. Summary of the invention

[0004] The purpose of the present invention is to provide a complex product selection and automatic quotation system based on intelligent AI to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a complex product selection and automatic quotation system based on intelligent AI, comprising a product query unit, a pricing method determination unit, a price approval unit, a product selection recommendation unit and a product catalog management unit;

[0006] A product query unit, after inputting product information, the product query unit searches in the product list according to the information, determines the bill of materials corresponding to the current product, and analyzes the form of the product according to the bill of materials. Different product forms correspond to different production methods and pricing methods;

[0007] a pricing method determination unit, wherein when the pricing methods are different, the pricing method determination unit determines the corresponding sub-product information, obtains the cost price of the product, associates the product information with the cost price, and outputs the result through a visual interface;

[0008] The price approval unit, after receiving the cost price of the sub-product, conducts an evaluation and calculation by the finance department to determine the corresponding profit margin of the product, calculates the authorized total price of the product based on the profit margin and the cost price, calculates the authorized total price of the product based on the discount rate corresponding to the current user, obtains the corresponding transaction price of the product, automatically performs profit calculation and discount health prompts, and feeds these data back to the price approval department;

[0009] A product recommendation unit, which obtains the serial numbers and corresponding indicators of the same type of products to be purchased, constructs a corresponding decision matrix based on these data, calculates the feature proportions corresponding to different product serial numbers under fixed indicators based on the values ​​in the matrix, calculates the weights corresponding to all indicators through the feature proportions, calculates the corresponding evaluation coefficient using the weights and the indicator values ​​of each product, and sorts and outputs the products to be purchased according to the evaluation coefficients;

[0010] A product catalog management unit maintains and manages product information, displays a multi-level product structure, maintains hierarchical associations, and thus forms a BOM structure. It supports the maintenance and management of product configuration rules, sorts out configuration rule types, and outputs product management and rule configuration data through a visual interface. It maintains the product's standard configuration, optional items, and customized items, sets customization rules and customization levels, formulates configuration logic and constraint rules between product parameters, and automatically calculates the corresponding customization level based on user matching requirements.

[0011] Preferably, the product query unit includes a bill of materials determination module and a general product analysis module. After the bill of materials determination module inputs the brand, category name, series number, rated current, rated power, application scenario and protection level, it queries in the product list according to this set of data. If the query is successful, the bill of materials corresponding to the current product is determined. If the query fails, a query failure prompt message is returned. After receiving the product bill of materials, the general product analysis module uses deep learning technology to determine the form of the product according to the bill of materials. If the corresponding form is a single piece, it is determined that the production method of the product is self-made, and the pricing method is the system library price. If the corresponding form is a combination, the product production method includes two types, namely self-made and purchased, and the pricing method corresponding to the self-made part is the system library price, and the pricing method corresponding to the purchased part is the purchase inquiry. If the corresponding form is labeling, the product production method is purchased, and the pricing method is the purchase inquiry.

[0012] Preferably, the product query unit also includes a customized product analysis module and a project product analysis module. If the customized product analysis module corresponds to small customization, the product production method is self-production, and the pricing method is intelligent accounting. If the corresponding form is large customization, the product production methods include two, namely, self-production and purchase, and the pricing method corresponding to the self-production part is intelligent accounting, and the pricing method corresponding to the purchased part is manual pricing. If the project product analysis module corresponds to combination and customization, the product production methods include two, namely, self-production and purchase, and the pricing method corresponding to the self-production part is intelligent accounting, and the pricing method corresponding to the purchased part is manual pricing.

[0013] Preferably, the pricing method determination unit includes a price query module and an inquiry output module. When the pricing method is the system library price, the price query module determines the sub-product information corresponding to the self-made part, queries the price database based on the information, obtains the cost price of the product, associates the product information and the cost price, and outputs them through a visual interface. When the pricing method is the purchase inquiry, the inquiry output module determines the sub-product information corresponding to the purchased part, transmits it to the product center, and the product center returns the cost price corresponding to the product information. After associating the product information and the cost price, it is output through a visual interface.

[0014] Preferably, the pricing method determination unit also includes an intelligent accounting module and a manual accounting module. When the pricing method is intelligent accounting, the intelligent accounting module determines the sub-product information corresponding to the self-made part and transmits it to the product center. After the product center determines the labor cost, machine cost, production cost, experimental cost, material cost and transportation cost corresponding to the product, the cost analysis algorithm is used to calculate the cost price corresponding to the product according to each cost value and the corresponding weight, and outputs it through a visual interface. When the pricing method is manual pricing, the manual accounting module determines the sub-product information corresponding to the purchased part and transmits it to the product center. After the product center determines the purchase cost, installation cost, packaging cost and transportation cost corresponding to the product, the cost analysis algorithm is used to calculate the base price of the product according to each cost value and the corresponding weight, the financial center calculates the corresponding tariff, accumulates the base price and the tariff, and obtains the cost price corresponding to the product, which is output through a visual interface. The cost analysis algorithm is specifically as follows:

[0015] F=w0S0+w1S1+w2S2…+w n S n

[0016] Among them, F represents the total cost, w0,w1,w2,…w nIndicates the weights corresponding to different cost types, S0, S1, S2, ..., S n Indicates the corresponding values ​​of different expense types, and n indicates the total number of expense types.

[0017] Preferably, the price approval unit includes an authorized price setting module, a total price calculation module and an output price determination module. After the authorized price setting module receives the cost price of the sub-product, the finance department will conduct an evaluation and accounting to determine the profit margin corresponding to the product, and calculate the authorized price of the product based on the profit margin and the cost price. The total price calculation module counts the authorized prices and numbers of all sub-products included in the specified product, and then adds them up to obtain the authorized total price of the product. The output price determination module transmits the authorized total price of the product to the sales center, and the sales center calculates the authorized total price of the product based on the discount rate corresponding to the current user to obtain the transaction price corresponding to the product, performs profit estimation and discount health prompts based on the transaction price, and feeds it back to the price approval department, which performs manual review. After the review is passed, the product output price and product information are returned to the user interface.

[0018] Preferably, the product recommendation unit includes a matrix generation module and an entropy calculation module. After the matrix generation module obtains the numbers and corresponding indicators of the same type of products to be purchased, it constructs a corresponding decision matrix based on these data, and standardizes the matrix to obtain a standardized matrix. The entropy calculation module calculates the characteristic proportions corresponding to different product numbers under a fixed indicator based on the values ​​in the standardized matrix, and analyzes the characteristic proportions corresponding to different product numbers through an entropy analysis algorithm, thereby obtaining the entropy value corresponding to the current indicator.

[0019] Preferably, the product recommendation unit also includes an evaluation coefficient determination module and a product output module. The evaluation coefficient determination module counts the entropy values ​​corresponding to all indicators, determines the weight corresponding to each indicator according to the entropy value, and calculates the corresponding evaluation coefficient using the weight and the indicator value of each product. The product output module sorts the products to be purchased according to the evaluation coefficient, obtains product information in the product list, and outputs it in sequence.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] The present invention performs fuzzy query on product information through the product query unit, determines the material list corresponding to the current product according to the content in the product list, and uses the material list to analyze the form of the product. Such a design can accurately identify all sub-products contained in the product selected by the user, and further refine the production method and pricing method of each sub-product, and use the pricing method determination unit to perform corresponding operations for different pricing methods to ensure that each product is configured with a more reasonable price, and use the price approval unit to calculate the corresponding authorized total price of the product according to the authorized price of the sub-products contained in each product, and flexibly adjust the output price of the product according to the discount rate corresponding to the transaction user to ensure the smooth development of the business, and set price intelligent early warning at the same time to reduce the cost of error correction, and the product recommendation unit will automatically recommend products with higher cost performance to help users make more favorable decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 Provides a schematic diagram of the overall system flow for an embodiment of the present invention;

[0023] Figure 2 A block diagram of the internal modules of a product query unit provided by an embodiment of the present invention;

[0024] Figure 3 A block diagram of the internal modules of a pricing method determination unit provided in an embodiment of the present invention;

[0025] Figure 4 A block diagram of the internal modules of the price approval unit provided by the embodiment of the present invention;

[0026] Figure 5 This is a block diagram of the internal modules of the product recommendation unit provided in an embodiment of the present invention.

[0027] In the figure: 1. Product query unit; 101. Bill of materials determination module; 102. General product analysis module; 103. Customized product analysis module; 104. Project product analysis module; 2. Pricing method determination unit; 201. Price query module; 202. Price inquiry output module; 203. Intelligent accounting module; 204. Manual accounting module; 3. Price approval unit; 301. Authorized price setting module; 302. Total price calculation module; 303. Output price determination module; 4. Product selection recommendation unit; 401. Matrix generation module; 402. Entropy value calculation module; 403. Evaluation coefficient determination module; 404. Product output module. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figure 1-5 , the present invention provides a technical solution: a complex product selection and automatic quotation system based on intelligent AI, including a product query unit 1, a pricing method determination unit 2, a price approval unit 3, a product selection recommendation unit 4 and a product catalog management unit 5;

[0030] Product query unit 1, after inputting product information, query in the product list according to the information, determine the bill of materials corresponding to the current product, analyze the form of the product according to the bill of materials, and different product forms correspond to different production methods and pricing methods;

[0031] The pricing method determination unit 2 determines the corresponding sub-product information when the pricing methods are different, obtains the cost price of the product, and outputs the product information and the cost price through a visual interface after associating them.

[0032] Price approval unit 3: After receiving the cost price of the sub-product, the finance department will evaluate and calculate the corresponding profit margin of the product, calculate the authorized total price of the product based on the profit margin and the cost price, calculate the authorized total price of the product based on the discount rate corresponding to the current user, and obtain the corresponding transaction price of the product. The unit will automatically calculate the profit and discount health prompt, and feed back these data to the price approval department;

[0033] The product recommendation unit 4 obtains the serial numbers and corresponding indicators of the same type of products to be purchased, and then constructs a corresponding decision matrix based on these data, calculates the characteristic proportions corresponding to different product serial numbers under fixed indicators based on the values ​​in the matrix, and calculates the weights corresponding to all indicators through the characteristic proportions, and calculates the corresponding evaluation coefficient using the weights and the indicator values ​​of each product, and sorts and outputs the products to be purchased according to the evaluation coefficients;

[0034] Product catalog management unit 5: Product catalog management unit 5 maintains and manages product information, displays multi-level product structure, maintains hierarchical associations, thereby forming a BOM structure, supports product configuration rule maintenance and management, sorts out configuration rule types, and outputs product management and rule configuration data through a visual interface, maintains product standard configurations, optional items, and customized items, sets customization rules and customization levels, formulates configuration logic and constraint rules between product parameters, and automatically calculates corresponding customization levels based on user matching requirements.

[0035] The product query unit 1 includes a bill of materials determination module 101 and a general product analysis module 102. After the bill of materials determination module 101 inputs the brand, category name, series number, rated current, rated power, application occasion and protection level, it searches in the product list according to this set of data. If the search is successful, the bill of materials corresponding to the current product is determined. If the search fails, a query failure prompt message is returned. After receiving the product bill of materials, the general product analysis module 102 uses deep learning technology to determine the form of the product according to the bill of materials. If the corresponding form is a single piece, it is determined that the production method of the product is self-made, and the pricing method is the system library price. If the corresponding form is a combination, the production method of the product includes two types, namely self-made and purchased, and the pricing method corresponding to the self-made part is the system library price, and the pricing method corresponding to the purchased part is the purchase inquiry. If the corresponding form is labeling, the production method of the product is purchased, and the pricing method is the purchase inquiry;

[0036] The product query unit 1 also includes a customized product analysis module 103 and a project product analysis module 104. If the corresponding form of the customized product analysis module 103 is small customization, the production method of the product is self-made, and the pricing method is intelligent accounting. If the corresponding form is large customization, the product production methods include two, namely, self-made and purchased, and the pricing method corresponding to the self-made part is intelligent accounting, and the pricing method corresponding to the purchased part is manual pricing. If the corresponding form of the project product analysis module 104 is combination and customization, the product production methods include two, namely, self-made and purchased, and the pricing method corresponding to the self-made part is intelligent accounting, and the pricing method corresponding to the purchased part is manual pricing.

[0037] The pricing method determination unit 2 includes a price query module 201 and a price inquiry output module 202. When the pricing method is the system library price, the price query module 201 determines the sub-product information corresponding to the self-made part, queries the price database based on the information, obtains the cost price of the product, associates the product information with the cost price, and outputs it through a visual interface. When the pricing method is the purchase inquiry, the price inquiry output module 202 determines the sub-product information corresponding to the purchased part, transmits it to the product center, and the product center returns the cost price corresponding to the product information. After associating the product information with the cost price, it is output through a visual interface.

[0038] The pricing method determination unit 2 also includes an intelligent accounting module 203 and a manual accounting module 204. When the pricing method is intelligent accounting, the intelligent accounting module 203 determines the sub-product information corresponding to the self-made part and transmits it to the product center. After the product center determines the labor cost, machine cost, production cost, experimental cost, material cost and transportation cost corresponding to the product, the cost analysis algorithm is used to calculate the cost price corresponding to the product according to each cost value and the corresponding weight, and outputs it through a visual interface. When the pricing method is manual pricing, the manual accounting module 204 determines the sub-product information corresponding to the purchased part and transmits it to the product center. After the product center determines the purchase cost, installation cost, packaging cost and transportation cost corresponding to the product, the cost analysis algorithm is used to calculate the base price of the product according to each cost value and the corresponding weight, the financial center calculates the corresponding tariff, accumulates the base price and the tariff, and obtains the cost price corresponding to the product, which is output through a visual interface. The specific cost analysis algorithm is:

[0039] F=w0S0+w1S1+w2S2…+w n S n

[0040] Among them, F represents the total cost, w0,w1,w2,…w n Indicates the weights corresponding to different cost types, S0, S1, S2, ..., S n Indicates the corresponding values ​​of different expense types, and n indicates the total number of expense types;

[0041] The price approval unit 3 includes an authorized price setting module 301, a total price calculation module 302 and an output price determination module 303. After the authorized price setting module 301 receives the cost price of the sub-product, the finance department will evaluate and calculate to determine the corresponding profit margin of the product, and calculate the authorized price of the product based on the profit margin and the cost price. The total price calculation module 302 counts the authorized prices and numbers of all sub-products included in the specified product, and then adds them up to obtain the authorized total price of the product. The output price determination module 303 transmits the authorized total price of the product to the sales center, and the sales center calculates the authorized total price of the product based on the discount rate corresponding to the current user to obtain the transaction price corresponding to the product, and performs profit measurement and discount health prompts based on the transaction price, and feeds it back to the price approval department, which performs manual review. After the review is passed, the product output price and product information are returned to the user interface;

[0042] The product recommendation unit 4 includes a matrix generation module 401 and an entropy value calculation module 402. After the matrix generation module 401 obtains the numbers and corresponding indicators of the same type of products to be purchased, it constructs a corresponding decision matrix based on these data, and standardizes the matrix to obtain a standardized matrix. The entropy value calculation module 402 calculates the characteristic proportions corresponding to different product numbers under a fixed indicator based on the values ​​in the standardized matrix, and analyzes the characteristic proportions corresponding to different product numbers through an entropy value analysis algorithm, thereby obtaining the entropy value corresponding to the current indicator. The entropy value analysis algorithm is specifically as follows:

[0043]

[0044] Among them, a y represents the entropy value corresponding to the yth indicator, q xy represents the characteristic weight corresponding to the xth product number under the yth indicator, m represents the total number of product numbers, and x and y represent parameters;

[0045] The product recommendation unit 4 also includes an evaluation coefficient determination module 403 and a product output module 404. After the evaluation coefficient determination module 403 counts the entropy values ​​corresponding to all indicators, it determines the weight corresponding to each indicator according to the entropy value, and calculates the corresponding evaluation coefficient using the weight and the indicator value of each product. The product output module 404 sorts the products to be purchased according to the evaluation coefficient, obtains product information in the product list, and outputs it in sequence.

[0046] Working principle: The present invention determines the bill of materials corresponding to the current product through the bill of materials determination module 101 in the product query unit 1. After receiving the product bill of materials, the general product analysis module 102 determines the form of the product according to the bill of materials. When the form is single piece, combination and labeling, the production method and pricing method of the product are analyzed. The customized product analysis module 103 analyzes the production method and pricing method corresponding to the small customization and large customization forms. The project product analysis module 104 analyzes the production method and pricing method of the product when the form is combination and customization. The price query module 201 in the pricing method determination unit 2 obtains the cost price of the product when the pricing method is the system library price. The inquiry output module 202z obtains the cost price of the product when the pricing method is the purchase inquiry. The intelligent accounting module 20 When the pricing method is intelligent accounting, the cost price of the product is obtained. When the pricing method is manual pricing, the manual accounting module 204 obtains the cost price of the product, calculates the authorized price of the product through the authorized price setting module 301 in the price approval unit 3, obtains the authorized total price of the product through the total price calculation module 302, returns the product output price and product information to the user interface, constructs the corresponding decision matrix through the matrix generation module 401 in the product recommendation unit 4, and the entropy value calculation module 402 analyzes the feature proportions corresponding to different product numbers to obtain the entropy value corresponding to the current indicator. The evaluation coefficient determination module 403 uses the weight and the indicator value of each product to calculate the corresponding evaluation coefficient, and the product output module 404 outputs the product information to be purchased in sequence.

[0047] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0048] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A complex product selection and automatic quotation system based on intelligent AI, comprising a product query unit (1), a pricing method determination unit (2), a price approval unit (3), a product selection recommendation unit (4) and a product catalog management unit (5), characterized in that: A product query unit (1), after inputting product information, the product query unit (1) searches in a product list according to the information, determines a bill of materials corresponding to the current product, and analyzes the form of the product according to the bill of materials, where different product forms correspond to different production methods and pricing methods; A pricing method determination unit (2), wherein when the pricing methods are different, the pricing method determination unit (2) determines the corresponding sub-product information, obtains the cost price of the product, and associates the product information with the cost price, and then outputs the result through a visual interface; The price approval unit (3) receives the cost price of the sub-product, and then the finance department evaluates and calculates the profit margin corresponding to the product, calculates the authorized total price of the product based on the profit margin and the cost price, calculates the authorized total price of the product based on the discount rate corresponding to the current user, obtains the transaction price corresponding to the product, automatically calculates the profit and discount health prompt, and feeds back the data to the price approval department; A product recommendation unit (4), wherein the product recommendation unit (4) obtains the serial numbers and corresponding indicators of the same type of products to be purchased, and then constructs a corresponding decision matrix based on these data, calculates the characteristic proportions corresponding to different product serial numbers under fixed indicators based on the values ​​in the matrix, calculates the weights corresponding to all indicators based on the characteristic proportions, calculates the corresponding evaluation coefficient using the weights and the indicator value of each product, and sorts and outputs the products to be purchased according to the evaluation coefficients; A product catalog management unit (5), wherein the product catalog management unit (5) maintains and manages product information, displays a multi-level product structure, maintains hierarchical associations, thereby forming a BOM structure, supports product configuration rule maintenance and management, sorts out configuration rule types, and outputs product management and rule configuration data through a visual interface, maintains product standard configurations, optional items, and customized items, sets customization rules and customization levels, formulates configuration logic and constraint rules between product parameters, and automatically calculates corresponding customization levels according to user selection requirements.

2. The complex product selection and automatic quotation system based on intelligent AI according to claim 1 is characterized by: The product query unit (1) comprises a bill of materials determination module (101) and a general product analysis module (102). After the bill of materials determination module (101) inputs the brand, category name, series number, rated current, rated power, application occasion and protection level, it searches in the product list according to the set of data. If the search is successful, the bill of materials corresponding to the current product is determined. If the search fails, a query failure prompt message is returned. After receiving the product bill of materials, the general product analysis module (102) uses deep learning technology to determine the form of the product according to the bill of materials. If the corresponding form is a single piece, it is determined that the production method of the product is self-made and the pricing method is the system library price. If the corresponding form is a combination, the product production method includes two types, namely self-made and purchased, and the pricing method corresponding to the self-made part is the system library price, and the pricing method corresponding to the purchased part is the purchase inquiry. If the corresponding form is labeling, the product production method is purchased and the pricing method is the purchase inquiry.

3. The complex product selection and automatic quotation system based on intelligent AI according to claim 2 is characterized by: The product query unit (1) also includes a customized product analysis module (103) and a project product analysis module (104). If the customized product analysis module (103) corresponds to small customization, the product production method is self-made, and the pricing method is intelligent accounting. If the corresponding form is large customization, the product production method includes two methods, namely, self-made and purchased, and the pricing method corresponding to the self-made part is intelligent accounting, and the pricing method corresponding to the purchased part is manual pricing. If the project product analysis module (104) corresponds to combination and customization, the product production method includes two methods, namely, self-made and purchased, and the pricing method corresponding to the self-made part is intelligent accounting, and the pricing method corresponding to the purchased part is manual pricing.

4. The complex product selection and automatic quotation system based on intelligent AI according to claim 1 is characterized by: The pricing method determination unit (2) includes a price query module (201) and a price inquiry output module (202). When the pricing method is the system library price, the price query module (201) determines the sub-product information corresponding to the self-made part, queries the price database based on the information, obtains the cost price of the product, associates the product information with the cost price, and outputs them through a visual interface. When the pricing method is the purchase inquiry, the price inquiry output module (202) determines the sub-product information corresponding to the purchased part, transmits it to the product center, and the product center returns the cost price corresponding to the product information. After associating the product information with the cost price, it outputs it through a visual interface.

5. The complex product selection and automatic quotation system based on intelligent AI according to claim 4 is characterized by: The pricing method determination unit (2) also includes an intelligent accounting module (203) and a manual accounting module (204). When the pricing method is intelligent accounting, the intelligent accounting module (203) determines the sub-product information corresponding to the self-made part and transmits it to the product center. After the product center determines the labor cost, machine cost, production cost, experimental cost, material cost and transportation cost corresponding to the product, it uses the cost analysis algorithm to calculate the cost price corresponding to the product according to each cost value and the corresponding weight, and outputs it through a visual interface. When the pricing method is manual pricing, the manual accounting module (204) determines the sub-product information corresponding to the purchased part and transmits it to the product center. After the product center determines the purchase cost, installation cost, packaging cost and transportation cost corresponding to the product, it uses the cost analysis algorithm to calculate the base price of the product according to each cost value and the corresponding weight, and the financial center calculates the corresponding tariff, accumulates the base price and the tariff to obtain the cost price corresponding to the product, and outputs it through a visual interface.

6. The complex product selection and automatic quotation system based on intelligent AI according to claim 1 is characterized by: The price approval unit (3) comprises an authorized price setting module (301), a total price calculation module (302) and an output price determination module (303). After receiving the cost price of the sub-product, the authorized price setting module (301) performs an evaluation and calculation to determine the profit margin corresponding to the product, and calculates the authorized price of the product based on the profit margin and the cost price. The total price calculation module (302) counts the authorized prices and numbers of all sub-products included in the specified product, and then adds them up to obtain the authorized total price of the product. The output price determination module (303) transmits the authorized total price of the product to the sales center, and the sales center calculates the authorized total price of the product based on the discount rate corresponding to the current user to obtain the transaction price corresponding to the product. The profit is calculated and the discount health prompt is given based on the transaction price, and the feedback is sent to the price approval department, which performs manual review. After the review is passed, the product output price and product information are returned to the user interface.

7. The complex product selection and automatic quotation system based on intelligent AI according to claim 1 is characterized by: The product selection and recommendation unit (4) comprises a matrix generation module (401) and an entropy value calculation module (402). After the matrix generation module (401) obtains the serial numbers and corresponding indicators of the same type of products to be selected and constructed a corresponding decision matrix according to these data, the matrix is ​​standardized to obtain a standardized matrix. The entropy value calculation module (402) calculates the characteristic proportions corresponding to different product numbers under a fixed indicator according to the values ​​in the standardized matrix, and analyzes the characteristic proportions corresponding to different product numbers through an entropy value analysis algorithm, thereby obtaining the entropy value corresponding to the current indicator.

8. The complex product selection and automatic quotation system based on intelligent AI according to claim 7 is characterized by: The product selection and recommendation unit (4) further comprises an evaluation coefficient determination module (403) and a product output module (404). The evaluation coefficient determination module (403) determines the weight corresponding to each indicator according to the entropy value after counting the entropy values ​​corresponding to all indicators, and calculates the corresponding evaluation coefficient using the weight and the indicator value of each product. The product output module (404) sorts the products to be selected and purchased according to the evaluation coefficient, obtains product information in the product list, and outputs it in sequence.

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