Supplier recommendation method and device, computer program product, and electronic device

Abstract

The present disclosure relates to the field of data processing technology, and provides a supplier recommendation method and device, a computer program product, and an electronic device. The above method is applied to an offshore photovoltaic construction project, and different processes of the offshore photovoltaic construction project have different demand information for the same target raw material. The method includes: determining a candidate supplier of the target raw material from candidate manufacturers based on distance; classifying the candidate suppliers based on each evaluation index of the target raw material, and obtaining the classified results of the candidate suppliers corresponding to each evaluation index; obtaining the demand information of the target raw material for different processes of the offshore photovoltaic construction project, matching the demand information with the classified results at least once, and determining the recommended supplier of the target raw material for each process according to the matching results; and recommending the recommended supplier of the target raw material to the different process units of each process. This solution can improve the accuracy of supplier recommendation.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a supplier recommendation method applied to an offshore photovoltaic construction project, a supplier recommendation device applied to an offshore photovoltaic construction project, a computer program product, and an electronic device. Background Art

[0002] Offshore photovoltaics refers to the construction and operation of solar photovoltaic power generation in the marine environment, that is, using ocean space to install photovoltaic panels to convert solar energy into electrical energy.

[0003] Offshore photovoltaic construction projects involve many processes and many suppliers. The relevant technologies lack methods for intelligent management and allocation of suppliers in offshore photovoltaic construction projects, and it is impossible to make intelligent and accurate recommendations for suppliers.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the present disclosure is to provide a supplier recommendation method and device, a computer program product and an electronic device applied to offshore photovoltaic construction projects, so as to improve the accuracy of supplier recommendation for offshore photovoltaic projects at least to a certain extent, thereby improving the construction efficiency of offshore photovoltaic projects.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to a first aspect of the present disclosure, a supplier recommendation method applied to an offshore photovoltaic construction project is provided, wherein different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the method comprises: obtaining first location information corresponding to a production address of a candidate manufacturer of the target raw material and second location information corresponding to a construction address of the offshore photovoltaic construction project; determining a distance between the production address and the construction address based on the first location information and the second location information, and determining a candidate supplier of the target raw material from the candidate manufacturers based on the distance; classifying the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; obtaining demand information for the target raw material of different processes of the offshore photovoltaic construction project, matching the demand information with the classified result at least once, and determining a recommended supplier for the target raw material for each process based on the matching result, wherein each process corresponds to a process unit and the process units of each process are different; and recommending the recommended supplier of the target raw material to the process units of each process respectively.

[0008] According to a second aspect of the present disclosure, a supplier recommendation device for an offshore photovoltaic construction project is provided, wherein different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the device comprises: a location information acquisition module, configured to acquire first location information corresponding to a production address of a candidate manufacturer of the target raw material and second location information corresponding to a construction address of the offshore photovoltaic construction project; a candidate supplier determination module, configured to determine a distance between the production address and the construction address according to the first location information and the second location information, and determine a candidate supplier of the target raw material from the candidate manufacturers based on the distance; a classification module, configured to classify the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; a matching module, configured to acquire demand information for the target raw material of different processes of the offshore photovoltaic construction project, perform at least one level of matching between the demand information and the classified result, and determine a recommended supplier for the target raw material for each process according to the matching result, wherein each process corresponds to a process unit, and the process units of each process are different; and a recommendation module, configured to recommend recommended suppliers of the target raw material to the process units of each process respectively.

[0009] According to a third aspect of the present disclosure, a computer program product comprising instructions is provided, which, when executed on a computer, enables the computer to execute the steps of the supplier recommendation method applied to an offshore photovoltaic construction project as described in the first aspect.

[0010] According to a fourth aspect of an embodiment of the present disclosure, there is provided an electronic device, comprising: a processor; and a storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the supplier recommendation method applied to offshore photovoltaic construction projects as described in the first aspect of the above embodiment.

[0011] It can be seen from the above technical solutions that the supplier recommendation method applied to offshore photovoltaic construction projects, the supplier recommendation device applied to offshore photovoltaic construction projects, and the computer program product and electronic device for implementing the supplier recommendation method applied to offshore photovoltaic construction projects in the exemplary embodiments of the present disclosure have at least the following advantages and positive effects:

[0012] In the technical solutions provided in some embodiments of the present disclosure, for any target raw material of an offshore photovoltaic project, first, based on the distance between the production address of the candidate manufacturer of the target raw material and the construction address of the construction project, a candidate supplier is determined from the candidate manufacturers, and then the candidate suppliers are classified according to the evaluation index of the target raw material to obtain classified results corresponding to different evaluation indexes, and then based on the demand information of different processes for the target raw material and the matching of the classified results, recommended suppliers are determined for different processes, and the recommended suppliers are recommended to the process units of different processes. Compared with the related art, the present disclosure can accurately recommend suppliers that meet the needs of the process units corresponding to different processes of an offshore photovoltaic project for the same target raw material, thereby helping to improve the construction efficiency of the offshore photovoltaic project, avoid the situation where the construction progress of the offshore photovoltaic project is affected due to the wrong selection of suppliers, and reduce the potential risks of the offshore photovoltaic construction project.

[0013] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0015] Figure 1 A schematic diagram showing an exemplary system architecture to which the embodiments of the present disclosure can be applied is shown.

[0016] Figure 2A schematic flow chart showing a method for recommending suppliers for an offshore photovoltaic construction project according to an exemplary embodiment of the present disclosure.

[0017] Figure 3 A schematic flow chart showing a method for determining production capacity of a candidate supplier in an exemplary embodiment of the present disclosure.

[0018] Figure 4 A flowchart of a method for determining a recommended supplier for a target raw material for each process according to a matching result in an exemplary embodiment of the present disclosure is shown.

[0019] Figure 5 A flowchart diagram showing another method for determining a recommended supplier for a target raw material for each process according to matching results in an exemplary embodiment of the present disclosure.

[0020] Figure 6 A flowchart diagram of another method for determining a recommended supplier for a target raw material for each process according to matching results in an exemplary embodiment of the present disclosure is shown.

[0021] Figure 7 A schematic diagram showing the composition of a supplier recommendation device applied to an offshore photovoltaic construction project in an exemplary embodiment of the present disclosure.

[0022] Figure 8 A schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0023] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the example embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0024] The terms "a", "an", "the" and "said" are used in this specification to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express an open-ended inclusion and mean that additional elements / components / etc. may exist in addition to the listed elements / components / etc.; the terms "first" and "second" etc. are used only as labels and are not intended to limit the quantity of their objects.

[0025] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0026] In recent years, as inland land resources have become increasingly scarce, photovoltaic projects that cover a large area have begun to gradually expand their application scenarios to the vast ocean. Offshore photovoltaics can build and operate solar photovoltaic power generation in the marine environment, so offshore photovoltaics have broad prospects.

[0027] However, offshore photovoltaic construction projects involve numerous processes and a large number of suppliers. Relevant technologies lack methods for intelligent management and recommendation of offshore photovoltaic suppliers, resulting in low construction efficiency of offshore photovoltaic projects and affected construction progress.

[0028] In order to solve the above problems, the present invention provides a supplier recommendation method and device for offshore photovoltaic construction projects. The method and device can be applied to Figure 1 In the system architecture of the exemplary application environment shown.

[0029] like Figure 1 As shown, the system architecture 100 may include a terminal device 110 and a server 120. The terminal device 110 may be a terminal device such as a smart phone, a tablet computer, a desktop computer, a laptop computer, a smart wearable device, etc. The server 120 generally refers to a background system that provides related services of the supplier recommendation method applied to the offshore photovoltaic construction project in this exemplary embodiment, and may be a server or a cluster formed by multiple servers. The terminal device 110 and the server 120 may be connected via a wired or wireless communication link to perform data exchange.

[0030] In an exemplary embodiment, the above-mentioned supplier recommendation method applied to offshore photovoltaic construction projects can be executed by the server 120. Accordingly, the supplier recommendation device applied to offshore photovoltaic construction projects can be set in the server 120 to realize the corresponding module functions. For example, the server 120 can obtain the first location information corresponding to the production address of the candidate manufacturer of the target raw material and the second location information corresponding to the construction address of the offshore photovoltaic construction project, determine the distance between the production address and the construction address according to the first location information and the second location information, determine the candidate supplier of the target raw material from the candidate manufacturer based on the distance, classify the candidate supplier based on each evaluation index of the target raw material, obtain the classified result of the candidate supplier corresponding to each evaluation index, and store it in the database of the server 120. Then, the demand information of the process units of different processes of the offshore photovoltaic project for the target raw material can be sent to the server 120 through the terminal device 110, and then after receiving the demand information, the server 120 can match the demand information with the classified results stored in the database at least once, so as to determine the recommended supplier of the target raw material for each process according to the matching result, and recommend the recommended supplier of the target raw material to the process units of different processes.

[0031] It should be understood that Figure 1 The number of terminal devices and servers in the example is only illustrative. Any number of terminal devices and servers may be provided as required. For example, the server 120 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0032] Next, Figure 2 A schematic diagram of a process flow of a supplier recommendation method applied to an offshore photovoltaic construction project in an exemplary embodiment of the present disclosure is shown, wherein different processes of the offshore photovoltaic construction project have different demand information for the same target raw material. Figure 2 , the method comprising:

[0033] Step S210, obtaining first location information corresponding to the production address of the candidate manufacturer of the target raw material and second location information corresponding to the construction address of the offshore photovoltaic construction project;

[0034] Step S220, determining the distance between the production address and the construction address according to the first location information and the second location information, and determining a candidate supplier of the target raw material from the candidate manufacturers based on the distance;

[0035] Step S230, classifying the candidate suppliers based on each evaluation index of the target raw material, and obtaining a classified result of the candidate suppliers corresponding to each evaluation index;

[0036] Step S240, obtaining demand information of the target raw materials for different processes of the offshore photovoltaic construction project, performing at least one level matching between the demand information and the classified results, and determining a recommended supplier of the target raw materials for each process according to the matching results, wherein each process corresponds to a process unit, and the process units of each process are different;

[0037] Step S250 , recommending a recommended supplier of the target raw material to the process unit of each process.

[0038] exist Figure 2 In the technical solution provided by the illustrated embodiment, for any target raw material of an offshore photovoltaic project, first, based on the distance between the production address of the candidate manufacturer of the target raw material and the construction address of the construction project, a candidate supplier is determined from the candidate manufacturers, and then the candidate suppliers are classified according to the evaluation index of the target raw material to obtain classified results corresponding to different evaluation indexes, and then based on the demand information of different processes for the target raw material and the matching of the classified results, recommended suppliers are determined for different processes, and the recommended suppliers are recommended to the process units of different processes. Compared with the related art, the present disclosure can accurately recommend suppliers that meet the needs of the process units corresponding to different processes of an offshore photovoltaic project for the same target raw material, thereby helping to improve the construction efficiency of the offshore photovoltaic project, avoid the situation where the construction progress of the offshore photovoltaic project is affected due to the wrong selection of suppliers, and reduce the potential risks of the offshore photovoltaic construction project.

[0039] The following Figure 2 The specific implementation methods of each step in the embodiment shown are described in detail:

[0040] In step S210, first location information corresponding to the production address of a candidate manufacturer of the target raw material and second location information corresponding to the construction address of the offshore photovoltaic construction project are obtained.

[0041] In an exemplary embodiment, the target raw material may include any construction material in an offshore photovoltaic construction project, such as concrete, steel bars, etc., and this exemplary embodiment does not specifically limit this.

[0042] In an exemplary application scenario, the same target raw material is required in different processes of an offshore photovoltaic construction project, but different processes have different demand information for the target raw material.

[0043] Among them, the different processes of offshore photovoltaic projects include the construction process of booster station, the construction process of onshore power collection line, the construction process of cable laying, etc. For example, the target raw material A is needed in both the construction process of booster station and the construction process of onshore power collection line, but the construction process of booster station requires 5 tons of the first-level standard target raw material A, while the construction process of onshore power collection line requires 3 tons of the second-level standard target raw material A, and the procurement budget for the target raw material in the construction process of onshore power collection line is 10,000 yuan.

[0044] In an exemplary embodiment, the candidate manufacturers may include manufacturers that can produce target raw materials that meet the construction standards of the offshore photovoltaic project and are located in the administrative area to which the offshore photovoltaic project belongs. Candidate manufacturers may also include manufacturers that can produce target raw materials and participate in the bidding during the bidding stage. Candidate manufacturers can be customized and determined according to needs, and this exemplary embodiment does not specifically limit this.

[0045] In an exemplary embodiment, the production address of the candidate manufacturer may include the location coordinates of the factory address where the candidate manufacturer generates the target raw materials. The construction address of the offshore photovoltaic project may include the location coordinates of the construction material stacking address of the offshore photovoltaic project. In the present disclosure, the construction material stacking address is located at the construction site, or the distance between the construction material stacking address and the construction site is less than a first preset value.

[0046] In step S220, the distance between the production address and the construction address is determined according to the first location information and the second location information, and the candidate supplier of the target raw material is determined from the candidate manufacturers based on the distance.

[0047] For example, the distance between the production address and the construction address may include a straight-line distance or a shortest transportation distance, wherein the shortest transportation distance is determined according to a transportation route between the production address and the construction address.

[0048] For example, a specific implementation of step S220 may include: determining candidate manufacturers whose distance from the construction site is less than or equal to a preset distance threshold as candidate suppliers, that is, the recommended suppliers are within a predetermined geographical range of the construction site.

[0049] The method for determining the preset distance threshold may include: the number of candidate suppliers that can be determined by the preset distance is greater than or equal to the preset number. That is, the preset distance cannot be set too small, otherwise the selection range of suppliers will be too small.

[0050] In other words, for different target raw materials, the preset distance threshold is different. For example, if the preset number is 10, for target raw material A, when the preset distance threshold is 10 kilometers, 11 candidate suppliers can be determined, and when the preset distance threshold is less than 10 kilometers, 8 candidate suppliers can be determined, and the preset distance threshold of target raw material A is 10 kilometers. For target raw material B, when the preset distance threshold is 5 kilometers, 12 candidate suppliers can be determined, and when the preset distance threshold is less than 5 kilometers, 5 candidate suppliers can be determined, and the preset distance threshold of target raw material B is 5 kilometers.

[0051] Of course, the preset distance threshold may also be determined based on other information, and the preset distance threshold may be the same for different target raw materials, which is not particularly limited in this exemplary embodiment.

[0052] Next, continue to refer to Figure 2 In step S230, the candidate suppliers are classified based on each evaluation index of the target raw material to obtain the classified results of the candidate suppliers corresponding to each evaluation index.

[0053] In an exemplary embodiment, the evaluation index of the target raw material includes a production capacity index, a price index, and a quality index. Of course, the evaluation index of the target raw material may also include other evaluation indexes, such as whether it is environmentally friendly, etc., which is not particularly limited in this exemplary embodiment.

[0054] Exemplarily, a specific implementation of step S230 may include: classifying the candidate suppliers according to their production capacity of the target raw materials to obtain a production capacity classification table; classifying the candidate suppliers according to the prices of the target raw materials provided by the candidate suppliers to obtain a price classification table; classifying the candidate suppliers according to the quality of the target raw materials provided by the candidate suppliers to obtain a quality classification table.

[0055] Among them, for the capacity classification table, candidate suppliers belonging to the same capacity interval can be determined as the same capacity category according to different capacity intervals, thereby obtaining a capacity classification table for candidate suppliers. Among them, the range of the capacity interval can be customized according to demand, and this exemplary embodiment does not make special limitations on this, such as a capacity greater than or equal to 1 ton and less than 3 tons as one category, a capacity greater than or equal to 3 tons and less than 6 tons as one category, etc., but the range of the capacity interval cannot be too large, otherwise, the capacity of the same category may differ too much, resulting in inaccurate recommendations. Candidate suppliers can also be automatically clustered and classified based on capacity information according to a clustering algorithm to determine candidate suppliers with similar capacity as the same category, thereby obtaining a capacity classification table for candidate suppliers. Of course, candidate suppliers can also be classified based on capacity information in other ways, such as determining candidate suppliers with the same capacity as the same category.

[0056] For the price classification table, candidate suppliers belonging to the same price range can be determined as the same price category according to different price ranges, thereby obtaining a price classification table of candidate suppliers. The range of the price range can also be customized according to demand, and this exemplary embodiment does not specifically limit this. Similarly, the range of the price range cannot be too large, otherwise, the prices of the same category may differ too much, resulting in inaccurate recommendations. Candidate suppliers can also be automatically clustered and classified based on price information according to a clustering algorithm to determine candidate suppliers with similar prices as the same category, thereby obtaining a price classification table of candidate suppliers.

[0057] For the quality classification table, according to different quality standards, candidate suppliers with the same quality standards can be determined as the same quality category, thereby obtaining a quality classification table for candidate suppliers. Quality standards can also be graded, and candidate suppliers whose target raw materials meet the quality standards and belong to the same quality level can be determined as the same quality category, thereby obtaining a quality classification table for candidate suppliers. For example, quality standard A and quality standard B both belong to the first quality level, quality standard C and quality standard D both belong to the second quality level, and so on.

[0058] For example, Figure 3 A flow chart showing a method for determining the production capacity of a candidate supplier for a target raw material in an exemplary embodiment of the present disclosure is shown. Figure 3 The method may include steps S310 to S360. Wherein:

[0059] In step S310, the production information of the candidate supplier is obtained.

[0060] In an exemplary embodiment, the production information includes the equipment usage time, equipment failure number, equipment yield, equipment failure time, equipment output, number of laborers, working years of each laborer, and historical working hours of each laborer during the historical period of the supply cycle of the target raw materials of the offshore photovoltaic project.

[0061] For example, the production information of the candidate supplier may be provided directly by the candidate supplier, or may be determined by a staff member after inspecting the production environment of the candidate supplier, and this exemplary embodiment does not specifically limit this.

[0062] Among them, the supply cycle of target raw materials can be understood as the time period during which the target raw materials are required to be supplied for offshore photovoltaic construction projects. For example, if the target raw materials need to be provided within 30 days after the supply is confirmed, and the estimated time of supply confirmation is October 1, 2024, then the supply cycle of the target raw materials is from October 2, 2024 to October 31, 2024. The historical period can be understood as the historical time period with the same supply cycle in the past three years, such as October 2, 2023 to October 31, 2023, October 2, 2022 to October 31, 2022, and October 2, 2021 to October 31, 2021.

[0063] In step S320, the equipment state of the equipment within the supply cycle of the target raw materials of the offshore photovoltaic construction project is predicted based on the usage time of the equipment, the number of equipment failures and the equipment failure time.

[0064] In an exemplary embodiment, the device status includes a use status, a fault status, and a disabled status.

[0065] For example, a machine learning model can be trained based on sample data so that the machine learning model can predict the next equipment failure time based on the equipment usage time, equipment failure times and equipment failure time, and thus predict the equipment status of the equipment within the supply cycle of the target raw materials based on whether the next equipment failure time falls within the supply cycle of the target raw materials. If the predicted next equipment failure time falls within the supply cycle of the target raw materials, the equipment status of the equipment within the supply cycle of the target raw materials is a failure state, otherwise it is a use state.

[0066] The training data may include sample data and sample labels, wherein the sample data may include the equipment failure time, the number of times the equipment has failed before the failure time, and the length of time the equipment has been in use before the failure time, and the label data is the next failure time of the equipment.

[0067] In step S330, for each device, the device production capacity of the target raw material within the target raw material supply cycle of the offshore photovoltaic construction project is determined according to the device status, the device yield rate and the device output.

[0068] For example, the usage status in the equipment status can be assigned a value of 1, and the fault status in the equipment status can be assigned a value of 0. Then, based on the product of the equipment status, equipment yield rate and equipment output, the equipment production capacity of the target raw material during the supply cycle of the target raw material can be determined.

[0069] In step S340, the predicted working hours of each worker in the supply cycle of the target raw material are predicted based on the working hours of the worker in the same historical period of the supply cycle of the target raw material.

[0070] For example, the average working hours of each worker in multiple historical periods of the supply cycle of the target raw materials can be calculated, and the value can be used as the predicted working hours of the worker in the supply cycle of the target raw materials.

[0071] In step S350, the labor capacity within the supply cycle of the target raw materials of the offshore photovoltaic construction project is predicted based on the working years of each laborer, the number of laborers and the predicted working hours.

[0072] For example, the average productivity efficiency of labors with different years of service can be calculated in advance, and then used as the preset labor productivity efficiency of the labors with corresponding years of service. Among them, the average productivity efficiency can be understood as the output per hour. Then, for each laborer, the preset labor productivity efficiency corresponding to the laborer's years of service is obtained, and the production capacity of the laborer within the supply cycle of the target raw materials is predicted based on the preset labor productivity efficiency and the predicted working hours of the laborer within the supply cycle of the target raw materials. The sum of the production capacity of each laborer within the supply cycle of the target raw materials is determined as the labor capacity within the supply cycle of the target raw materials of the offshore photovoltaic construction project.

[0073] In step S360, the production capacity of the target raw material of the candidate supplier within the supply cycle of the target raw material of the offshore photovoltaic construction project is determined based on the equipment production capacity and the labor production capacity.

[0074] For example, the total equipment capacity can be determined according to the sum of the capacity of each device, and the total labor capacity can be determined according to the sum of the capacity of each labor force. Then, the sum of the total equipment capacity and the total labor capacity can be calculated to obtain the capacity of the target raw materials of the candidate suppliers during the supply cycle of the target raw materials for the offshore photovoltaic project.

[0075] In the present disclosure, the above-mentioned steps S310 to S360 can be used to predict the production capacity of the target raw materials of the candidate suppliers within the supply cycle of the target raw materials, so that the production capacity and the supply cycle are combined, and various factors affecting the production capacity are comprehensively considered. The situation of the factor within the supply cycle is predicted, thereby improving the accuracy of the production capacity determination, and then assisting in improving the accuracy of supplier recommendations, reducing the risk that the recommended supplier cannot provide the target raw materials in time due to various risk factors, resulting in the offshore photovoltaic construction project being unable to be completed on schedule.

[0076] Continue to refer Figure 2 In step S240, the demand information of the target raw materials for different processes of the offshore photovoltaic construction project is obtained, the demand information and the classified results are matched at least once, and the recommended supplier of the target raw materials for each process is determined according to the matching results.

[0077] In an exemplary embodiment, each process corresponds to a process unit, and the process units of each process are different. For example, in an offshore photovoltaic construction project, different processes correspond to different process units, and different process units using the same target raw materials have different requirements for the target raw materials. For example, a process unit requires a target raw material with quality standard A, and a process unit requires a target raw material with quality standard B, etc.

[0078] In the present disclosure, the recommended supplier for the target raw material for each process may be determined based on the demand information for the target raw material in different processes and the matching result of the classified results obtained in the above step S230.

[0079] Exemplarily, the demand information includes any one of demand quantity, budget price, and quality standard. Based on this, Figure 4 A flowchart of a method for determining a recommended supplier for a target raw material for each process according to a matching result in an exemplary embodiment of the present disclosure is shown. Figure 4, the method may include steps S410 to S430. Wherein: in step S410, for any process, when the demand information is the demand quantity, the demand information is matched with the capacity in the capacity classification table, so as to determine the candidate supplier whose capacity in the capacity classification table is greater than or equal to the demand quantity indicated by the demand information as the recommended supplier of the target raw material for the process; in step S420, for any process, when the demand information is the budget price, the demand information is matched with the price in the price classification table, so as to determine the candidate supplier whose price in the price classification table is less than or equal to the budget price indicated by the demand information as the recommended supplier of the target raw material for the process; in step S430, for any process, when the demand information is the quality standard, the first quality level to which the quality standard in the demand information belongs is determined, and the first quality level is matched with the quality level in the quality classification table, so as to determine the candidate supplier corresponding to the second quality level in the quality classification table whose quality level is higher than or equal to the first quality level as the recommended supplier of the target raw material.

[0080] Exemplarily, a specific implementation of step S430 may include: different quality standards may be classified in advance, and quality standards belonging to the same quality level may be classified into the same category, so as to establish a mapping relationship table between quality standards and quality levels. Then, the quality standard in the demand information is obtained, and the quality level corresponding to the quality standard is queried in the mapping relationship table between quality standards and quality levels, so as to obtain the first quality level. Then, the first quality level is matched with the quality level in the quality classification table, and the candidate supplier corresponding to the quality level whose quality standard indicated by the successfully matched quality level in the quality classification table is higher than the quality standard corresponding to the successfully matched quality level is determined as a recommended supplier.

[0081] Of course, if the quality classification table is classified and determined according to the same quality standard, the quality standard in the demand information and the quality standard in the quality classification table can also be directly matched. Then, the candidate supplier corresponding to the successfully matched quality standard is determined as the recommended supplier, and this exemplary embodiment does not specifically limit this.

[0082] Exemplarily, the demand information may also include at least two of the demand quantity, budget price, and quality standard. Based on this, Figure 5 A flowchart of another method for determining a recommended supplier for a target raw material for each process according to a matching result in an exemplary embodiment of the present disclosure is shown. Figure 5 , the method may include steps S510 to S530. Wherein:

[0083] In step S510, for each process, demand information of the process for the target raw material and the demand priority of the demand information are obtained.

[0084] For example, the client can input the demand information of each process for the target raw materials and the demand priority of the demand information. The demand information and demand priority are determined by each process unit according to its actual situation. For example, if the demand information of a process unit includes the demand quantity and the budget price, and the priority of the budget price is higher than the priority of the demand quantity, that is, in the subsequent matching, the candidate suppliers whose prices meet the budget price will be matched first.

[0085] In step S520, for the highest priority, a first-level matching is performed between the demand value indicated by the demand information of the highest priority and the classified results corresponding to the demand information to obtain the matching result of the highest priority.

[0086] In an exemplary implementation, the demand quantity in the demand information corresponds to the production capacity classification table, the budget price in the demand information corresponds to the price classification table, and the quality standard in the demand information corresponds to the quality classification table.

[0087] For example, the demand value indicated by the demand information with the highest priority can be matched with the classified result corresponding to the demand information at the first level to obtain the matching result of the demand information with the highest priority. For example, if the demand information includes demand quantity, budget price, quality standard, and the priority order is quality standard, budget price and demand quantity, that is, the quality standard has the highest priority, the budget price has the second priority, and the demand quantity has the lowest priority, the quality standard in the demand information and the quality classification table can be matched at the first level to obtain the matching result of the demand information with the highest priority. Among them, the specific implementation method of the first level matching of the quality standard in the demand information and the quality classification table can refer to the above-mentioned step S430, which will not be repeated here.

[0088] In step S530, for other priorities, according to the order of priority, the first category of candidate suppliers in the previous level matching results corresponding to the previous level priority of the priority is searched in the classified results corresponding to the demand information indicated by the current priority, the found first category is matched with the demand information indicated by the current priority, and the matching result of the current priority is determined based on the candidate suppliers in the previous level matching results that successfully matched the first category. This process is repeated until the current priority is the last priority, and the recommended supplier of the target raw material for the process is obtained based on the matching result of the last priority.

[0089] Continue to take the case where the demand information includes demand quantity, budget price, quality standard, and the priority order is quality standard, budget price and demand quantity, that is, the quality standard has the highest priority, the budget price has the second highest priority, and the demand quantity has the lowest priority. After obtaining the matching result of the quality standard, the current priorities are respectively the budget price and the demand quantity, that is, firstly, the second-level matching is performed based on the matching result of the budget price and the quality standard to obtain the matching result of the budget price, and then the third-level matching is performed based on the matching result of the budget price and the demand quantity, and the recommended supplier is obtained according to the matching result of the third-level matching. For example, after obtaining the matching result of the quality standard, for the candidate supplier included in the matching result of the quality standard, the price category to which the candidate supplier belongs can be searched in the price classification table, and the price category indicated by the budget price can be matched to obtain the matching result of the budget price, that is, the candidate supplier included in the matching result of the budget price satisfies both the quality standard and the budget price. Then, for the candidate supplier included in the matching result of the budget price, the capacity category to which the candidate supplier belongs can be searched in the capacity classification table corresponding to the demand quantity, and the capacity category can be matched with the capacity category indicated by the demand quantity to obtain the matching result of the demand quantity. Finally, the candidate suppliers in the demand matching results are used as recommended suppliers. The demand matching results may include one or more suppliers, and the one or more suppliers can simultaneously meet the quality standard, price budget and demand in the demand information.

[0090] The specific implementation of matching the price category with the price category indicated by the budget price can refer to the above step S420, and the specific implementation of matching the capacity category with the demand category can refer to the above step S410, which will not be repeated here.

[0091] In an exemplary embodiment, when the first category found in step S530 does not match the demand information indicated by the current priority, the candidate suppliers included in the previous level matching results are determined as recommended suppliers for the process, and a first prompt information is generated. The first prompt information is used to prompt the priorities met and not met by the current recommended supplier.

[0092] For example, after obtaining the matching results of the demand information with an earlier priority, when matching again with the demand information with a next priority, there may be a situation where none of the candidate suppliers in the matching results of the demand information with an earlier priority meets the demand value indicated by the demand information with a next priority. At this time, the candidate suppliers in the matching results of the demand information with an earlier priority can be directly used as recommended suppliers, and the first prompt information is generated based on the relevant information of the demand information after this priority for each recommended supplier.

[0093] Continuing with the example that the demand information includes demand quantity, budget price, quality standard, and the priority order is quality standard, budget price, and demand quantity, that is, the quality standard has the highest priority, the budget price has the second highest priority, and the demand quantity has the lowest priority, for example, after obtaining the matching result of the budget price, the production capacity of the candidate suppliers in the matching result of the budget price does not meet the demand quantity, then the candidate suppliers in the matching result of the budget price can be determined as recommended suppliers, and the first prompt information "The current recommended suppliers meet your quality and price requirements, but their production capacity cannot meet your demand quantity, you can make a combination selection to meet your demand quantity" is generated. At the same time, the first prompt information can also provide the production capacity information of each recommended supplier for the user to make a selection.

[0094] Exemplarily, when the demand information includes at least two of the demand quantity, budget price, and quality standard, another specific implementation of step S240 may include: for each process, matching each demand information with the classified results corresponding to the demand information, and obtaining matching results for each demand information; and determining the recommended supplier of the target raw material for the process based on the candidate suppliers existing in the matching results of each demand information.

[0095] For example, when a process includes multiple types of demand information, each type of demand information can be matched separately with its corresponding classified results to obtain their respective matching results, and then the intersection of their respective matching results is taken to determine the recommended supplier of the target raw material for the process based on the candidate suppliers in the intersection.

[0096] In this disclosure, the same target raw materials are used in different processes of the same offshore photovoltaic construction project, and suppliers of the same target raw materials in different production processes are recommended. In the recommended results, there may be multiple suppliers that can meet the needs of a certain production process at the same time. Users can choose one or more suppliers to cooperate according to their preferences or experience. Since the same supplier may meet the demand information of different processes at the same time, but the production capacity of a supplier is limited, special processing is required for this situation to ensure the timely supply of target raw materials, thereby ensuring the construction progress of the offshore photovoltaic construction project.

[0097] Based on this, for example, Figure 6 A flowchart of another method for determining a recommended supplier for a target raw material for each process according to a matching result in an exemplary embodiment of the present disclosure is shown. Figure 6 The method may include steps S610 to S650. Wherein:

[0098] In step S610, in response to a selection operation of any process unit on the recommended supplier, the recommended supplier indicated by the selection operation is determined as a target supplier of the process unit for the target raw material, and a first mark is added to the target supplier.

[0099] In an exemplary embodiment, the first mark is used to indicate the process unit supplied by the target supplier and the supply quantity provided for the process unit.

[0100] For example, after a process unit selects a supplier recommended to it, the recommended supplier indicated by the selection operation can be used as the target supplier of the target raw material of the process unit. The target supplier is the final supplier, that is, the target supplier is assigned to the process unit. After the target supplier is assigned to a process unit, a first mark can be added to the target supplier, and the first mark is used to indicate that the target supplier has been assigned, as well as the process unit assigned to the target supplier and the process unit's demand for the target raw material.

[0101] In step S620, when there is a candidate supplier with a first tag in the matching result, the demand quantity of the process, the production capacity of the candidate supplier with the first tag, and the supply quantity indicated by the first tag are obtained.

[0102] In step S630, the remaining capacity of the candidate supplier with the first mark is determined according to the capacity and the supply.

[0103] In step S640, when the remaining capacity is greater than the demand and the absolute value of the difference between the remaining capacity and the demand is greater than a first preset value, the candidate supplier with the first mark is retained in the matching result; otherwise, the candidate supplier with the first mark is eliminated from the matching result to perform risk processing on the matching result.

[0104] In step S650, the candidate suppliers remaining in the matching results after the risk processing are determined as recommended suppliers for the target raw material for the process.

[0105] For example, for the demand information of any process, if there is a candidate supplier with a first mark in the final matching result of the demand information, it is necessary to measure whether the production capacity of the candidate supplier can meet the needs of multiple processes at the same time. When the production capacity of the candidate supplier with the first mark can no longer meet the demand of the current process, the candidate supplier is either eliminated from the final matching result or retained, so as to perform risk processing on the matching result, and determine the candidate supplier included in the matching result after risk processing as the recommended supplier of the target raw material for the process.

[0106] Through the above-mentioned steps S610 to S650, when the needs of different processes for the same target raw material are met, suppliers can be recommended for different processes based on the suppliers' production capacity, thereby avoiding the untimely supply of the target raw materials and improving the accuracy of supplier recommendations.

[0107] In step S250, a recommended supplier of the target raw material is recommended to the process unit of each process.

[0108] For example, the process unit of each process can log in to its own account through the client, and then enter its own demand information for any target raw material in the client, and recommend the recommended supplier of the target raw material for the process unit through the method disclosed in the present invention. After obtaining the recommended supplier of each process, the recommended supplier of the target raw material can be recommended to the client of each process unit. Alternatively, the process unit identifier and the process demand information for the target raw material can be entered in one client, and then the recommended supplier of the target raw material for each process unit can be output simultaneously in one client.

[0109] In the supplier recommendation method for offshore photovoltaic construction projects disclosed in the present invention, the allocation management of suppliers can be carried out according to the characteristics of offshore photovoltaic construction projects, the accuracy of supplier recommendation can be improved, and the timeliness of raw material supply can be ensured. At the same time, different suppliers are recommended for different process units, and different suppliers can provide corresponding raw materials at the corresponding construction stage. Different suppliers also have different information such as packaging of the same raw material, which can avoid mutual interference between different processes during construction, so as to improve construction efficiency.

[0110] In addition, it should be noted that the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0111] Furthermore, the exemplary embodiment of the present disclosure also provides a supplier recommendation device 700 applied to an offshore photovoltaic construction project, wherein different processes of the offshore photovoltaic construction project have different demand information for the same target raw material. Figure 7As shown, the supplier recommendation device applied to the offshore photovoltaic construction project includes the following program modules: a location information acquisition module 710, configured to obtain the first location information corresponding to the production address of the candidate manufacturer of the target raw material and the second location information corresponding to the construction address of the offshore photovoltaic construction project; a candidate supplier determination module 720, configured to determine the distance between the production address and the construction address according to the first location information and the second location information, and determine the candidate supplier of the target raw material from the candidate manufacturers based on the distance; a classification module 730, configured to classify the candidate suppliers based on each evaluation index of the target raw material, and obtain the classified results of the candidate suppliers corresponding to each evaluation index; a matching module 740, configured to obtain the demand information of the target raw material for different processes of the offshore photovoltaic construction project, perform at least one level of matching between the demand information and the classified results, and determine the recommended supplier of the target raw material for each process according to the matching results, wherein each process corresponds to a process unit, and the process units of each process are different; a recommendation module 750, configured to recommend the recommended supplier of the target raw material to the process units of each process respectively.

[0112] Optionally, the evaluation indicators include a production capacity indicator, a price indicator, and a quality indicator, and the candidate suppliers are classified based on each evaluation indicator of the target raw material to obtain a classified result corresponding to each evaluation indicator, including: classifying the candidate suppliers according to their production capacity for the target raw materials to obtain a production capacity classification table; classifying the candidate suppliers according to the prices of the target raw materials provided by the candidate suppliers to obtain a price classification table; classifying the candidate suppliers according to the quality of the target raw materials provided by the candidate suppliers to obtain a quality classification table.

[0113] Optionally, the production capacity of the target raw material by the candidate supplier is determined in the following manner: obtaining the production information of the candidate supplier, the production information including the length of time that each production equipment has been in use, the number of equipment failures, the time of equipment failure, the equipment yield, the equipment output, the number of laborers, the working years of each laborer, and the historical working hours of each laborer in the same period of the supply cycle of the target raw materials of the offshore photovoltaic project; predicting the equipment status of the equipment in the supply cycle of the target raw materials of the offshore photovoltaic construction project based on the length of time that the equipment has been in use, the number of equipment failures and the time of equipment failure, the equipment status including the usage status and the failure status; for each equipment, predicting the equipment status based on the equipment status The equipment capacity of the target raw materials for the offshore photovoltaic construction project is determined based on the equipment status, the equipment yield rate and the equipment output; the predicted working hours of the labor force within the supply cycle of the target raw materials are predicted based on the historical working hours of each labor force in the historical period of the supply cycle of the target raw materials; the labor capacity within the supply cycle of the target raw materials for the offshore photovoltaic construction project is predicted based on the working years of each labor force, the number of laborers and the predicted working hours; the capacity of the candidate supplier for the target raw materials within the supply cycle of the target raw materials for the offshore photovoltaic construction project is determined based on the equipment capacity and the labor capacity.

[0114] Optionally, the demand information includes any one of demand quantity, budget price, and quality standard, and the acquiring of demand information of the target raw materials for different processes of the offshore photovoltaic construction project, matching the demand information with the classified results at least one level, and determining the recommended supplier of the target raw materials for each process according to the matching result includes: for any process, when the demand information is the demand quantity, matching the demand information with the capacity in the capacity classification table, so as to determine the candidate supplier in the capacity classification table whose capacity is greater than or equal to the demand quantity indicated by the demand information as the recommended supplier of the target raw materials for the process; for any process, in the case where the demand information is the demand quantity, When the demand information is the budget price, the demand information is matched with the price in the price classification table to determine the candidate supplier in the price classification table whose price is less than or equal to the budget price indicated by the demand information as the recommended supplier of the target raw material for the process; for any process, when the demand information is the quality standard, the first quality level to which the quality standard in the demand information belongs is determined, and the first quality level is matched with the quality level in the quality classification table to determine the candidate supplier corresponding to the second quality level in the quality classification table whose quality level is higher than or equal to the first quality level as the recommended supplier of the target raw material.

[0115] Optionally, the demand information includes at least two of demand quantity, budget price, and quality standard. The demand information of different processes of the offshore photovoltaic construction project for the target raw materials is obtained, the demand information is matched with the classified results at least once, and the recommended supplier of the target raw materials for each process is determined according to the matching results. The method includes: for each process, obtaining the demand information of the process for the target raw materials and the demand priority of the demand information; for the highest priority, the demand value indicated by the highest priority demand information is matched with the classified results corresponding to the demand information at the first level to obtain the matching result of the highest priority; for other priorities, according to the priority order, the first category of candidate suppliers in the previous level matching results corresponding to the previous level priority of the priority is searched in the classified results corresponding to the demand information indicated by the current priority, the first category is matched with the demand information indicated by the current priority, and the matching result of the current priority is determined according to the candidate suppliers in the previous level matching results that successfully matched the first category, and the process is repeated until the current priority is the last priority, and the recommended supplier of the target raw materials for the process is obtained according to the matching result of the last priority.

[0116] Optionally, the device also includes a first prompt module, which can be configured to: when the first category found does not match the demand information indicated by the current priority, determine the candidate supplier included in the previous level matching result as the recommended supplier for the process, and generate a first prompt information, wherein the first prompt information is used to prompt the priorities met and not met by the current recommended supplier.

[0117] Optionally, determining the recommended supplier of the target raw material for each process according to the matching results includes: when there is a candidate supplier with a first mark added in the matching results, obtaining the demand of the process, the production capacity of the candidate supplier with the first mark added, and the supply indicated by the first mark; determining the remaining capacity of the candidate supplier with the first mark added according to the production capacity and the supply; when the remaining capacity is greater than the demand and the absolute value of the difference between the remaining capacity and the demand is greater than a first preset value, retaining the candidate supplier with the first mark added in the matching results, otherwise, eliminating the candidate supplier with the first mark added in the matching results, so as to perform risk processing on the matching results; determining the remaining candidate suppliers in the matching results after the risk processing as the recommended suppliers for the target raw material for the process; wherein the method of adding the first mark includes: in response to a selection operation of any process unit on the recommended supplier, determining the recommended supplier indicated by the selection operation as the target supplier of the process unit for the target raw material, and adding a first mark to the target supplier, wherein the first mark is used to indicate the process units supplied by the target supplier and the supply provided to the process unit.

[0118] The specific details of each part of the above-mentioned device have been described in detail in the implementation method of the method part. The undisclosed details can be found in the implementation method of the method part, so they will not be repeated here.

[0119] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the exemplary embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0120] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0121] The exemplary embodiments of the present disclosure also provide a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the supplier recommendation method applied to an offshore photovoltaic construction project is implemented.

[0122] In one embodiment, the computer program product may be a tangible product containing a computer program, such as a computer-readable storage medium storing a computer program. The readable storage medium may be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), mechanical hard disk (HDD), solid state drive (SSD), and the like. Exemplarily, the computer program product may be implemented as a non-volatile storage medium storing a computer program, such as a read-only memory, a NAND flash memory (Nand Flash), and the like.

[0123] In one embodiment, the computer program product may be an intangible product including a computer program. Exemplarily, the computer program product may be implemented as a virtual digital product, such as a digital file storing an executable file, an installation package, etc. of the computer program.

[0124] The code of the computer program can be written in one or more programming languages. Programming languages ​​such as C language, Java, C++, Python, etc. The program code can be executed completely on the user computing device, or partially on the user computing device, or as a separate software package, or partially on the user computing device and partially on the remote computing device, or completely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (for example, through an Internet connection provided by an operator).

[0125] Computer programs can be carried or transmitted through electrical, magnetic, optical, electromagnetic, infrared, etc. Electronic devices can convert signals carrying computer programs into digital signals and then run the computer programs. When the computer program is executed on an electronic device, its code is used to enable the electronic device to execute (more specifically, enable the processor of the electronic device to execute) the method steps of various exemplary embodiments of the present disclosure, such as the above-mentioned supplier recommendation method applied to an offshore photovoltaic construction project, where different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the method includes the following steps: obtaining first location information corresponding to the production address of a candidate manufacturer of the target raw material and second location information corresponding to the construction address of the offshore photovoltaic construction project; determining the distance between the production address and the construction address according to the first location information and the second location information, and determining the candidate supplier of the target raw material from the candidate manufacturers based on the distance; classifying the candidate suppliers based on each evaluation index of the target raw material to obtain the classified results of the candidate suppliers corresponding to each evaluation index; obtaining the demand information of different processes of the offshore photovoltaic construction project for the target raw material, matching the demand information with the classified results at least once, and determining the recommended supplier of the target raw material for each process according to the matching results, wherein each process corresponds to a process unit, and the process units of each process are different; and recommending the recommended supplier of the target raw material to the process unit of each process respectively.

[0126] By executing the above method steps through a computer program, for the same target raw material, suppliers that meet the needs of the process units corresponding to different processes of the offshore photovoltaic project can be accurately recommended, thereby helping to improve the construction efficiency of the offshore photovoltaic project, avoiding the situation where the construction progress of the offshore photovoltaic project is affected due to incorrect supplier selection, and reducing the potential risks of the offshore photovoltaic construction project.

[0127] The exemplary embodiments of the present disclosure also provide an electronic device, such as the terminal device 110 or the server 120 described above. The electronic device may include a processor and a memory. The memory stores executable instructions of the processor, such as a computer program. The processor executes the method steps of various exemplary embodiments of the present disclosure by executing the executable instructions. In addition, the electronic device may also include a display for displaying a graphical user interface.

[0128] Reference below Figure 8 , the electronic device is exemplarily described in the form of a general-purpose computing device. It should be understood that Figure 8 The electronic device 800 shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0129] like Figure 8 As shown, the electronic device 800 may include a processor 810 , a memory 820 , a bus 830 , an I / O (input / output) interface 840 , a network adapter 850 , and a display 860 .

[0130] The memory 820 may include a volatile memory, such as a RAM 821, a cache unit 822, and may also include a non-volatile memory, such as a ROM 823. The memory 820 may also include one or more program modules 824, such program modules 824 include but are not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or a combination thereof may include the implementation of a network environment. For example, the program module 824 may include each module in the above-mentioned device.

[0131] The processor 810 may include one or more processing units. For example, the processor 810 may include an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor and / or an NPU (Neural-Network Processing Unit), etc.

[0132] The processor 810 can be used to execute executable instructions stored in the memory 820, such as executing the above-mentioned supplier recommendation method applied to offshore photovoltaic construction projects, where different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, which includes the following steps: obtaining first location information corresponding to the production address of a candidate manufacturer of the target raw material and second location information corresponding to the construction address of the offshore photovoltaic construction project; determining the distance between the production address and the construction address based on the first location information and the second location information, and determining candidate suppliers of the target raw material from the candidate manufacturers based on the distance; classifying the candidate suppliers based on each evaluation index of the target raw material to obtain classified results of the candidate suppliers corresponding to each evaluation index; obtaining demand information for the target raw material of different processes of the offshore photovoltaic construction project, matching the demand information with the classified results at least once, and determining the recommended supplier of the target raw material for each process based on the matching results, wherein each process corresponds to a process unit, and the process units of each process are different; and recommending recommended suppliers of the target raw material to the process units of each process respectively.

[0133] By implementing the above method through a computer program, for the same target raw material, suppliers that meet the needs of the process units corresponding to different processes of the offshore photovoltaic project can be accurately recommended, thereby helping to improve the construction efficiency of the offshore photovoltaic project, avoiding the situation where the construction progress of the offshore photovoltaic project is affected due to incorrect supplier selection, and reducing the potential risks of the offshore photovoltaic construction project.

[0134] The bus 830 is used to realize the connection between different components of the electronic device 800, and may include a data bus, an address bus, and a control bus.

[0135] The electronic device 800 can communicate with one or more external devices 900 (eg, a keyboard, a mouse, an external controller, etc.) through the I / O interface 840 .

[0136] The electronic device 800 can communicate with one or more networks through the network adapter 850. For example, the network adapter 850 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, near field communication, etc. The network adapter 850 can communicate with other modules of the electronic device 800 through the bus 830.

[0137] The electronic device 800 may display a graphical user interface, such as a recommendation result interface, through the display 860 .

[0138] although Figure 8 Not shown, other hardware and / or software modules may also be provided in the electronic device 800, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0139] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0140] As can be seen from the above, the technical solution of the present disclosure can be implemented as a method, an apparatus, a system, a computer program product, a storage medium, an electronic device, etc. Those skilled in the art can understand that various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software, such as being respectively referred to as a "circuit", "module" or "system".

[0141] It should be understood that the present disclosure is not limited to the specific method steps or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. Those skilled in the art will easily think of other embodiments based on the specific embodiments provided by the present disclosure. Therefore, the specific embodiments provided by the present disclosure are only exemplary, and the scope and spirit of the present disclosure are indicated by the claims, and any variations, uses or adaptive changes of the present disclosure should be covered, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the technical field that are not disclosed in the present disclosure.

Claims

1. A supplier recommendation method for offshore photovoltaic construction projects, characterized in that: Different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the method includes: Acquire first location information corresponding to a production address of a candidate manufacturer of the target raw material and second location information corresponding to a construction address of the offshore photovoltaic construction project; Determine the distance between the production address and the construction address according to the first location information and the second location information, and determine a candidate supplier of the target raw material from the candidate manufacturers based on the distance; Classifying the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; Obtaining demand information for the target raw materials of different processes of the offshore photovoltaic construction project, performing at least one level of matching between the demand information and the classified results, and determining a recommended supplier for the target raw materials for each process according to the matching results, wherein each process corresponds to a process unit, and the process units of each process are different; Recommending the recommended supplier of the target raw material to the process unit of each process respectively; The evaluation index includes a capacity index, a price index, and a quality index. The classifying of the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result corresponding to each evaluation index includes: classifying the candidate suppliers according to their capacity for the target raw material to obtain a capacity classification table; classifying the candidate suppliers according to the price of the target raw material provided by the candidate suppliers to obtain a price classification table; classifying the candidate suppliers according to the quality of the target raw material provided by the candidate suppliers to obtain a quality classification table; The demand information includes any one of demand quantity, budget price, and quality standard. The acquiring of demand information of the target raw materials for different processes of the offshore photovoltaic construction project, matching the demand information with the classified results at least one level, and determining the recommended supplier of the target raw materials for each process according to the matching results includes: for any process, when the demand information is the demand quantity, matching the demand information with the capacity in the capacity classification table, so as to determine the candidate supplier in the capacity classification table whose capacity is greater than or equal to the demand quantity indicated by the demand information as the recommended supplier of the target raw materials for the process; for any process, when the demand information is the budget price, matching the demand information with the price in the price classification table, so as to determine the candidate supplier in the price classification table whose price is less than or equal to the budget price indicated by the demand information as the recommended supplier of the target raw materials for the process; for any process, when the demand information is the quality standard, determining the first quality level to which the quality standard in the demand information belongs, matching the first quality level with the quality level in the quality classification table, so as to determine the candidate supplier corresponding to the second quality level in the quality classification table whose quality level is higher than or equal to the first quality level as the recommended supplier of the target raw materials.

2. The method according to claim 1, characterized in that The production capacity of the candidate supplier for the target raw material is determined in the following manner: Acquire production information of the candidate supplier, the production information including the equipment usage time, equipment failure times, equipment failure time, equipment yield rate, equipment output, number of laborers, working years of each laborer, and historical working hours of each laborer in the same period of the supply cycle of the target raw materials of the offshore photovoltaic project; According to the length of time the equipment has been in use, the number of equipment failures and the equipment failure time, predict the equipment status of the equipment within the supply cycle of the target raw materials of the offshore photovoltaic construction project, wherein the equipment status includes the use status and the failure status; For each device, according to the device status, the device yield rate and the device output, determine the device capacity of the device for the target raw material within the target raw material supply cycle of the offshore photovoltaic construction project; Predicting the predicted working hours of each labor force in the supply cycle of the target raw materials according to the historical working hours of each labor force in the same historical period of the supply cycle of the target raw materials; Predicting the labor capacity within the supply cycle of the target raw materials for the offshore photovoltaic construction project based on the working years of each laborer, the number of laborers and the predicted working hours; The production capacity of the target raw material of the candidate supplier within the supply cycle of the target raw material of the offshore photovoltaic construction project is determined according to the equipment production capacity and the labor production capacity.

3. The method according to claim 1, characterized in that The demand information includes at least two of demand quantity, budget price, and quality standard. The acquiring of demand information of the target raw materials for different processes of the offshore photovoltaic construction project, performing at least one level matching between the demand information and the classified results, and determining the recommended supplier of the target raw materials for each process according to the matching results includes: For each process, obtaining demand information of the process for the target raw material and demand priority of the demand information; For the highest priority, a first-level matching is performed between the demand value indicated by the demand information of the highest priority and the classified results corresponding to the demand information to obtain the matching result of the highest priority; For other priorities, according to the priority order, the first category of candidate suppliers in the previous level matching results corresponding to the previous level priority of the priority is queried in the classified results corresponding to the demand information indicated by the current priority, and the found first category is matched with the demand information indicated by the current priority. The matching result of the current priority is determined based on the candidate suppliers in the previous level matching results that successfully matched the first category. This process is repeated until the current priority is the last priority. Based on the matching result of the last priority, the recommended supplier of the target raw material for the process is obtained.

4. The method according to claim 3, characterized in that The method further comprises: When the first category found does not match the demand information indicated by the current priority, the candidate suppliers included in the previous level matching results are determined as recommended suppliers for the process, and a first prompt information is generated. The first prompt information is used to prompt the priorities met and not met by the current recommended supplier.

5. The method according to claim 1, characterized in that Determining the recommended supplier of the target raw material for each process according to the matching results includes: When there is a candidate supplier with a first mark in the matching result, obtaining the demand of the process, the production capacity of the candidate supplier with the first mark, and the supply indicated by the first mark; Determine the remaining capacity of the candidate supplier with the first mark added according to the capacity and the supply; In the case where the remaining capacity is greater than the demand and the absolute value of the difference between the remaining capacity and the demand is greater than a first preset value, the candidate supplier with the first mark is retained in the matching result; otherwise, the candidate supplier with the first mark is eliminated from the matching result, so as to perform risk processing on the matching result; Determine the remaining candidate suppliers in the matching results after the risk processing as recommended suppliers for the target raw material for the process; The method of adding the first mark includes: In response to a selection operation of the recommended supplier by any process unit, the recommended supplier indicated by the selection operation is determined as the target supplier of the target raw material for the process unit, and a first mark is added to the target supplier, wherein the first mark is used to indicate the process units supplied by the target supplier and the supply quantity provided to the process unit.

6. A supplier recommendation device applied to offshore photovoltaic construction projects, characterized in that: Different processes of the offshore photovoltaic construction project have different demand information for the same target raw material, and the device includes: A location information acquisition module, configured to acquire first location information corresponding to a production address of a candidate manufacturer of the target raw material and second location information corresponding to a construction address of the offshore photovoltaic construction project; a candidate supplier determination module, configured to determine the distance between the production address and the construction address according to the first location information and the second location information, and determine a candidate supplier of the target raw material from the candidate manufacturers based on the distance; A classification module is configured to classify the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result of the candidate suppliers corresponding to each evaluation index; A matching module is configured to obtain demand information of the target raw materials for different processes of the offshore photovoltaic construction project, perform at least one level of matching between the demand information and the classified results, and determine a recommended supplier of the target raw materials for each process according to the matching results, wherein each process corresponds to a process unit, and the process units of each process are different; A recommendation module, configured to recommend a recommended supplier of the target raw material to the process unit of each process respectively; The evaluation index includes a capacity index, a price index, and a quality index. The classifying of the candidate suppliers based on each evaluation index of the target raw material to obtain a classified result corresponding to each evaluation index includes: classifying the candidate suppliers according to their capacity for the target raw material to obtain a capacity classification table; classifying the candidate suppliers according to the price of the target raw material provided by the candidate suppliers to obtain a price classification table; classifying the candidate suppliers according to the quality of the target raw material provided by the candidate suppliers to obtain a quality classification table; The demand information includes any one of demand quantity, budget price, and quality standard. The acquiring of demand information of the target raw materials for different processes of the offshore photovoltaic construction project, matching the demand information with the classified results at least one level, and determining the recommended supplier of the target raw materials for each process according to the matching results includes: for any process, when the demand information is the demand quantity, matching the demand information with the capacity in the capacity classification table, so as to determine the candidate supplier in the capacity classification table whose capacity is greater than or equal to the demand quantity indicated by the demand information as the recommended supplier of the target raw materials for the process; for any process, when the demand information is the budget price, matching the demand information with the price in the price classification table, so as to determine the candidate supplier in the price classification table whose price is less than or equal to the budget price indicated by the demand information as the recommended supplier of the target raw materials for the process; for any process, when the demand information is the quality standard, determining the first quality level to which the quality standard in the demand information belongs, matching the first quality level with the quality level in the quality classification table, so as to determine the candidate supplier corresponding to the second quality level in the quality classification table whose quality level is higher than or equal to the first quality level as the recommended supplier of the target raw materials.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

8. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the method according to any one of claims 1 to 5.

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