CN114418293A - Artificial intelligence bid evaluation method, system and equipment based on big data analysis - Google Patents
Artificial intelligence bid evaluation method, system and equipment based on big data analysis Download PDFInfo
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Abstract
The invention provides an artificial intelligence bid evaluation method, system and equipment based on big data analysis, which are used for calling bid evaluation data information from a bid inviting file and extracting a bid evaluation model and a bid evaluation rule in the bid evaluation data information; bidding sub-modules in the obtained bidding documents according to the bidding keyword labels; judging whether the bidding sub-modules in the bidding document are matched with the bidding keyword tags in the bidding document; if the bidding documents are matched with the bidding documents, starting a scoring program to score the bidding sub-modules in the bidding documents; and outputting the total score of the bid evaluation. Automatic scoring and bid evaluation are realized, and comprehensive calculation scoring is performed in combination with expert scoring. In order to ensure the scoring accuracy, a large amount of repeated examination of each score is required, a large amount of scoring time is consumed, the manual intervention degree is large, each expert has different understanding on a certain project, and if some projects cannot be scored uniformly, the scoring of each expert lacks the standard, and the objectivity of scoring work is influenced.
Description
Technical Field
The invention relates to the technical field of bidding, in particular to an artificial intelligence bid evaluation method, system and device based on big data analysis.
Background
The bidding mode is applied to a plurality of industries at present, and can relate to purchasing bidding, construction bidding and the like. Each bidding requires a bidding announcement to be issued first, and the bidding company creates a bidding document based on the bidding document and makes a bid for a predetermined time. And then opening bid, singing bid and evaluating bid, and finally advertising winning bid enterprises.
In the bid evaluation process, an expert group is generally allocated first, and each bid document is evaluated by an expert, if the bid amount is large, the expert can evaluate the bid by individuals, so that more time is consumed, and the objectivity of bid evaluation work cannot be ensured.
In the process of grading, the expert needs to calculate a large number of grading items of the bid documents, and then carries out weighting according to the grading to calculate the result of each bid document. In order to ensure the scoring accuracy, a large amount of repeated examination of each score is required, a large amount of scoring time is consumed, the manual intervention degree is large, each expert has different understanding on a certain project, and if some projects cannot be scored uniformly, the scoring of each expert lacks the standard, and the objectivity of scoring work is influenced.
Disclosure of Invention
The invention provides an artificial intelligence bid evaluation method based on big data analysis.
The artificial intelligence bid evaluation method comprises the following steps:
s101, calling bid evaluation data information from the bid inviting file, and extracting bid evaluation models and bid evaluation rules in the bid evaluation data information;
s102, obtaining a bidding submodule in a bidding document according to the bidding keyword label;
s103, judging whether the bidding sub-module in the bidding document is matched with the bidding keyword tag in the bidding document;
if the bidding documents are matched with the bidding documents, starting a scoring program to score the bidding sub-modules in the bidding documents;
and outputting the total score of the bid evaluation.
Preferably, a bidding keyword tag is set in the bidding document; the bid keyword tag is a rule that is set based on a bid condition required by the bidder in the bid document.
Preferably, if the bidding submodule in the bidding document fails to match the bidding keyword tag in the bidding document, the bidding document is determined to be bid-spoiling if the bidding keyword tag in the bidding document is absent from the bidding document.
Preferably, a plurality of bid evaluation sub-modules are arranged in the bid evaluation data information, and a bid evaluation identifier is arranged for each bid evaluation sub-module; and the bid evaluation mark is set according to the bid inviting keyword label.
Preferably, a bid evaluation weight coefficient is set for each bid evaluation sub-module, the bid evaluation weight coefficient is combined with the bid evaluation sub-modules to obtain the current bid evaluation item score, and the bid evaluation item scores are summed to obtain the bid evaluation score of the bid document.
Preferably, by
Calculating a bid evaluation weight coefficient of each bid evaluation submodule;
p is the importance of the evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag related in the evaluation sub-module.
Preferably, each bid evaluation expert is configured with a bid evaluation terminal;
obtaining the grade of each bidding submodule by the bid evaluation expert through the bid evaluation terminal;
and calculating based on the evaluation weighting coefficient of the evaluation submodule and the score of the bidding submodule to obtain the score of each expert, and then carrying out weighted average scoring on all the evaluations to obtain the score of each bidding document.
Preferably, the score of each bid document is calculated as follows;
DN＝(XA1,XA2,XA3,XA4,XA5)
a1, A2, A3, A4 and A5 respectively represent different bidding submodules;
d1, D2, D3, DN each represent the score of each expert.
The invention also provides an artificial intelligence bid evaluation system based on big data analysis, which comprises: the system comprises a bidding document acquisition module, an identification setting module, a bidding matching scoring module, an output module and a database;
the bidding document acquisition module is used for acquiring bidding documents according to a preset format and storing the acquired bidding documents into a database;
the identification setting module is used for setting a bidding keyword label in a bidding document, setting a bidding sub-module in the bidding document, setting a plurality of bid evaluation sub-modules in the bid evaluation data information, and setting a bid evaluation identification for each bid evaluation sub-module;
the bid matching scoring module is used for judging whether a bid submodule in the bid file is matched with a bid calling keyword label in the bid file; if the bidding documents are matched with the bidding documents, starting a scoring program to score the bidding sub-modules in the bidding documents;
the output module is used for outputting the total score of the bid evaluation.
The invention also provides equipment for realizing the artificial intelligence bid evaluation method based on big data analysis, which comprises the following steps:
the storage is used for storing a computer program and an artificial intelligence evaluation method based on big data analysis;
and the processor is used for executing the computer program and the artificial intelligence bid evaluation method based on the big data analysis so as to realize the steps of the artificial intelligence bid evaluation method based on the big data analysis.
According to the technical scheme, the invention has the following advantages:
the artificial intelligence bid evaluation method and the system based on big data analysis provided by the invention realize automatic scoring and bid evaluation, and carry out comprehensive calculation scoring by combining expert scoring.
The invention can screen the bids, carry out matching judgment on the bid documents which do not meet the bidding requirement, reject the bid documents which do not meet the requirement and then carry out subsequent bid evaluation.
In the bid evaluation process, the system can realize the automatic bid evaluation and scoring process, and can avoid the problems of missed bid evaluation and wrong bid evaluation in manual scoring.
Therefore, the bid evaluation work can be simplified, and the bid evaluation efficiency and accuracy are improved. The bid evaluation method and the bid evaluation system avoid the situation that a large amount of repeated checking of each score consumes a large amount of bid evaluation time, and can improve the bid evaluation efficiency and the bid evaluation accuracy.
The artificial intelligence bid evaluation method and the system based on big data analysis provided by the invention reduce the large degree of manual intervention, can carry out scoring according to a unified model, realize unified scoring detailed rules, and reduce the problem that the scoring of each expert lacks the standard and influences the objectivity of bid evaluation work.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings used in the description will be briefly introduced, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of an artificial intelligence bid evaluation method based on big data analysis;
FIG. 2 is a schematic diagram of an artificial intelligence bid evaluation system based on big data analysis.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides an artificial intelligence bid evaluation method based on big data analysis, which comprises the following steps of:
s101, calling bid evaluation data information from the bid inviting file, and extracting bid evaluation models and bid evaluation rules in the bid evaluation data information;
in the present invention, the bidding document may include, but is not limited to, electric power material purchasing bidding or electric power construction project bidding. The bidding document has the contents of bidding requirements, qualification requirements for bidders, capital requirements, qualification requirements for bidders and the like, and the bidding document is the bidding requirements displayed for the bidders, so that the bidders can know the contents required to be prepared for bidding, and bid evaluation models and bid evaluation rules.
Setting a bidding keyword label in a bidding document; the bid keyword tag is a rule that is set based on a bid condition required by the bidder in the bid document. For example, bidding keywords may include, but are not limited to, bid price, technical capability, research and development capability, corporate financial information, corporate reputation, corporate performance, after-market services, and the like.
The bidding price, technical capability, research and development capability, enterprise financial information, enterprise reputation, enterprise performance, after-sales service and other aspects in the bidding document can be respectively set with bidding keyword labels and highlighted.
And setting a plurality of bid evaluation sub-modules in the bid evaluation data information, and setting bid evaluation identifications for each bid evaluation sub-module. And the bid evaluation mark is set according to the bid inviting keyword label.
And setting a bid evaluation weight coefficient for each bid evaluation submodule, combining the bid evaluation weight coefficient with the bid evaluation submodule to obtain the current bid evaluation item score, and summing the bid evaluation item scores to obtain the bid evaluation score of the bid document.
In the invention, each bid evaluation item can correspond to at least one bid inviting item information, and the bid inviting item information is provided with a corresponding score.
S102, obtaining a bidding submodule in a bidding document according to the bidding keyword label;
s103, judging whether the bidding sub-module in the bidding document is matched with the bidding keyword tag in the bidding document;
s104, if the bidding documents are matched with the bidding documents, starting a grading program, and grading the bidding sub-modules in the bidding documents;
and S105, outputting the total score of the evaluation targets.
And if the bidding submodule in the bidding document is not matched with the bidding keyword label in the bidding document, judging that the bidding document is wasted if the bidding submodule lacks the bidding keyword label in the bidding document.
In the invention, a preset number of bidding keyword labels are set in the bidding document according to the bidding requirement, and the bidding keyword labels represent the requirement of the bidding party on the bidding enterprise. The bidding enterprises are required to meet the corresponding requirements. For example, the bidding enterprise is required to meet the requirements of bidding price, technical capability, research and development capability, enterprise financial information, enterprise reputation, enterprise performance, after-sales service and the like. The bidder is required to explain the items described above when making a bid.
The invention sets the requirements as bidding keyword tags, namely, how many bidding keyword tags are required to be set. When making a bid document, a bidder needs to fill in a corresponding project according to the requirements of the bidder, for example, the bidder sets requirements on bid price, technical capability, research and development capability, enterprise financial information, enterprise reputation, enterprise performance, after-sales service and the like. Then the bidder is required to provide business information and bid information in a one-to-one correspondence to the above requirements and form a bidding submodule.
The invention can match the bidding sub-module with the bidding keyword tag in the bidding document. And if the bidding sub-module is completely matched with the bidding keyword tags in the bidding document, the fact that all the bidders correspond to the requirements of the bidding document is shown.
If the bidding sub-module does not completely cover the bidding keyword label of the bidding document, the fact that the bidding document has a defect is indicated, and the system judges the bidding document to be the bid disuse.
Further, in the bid evaluation method according to the present invention, first, the bid evaluation method is performed
By passing
Calculating a bid evaluation weight coefficient of each bid evaluation submodule;
p is the importance of the evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag related in the evaluation sub-module.
Such as the technical capabilities of the enterprise as bidding keyword tags. Specifically, the sub-items include production capacity, development capacity, test capacity, equipment status, and the like.
Also, the corporate financial information may specifically relate to the corporate asset information, liability information, profit information, and the like.
In the invention, an evaluation terminal is configured for each evaluation expert;
obtaining the grade of each bidding submodule by the bid evaluation expert through the bid evaluation terminal;
and calculating based on the evaluation weighting coefficient of the evaluation submodule and the score of the bidding submodule to obtain the score of each expert, and then carrying out weighted average scoring on all the evaluations to obtain the score of each bidding document.
Calculating a score for each bid document by;
DN＝(XA1,XA2,XA3,XA4,XA5)
a1, A2, A3, A4 and A5 respectively represent different bidding submodules;
d1, D2, D3, DN each represent the score of each expert.
Based on the method, the invention also provides an artificial intelligence bid evaluation system based on big data analysis, as shown in fig. 2, comprising: the system comprises a bidding document acquisition module, an identification setting module, a bidding matching scoring module, an output module and a database;
the bidding document acquisition module is used for acquiring bidding documents according to a preset format and storing the acquired bidding documents into a database;
the identification setting module is used for setting a bidding keyword label in a bidding document, setting a bidding sub-module in the bidding document, setting a plurality of bid evaluation sub-modules in the bid evaluation data information, and setting a bid evaluation identification for each bid evaluation sub-module;
the bid matching scoring module is used for judging whether a bid submodule in the bid file is matched with a bid calling keyword label in the bid file; if the bidding documents are matched with the bidding documents, starting a scoring program to score the bidding sub-modules in the bidding documents;
the output module is used for outputting the total score of the bid evaluation.
An apparatus for implementing an artificial intelligence bid evaluation method based on big data analysis comprises: the storage is used for storing a computer program and an artificial intelligence evaluation method based on big data analysis; and the processor is used for executing the computer program and the artificial intelligence bid evaluation method based on the big data analysis so as to realize the steps of the artificial intelligence bid evaluation method based on the big data analysis.
The artificial intelligence bid evaluation method based on big data analysis mainly relates to artificial intelligence computer vision technology and artificial intelligence cloud service in cloud technology, and particularly realizes artificial intelligence processing of bid evaluation process data by utilizing the computer vision technology and the artificial intelligence cloud service, so that accuracy of bid inviting and bidding of artificial intelligence processing can be improved.
Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a manner similar to human intelligence. Artificial intelligence is the research of the design principle and the realization method of various intelligent machines, so that the machines have the functions of perception, reasoning and decision making.
The invention relates to an artificial intelligence technology, which is a comprehensive subject and relates to the field of extensive technology, namely a hardware technology and a software technology. The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like. Computer Vision technology (CV) is a science for researching how to make a machine see, and further means that a camera and a Computer are used for replacing human eyes to perform machine Vision such as identification, tracking and measurement on a target, and further image processing is performed, so that the Computer processing becomes an image more suitable for human eyes to observe or is transmitted to an instrument to detect. As a scientific discipline, computer vision research-related theories and techniques attempt to build artificial intelligence systems that can capture information from images or multidimensional data. Computer vision technologies generally include image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content/behavior recognition, three-dimensional object reconstruction, 3D technologies, virtual reality, augmented reality, synchronous positioning, map construction, and other technologies, and also include common biometric technologies such as face recognition and fingerprint recognition.
The artificial intelligence bid evaluation method based on big data analysis can be used on terminal equipment, the terminal equipment can be equipment for providing artificial intelligence service, and a user can access or use bid inviting and evaluation function service provided by the artificial intelligence platform in an API (application programming interface) interface mode.
The device can also be a basic cloud computing service providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, web services, cloud communication, middleware services, domain name services, security services, Content Delivery Networks (CDNs), big data and artificial intelligence platforms, and the like. The device may be, but is not limited to, a tablet computer, a notebook computer, a desktop computer, and the like.
As will be appreciated by one skilled in the art, aspects of the method, system and apparatus for artificial intelligence bid evaluation based on big data analysis may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. An artificial intelligence bid evaluation method based on big data analysis is characterized by comprising the following steps:
s101, calling bid evaluation data information from the bid inviting file, and extracting bid evaluation models and bid evaluation rules in the bid evaluation data information;
s102, obtaining a bidding submodule in a bidding document according to the bidding keyword label;
s103, judging whether the bidding sub-module in the bidding document is matched with the bidding keyword tag in the bidding document;
s104, if the bidding documents are matched with the bidding documents, starting a grading program, and grading the bidding sub-modules in the bidding documents;
and S105, outputting the total score of the evaluation targets.
2. The artificial intelligence bid evaluation method based on big data analysis according to claim 1,
setting a bidding keyword label in a bidding document; the bid keyword tag is a rule that is set based on a bid condition required by the bidder in the bid document.
3. The artificial intelligence bid evaluation method based on big data analysis according to claim 1,
and if the bidding submodule in the bidding document is not matched with the bidding keyword label in the bidding document, judging that the bidding document is wasted if the bidding submodule lacks the bidding keyword label in the bidding document.
4. The artificial intelligence bid evaluation method based on big data analysis according to claim 1,
setting a plurality of bid evaluation sub-modules in the bid evaluation data information, and setting bid evaluation identifications for each bid evaluation sub-module; and the bid evaluation mark is set according to the bid inviting keyword label.
5. The artificial intelligence bid evaluation method based on big data analysis according to claim 4,
and setting a bid evaluation weight coefficient for each bid evaluation submodule, combining the bid evaluation weight coefficient with the bid evaluation submodule to obtain the current bid evaluation item score, and summing the bid evaluation item scores to obtain the bid evaluation score of the bid document.
6. The artificial intelligence bid evaluation method based on big data analysis according to claim 5,
by passing
Calculating a bid evaluation weight coefficient of each bid evaluation submodule;
p is the importance of the evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag related in the evaluation sub-module.
7. The artificial intelligence bid evaluation method based on big data analysis according to claim 6, wherein a bid evaluation terminal is configured for each bid evaluation expert;
obtaining the grade of each bidding submodule by the bid evaluation expert through the bid evaluation terminal;
and calculating based on the evaluation weighting coefficient of the evaluation submodule and the score of the bidding submodule to obtain the score of each expert, and then carrying out weighted average scoring on all the evaluations to obtain the score of each bidding document.
8. The artificial intelligence bid evaluation method based on big data analysis according to claim 7, wherein the score of each bid document is calculated by;
DN＝(XA1，XA2，XA3，XA4，XA5)
a1, A2, A3, A4 and A5 respectively represent different bidding submodules;
d1, D2, D3, DN each represent the score of each expert.
9. An artificial intelligence bid evaluation system for realizing big data analysis is characterized by comprising: the system comprises a bidding document acquisition module, an identification setting module, a bidding matching scoring module, an output module and a database;
the bidding document acquisition module is used for acquiring bidding documents according to a preset format and storing the acquired bidding documents into a database;
the identification setting module is used for setting a bidding keyword label in a bidding document, setting a bidding sub-module in the bidding document, setting a plurality of bid evaluation sub-modules in the bid evaluation data information, and setting a bid evaluation identification for each bid evaluation sub-module;
the bid matching scoring module is used for judging whether a bid submodule in the bid file is matched with a bid calling keyword label in the bid file; if the bidding documents are matched with the bidding documents, starting a scoring program to score the bidding sub-modules in the bidding documents;
the output module is used for outputting the total score of the bid evaluation.
10. The device for realizing the artificial intelligence bid evaluation method based on big data analysis is characterized by comprising the following steps:
the storage is used for storing a computer program and an artificial intelligence evaluation method based on big data analysis;
a processor for executing the computer program and the artificial intelligence bid evaluation method based on big data analysis to realize the steps of the artificial intelligence bid evaluation method based on big data analysis according to any one of claims 1 to 8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117035674A (en) * | 2023-08-17 | 2023-11-10 | 国义招标股份有限公司 | Intelligent subcontracting management system and method applied to bidding |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117035674A (en) * | 2023-08-17 | 2023-11-10 | 国义招标股份有限公司 | Intelligent subcontracting management system and method applied to bidding |
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