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 PDF

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CN114418293A
CN114418293A CN202111524965.7A CN202111524965A CN114418293A CN 114418293 A CN114418293 A CN 114418293A CN 202111524965 A CN202111524965 A CN 202111524965A CN 114418293 A CN114418293 A CN 114418293A
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bid evaluation
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张流畅
严瑾
敖翔
张迪
张晨
聂灿
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State Grid Chongqing Tendering Co
State Grid Corp of China SGCC
State Grid Chongqing Electric Power Co Ltd
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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

一种基于大数据分析的人工智能评标方法、系统和设备An artificial intelligence bid evaluation method, system and equipment based on big data analysis

技术领域technical field

本发明涉及招投标技术领域,尤其涉及一种基于大数据分析的人工智能评标方法、系统和设备。The invention relates to the technical field of bidding, in particular to an artificial intelligence bid evaluation method, system and equipment based on big data analysis.

背景技术Background technique

目前招投标方式已经应用许多行业,可以涉及采购招投标、施工招投标等等。在每次招投标过中,需要先发招标公告,投标公司基于招标文件来制作投标文件,并按照规定的时间进行投标。再进行开标,唱标以及评标过程,最后公告中标企业。At present, the bidding method has been applied in many industries, which can involve procurement bidding, construction bidding and so on. In each bidding process, the bidding announcement needs to be issued first, and the bidding company prepares the bidding documents based on the bidding documents, and bids according to the specified time. Then open the bid, call the bid and evaluate the bid process, and finally announce the winning company.

在进行评标过程中,一般先分派专家组,由专家对每个投标文件进行评标,如果投标量较大,由专家个人评标,将会耗费时间较多,还不能保证评标工作的客观性。In the process of bid evaluation, an expert group is usually assigned first, and the experts evaluate each bidding document. If the bidding volume is large, it will take a lot of time to evaluate the bids individually, and the bid evaluation work cannot be guaranteed. objectivity.

专家在进行评分过程中,需要大量的计算投标文件的评分项,在根据评分进行加权,核算出每个投标文件的结果。为了保证评分的准确性,存在大量重复检查每项评分,会耗费大量评标时间,而且人工干预程度较大,每个专家对某个项目的理解不一样,如果有些项次未能统一评分细则,导致每个专家评分缺乏标准,影响评标工作的客观性。In the process of scoring, experts need to calculate a large number of scoring items for bidding documents, and then weight according to the scores to calculate the results of each bidding document. In order to ensure the accuracy of the scoring, there are a large number of repeated checks for each score, which will consume a lot of time for bid evaluation, and the degree of manual intervention is large. Each expert has a different understanding of a certain item. If some items fail to unify the scoring rules , resulting in the lack of standards for each expert's score, which affects the objectivity of the bid evaluation work.

发明内容SUMMARY OF THE INVENTION

本发明提供一种基于大数据分析的人工智能评标方法,方法根据预设评分方式并结合专家的评分,进行综合评分评标,满足评标要求。The present invention provides an artificial intelligence bid evaluation method based on big data analysis. The method conducts comprehensive evaluation and evaluation of bids according to a preset scoring method and combined with the evaluation of experts, so as to meet the requirements of bid evaluation.

人工智能评标方法包括:AI bid evaluation methods include:

S101,从招标文件中调取评标数据信息,并提取评标数据信息中的评标模型及评标规则;S101, retrieve bid evaluation data information from the bidding documents, and extract bid evaluation models and bid evaluation rules in the bid evaluation data information;

S102,根据招标关键词标签在获取投标文件中投标子模块;S102, bidding for submodules in obtaining bidding documents according to the bidding keyword tag;

S103,判断投标文件中的投标子模块是否与招标文件中的招标关键词标签相匹配;S103, judging whether the bidding sub-module in the bidding document matches the bidding keyword label in the bidding document;

如匹配则,启动评分程序,对投标文件中的投标子模块进行评分;If there is a match, start the scoring process to score the bidding sub-modules in the bidding documents;

输出评标的总分。Output the total score of the bid evaluation.

优选地,在招标文件中设置招标关键词标签;招标关键词标签是基于招标文件中招标方要求投标条件进行设置的规则。Preferably, a bidding keyword tag is set in the bidding document; the bidding keyword tag is a rule set based on the bidding conditions required by the bidder in the bidding document.

优选地,如投标文件中的投标子模块未能与招标文件中的招标关键词标签相匹配,则投标文件中缺少招标文件中的招标关键词标签,对所述投标文件判定为废标。Preferably, if the bidding sub-module in the bidding document fails to match the bidding keyword tag in the bidding document, the bidding document lacks the bidding keyword tag in the bidding document, and the bidding document is determined to be rejected.

优选地,评标数据信息中,设置多个评标子模块,对每个评标子模块设置评标标识;评标标识根据招标关键词标签设置。Preferably, in the bid evaluation data information, multiple bid evaluation sub-modules are set, and each bid evaluation sub-module is set with a bid evaluation mark; the bid evaluation mark is set according to the bidding keyword tag.

优选地,对每个评标子模块设置评标权重系数,评标权重系数与评标子模块相结合得到当前评标项目评分,对评标项目评分进行加和得到投标文件的评标分数。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-module to obtain the current bid evaluation item score, and the bid evaluation item scores are added to obtain the bid evaluation score of the bidding document.

优选地,通过

Figure BDA0003409902870000021
计算每个评标子模块评标权重系数;Preferably, by
Figure BDA0003409902870000021
Calculate the bid evaluation weight coefficient of each bid evaluation sub-module;

P为评标子模块的重要度,n代表评标子模块中涉及的招标关键词标签中的子项目数量。P is the importance of the bid evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag involved in the bid evaluation sub-module.

优选地,为每个评标专家配置评标终端;Preferably, a bid evaluation terminal is configured for each bid evaluation expert;

获取评标专家通过评标终端对每个投标子模块的评分;Obtain the evaluation expert's score for each bidding sub-module through the evaluation terminal;

基于评标子模块的评标权重系数与投标子模块的评分进行计算得到每个专家的评分,再对所有评价进行加权平均分得到每个投标文件的评分。The evaluation weight coefficient of the bid evaluation sub-module and the score of the bidding sub-module are calculated to obtain the score of each expert, and then the weighted average score of all evaluations is obtained to obtain the score of each bidding document.

优选地,通过如下方式来计算每个投标文件的评分;Preferably, the score for each bid is calculated as follows;

DN=(XA1,XA2,XA3,XA4,XA5)DN=(XA1,XA2,XA3,XA4,XA5)

Figure BDA0003409902870000031
Figure BDA0003409902870000031

A1、A2、A3、A4、A5分别表示不同的投标子模块;A1, A2, A3, A4, and A5 respectively represent different bidding sub-modules;

D1、D2、D3、DN分别表示每个专家的评分。D1, D2, D3, and DN represent the scores of each expert, respectively.

本发明还提供一种实现基于大数据分析的人工智能评标系统,包括:招标投标文件获取模块、标识设置模块、投标匹配评分模块、输出模块以及数据库;The present invention also provides an artificial intelligence bid evaluation system based on big data analysis, comprising: a bidding document acquisition module, an identification setting module, a bid matching scoring module, an output module and a database;

招标投标文件获取模块用于按照预设的格式获取招标投标文件,并将获取的招标投标文件储存至数据库中;The bidding document obtaining module is used to obtain the bidding document according to the preset format, and store the obtained bidding document in the database;

标识设置模块用于在招标文件中设置招标关键词标签,在投标文件中设置投标子模块,在评标数据信息中,设置多个评标子模块,对每个评标子模块设置评标标识;The identification setting module is used to set the bidding keyword label in the bidding document, set the bidding sub-module in the bidding document, set multiple bid evaluation sub-modules in the bid evaluation data information, and set the bid evaluation mark for each bid evaluation sub-module ;

投标匹配评分模块用于判断投标文件中的投标子模块是否与招标文件中的招标关键词标签相匹配;如匹配则,启动评分程序,对投标文件中的投标子模块进行评分;The bidding matching scoring module is used to judge whether the bidding sub-module in the bidding document matches the bidding keyword tag in the bidding document; if it matches, start the scoring procedure to score the bidding sub-module in the bidding document;

输出模块用于输出评标的总分。The output module is used to output the total score of the bid evaluation.

本发明还提供一种实现基于大数据分析的人工智能评标方法的设备,包括:The present invention also provides a device for implementing an artificial intelligence bid evaluation method based on big data analysis, including:

存储器,用于存储计算机程序及基于大数据分析的人工智能评标方法;Memory for storing computer programs and artificial intelligence bid evaluation methods based on big data analysis;

处理器,用于执行所述计算机程序及基于大数据分析的人工智能评标方法,以实现基于大数据分析的人工智能评标方法的步骤。A processor for executing the computer program and the artificial intelligence bid evaluation method based on big data analysis, so as to realize the steps of the artificial intelligence bid evaluation method based on big data analysis.

从以上技术方案可以看出,本发明具有以下优点:As can be seen from the above technical solutions, the present invention has the following advantages:

本发明提供的基于大数据分析的人工智能评标方法和系统实现了自动评分和评标,并结合专家评分来进行综合计算评分。The artificial intelligence bid evaluation method and system based on big data analysis provided by the present invention realizes automatic scoring and bid evaluation, and performs comprehensive calculation and scoring in combination with expert scoring.

本发明可以先对投标进行筛选,对于不满足要求招标要求的投标文件进行匹配判断,不满足要求的先进行剔除,再进行后续的评标。The present invention can screen the bids first, make matching judgment for the bid documents that do not meet the required bidding requirements, and eliminate those that do not meet the requirements, and then carry out subsequent bid evaluation.

在评标过程中,系统可以实现自动计算评标评分过程,够避免人工计算评分出现漏评和错评的问题。During the bid evaluation process, the system can automatically calculate the bid evaluation score process, which can avoid the problem of missed evaluation and wrong evaluation in the manual calculation score.

从而能够简化评标工作,提高评标的效率和准确率。避免了存在大量重复检查每项评分,会耗费大量评标时间,本发明可以提高评标效率,提高评标的准确率。Therefore, the bid evaluation work can be simplified, and the efficiency and accuracy of the bid evaluation can be improved. It avoids a large number of repeated inspections of each score, which consumes a lot of bid evaluation time, and the present invention can improve the efficiency of bid evaluation and the accuracy of bid evaluation.

本发明提供的基于大数据分析的人工智能评标方法和系统降低了人工干预程度较大,可以根据统一的模型来进行评分,实现统一评分细则,减少每个专家评分缺乏标准,影响评标工作客观性的问题。The artificial intelligence bid evaluation method and system based on big data analysis provided by the present invention reduces the degree of manual intervention to a large extent, can be scored according to a unified model, realizes unified scoring rules, reduces the lack of standards for each expert's scoring, and affects bid evaluation work question of objectivity.

附图说明Description of drawings

为了更清楚地说明本发明的技术方案,下面将对描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。In order to illustrate the technical solutions of the present invention more clearly, the accompanying drawings required in the description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, which are not relevant to ordinary skills in the art. As far as personnel are concerned, other drawings can also be obtained from these drawings on the premise of no creative work.

图1为基于大数据分析的人工智能评标方法流程图;Figure 1 is a flowchart of an artificial intelligence bid evaluation method based on big data analysis;

图2为基于大数据分析的人工智能评标系统示意图。Figure 2 is a schematic diagram of an artificial intelligence bid evaluation system based on big data analysis.

具体实施方式Detailed ways

下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

本发明提供的一种基于大数据分析的人工智能评标方法,如图1所示,方法包括:A kind of artificial intelligence bid evaluation method based on big data analysis provided by the present invention, as shown in Figure 1, the method includes:

S101,从招标文件中调取评标数据信息,并提取评标数据信息中的评标模型及评标规则;S101, retrieve bid evaluation data information from the bidding documents, and extract bid evaluation models and bid evaluation rules in the bid evaluation data information;

本发明中,招标文件中可以包括但不限于电力物资采购招标、或电力施工项目招标项目。在招标文件中具有招标要求,对投标人的资格要求,资金要求,投标人资质要求等内容,招标文件是给投标人展示的招标要求,让投标人了解投标需要准备的内容以及评标模型及评标规则。In the present invention, the bidding documents may include, but are not limited to, power material procurement bidding, or power construction project bidding items. In the bidding documents, there are bidding requirements, qualification requirements for bidders, capital requirements, and qualification requirements for bidders. Bid evaluation rules.

在招标文件中设置招标关键词标签;招标关键词标签是基于招标文件中招标方要求投标条件进行设置的规则。比如招标关键词可以包括但不限于投标价格、技术能力、研发能力,企业财务信息、企业信誉、企业业绩、售后服务等方面。The bidding keyword tag is set in the bidding document; the bidding keyword tag is a rule set based on the bidding conditions required by the bidder in the bidding document. For example, bidding keywords may include, but are not limited to, bidding price, technical capability, R&D capability, corporate financial information, corporate reputation, corporate performance, and after-sales service.

可以对招标文件中投标价格、技术能力、研发能力,企业财务信息、企业信誉、企业业绩、售后服务等方面分别设置招标关键词标签,并进行突出显示。Bidding keyword tags can be set and highlighted in the bidding documents in terms of bid price, technical capability, R&D capability, corporate financial information, corporate reputation, corporate performance, and after-sales service.

评标数据信息中,设置多个评标子模块,对每个评标子模块设置评标标识。评标标识根据招标关键词标签设置。In the bid evaluation data information, multiple bid evaluation sub-modules are set, and a bid evaluation mark is set for each bid evaluation sub-module. The bid evaluation logo is set according to the bidding keyword label.

对每个评标子模块设置评标权重系数,评标权重系数与评标子模块相结合得到当前评标项目评分,对评标项目评分进行加和得到投标文件的评标分数。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-module to obtain the current bid evaluation item score, and the bid evaluation item scores are added to obtain the bid evaluation score of the bidding document.

本发明中,每个评标项目可以对应至少一种招标项目信息,招标项目信息设置有对应的分值。In the present invention, each bid evaluation item may correspond to at least one kind of bidding item information, and the bidding item information is set with a corresponding score.

S102,根据招标关键词标签在获取投标文件中投标子模块;S102, bidding for submodules in obtaining bidding documents according to the bidding keyword tag;

S103,判断投标文件中的投标子模块是否与招标文件中的招标关键词标签相匹配;S103, judging whether the bidding sub-module in the bidding document matches the bidding keyword label in the bidding document;

S104,如匹配则,启动评分程序,对投标文件中的投标子模块进行评分;S104, if there is a match, start the scoring program to score the bidding sub-modules in the bidding document;

S105,输出评标的总分。S105, output the total score of the bid evaluation.

如投标文件中的投标子模块未能与招标文件中的招标关键词标签相匹配,则投标文件中缺少招标文件中的招标关键词标签,对所述投标文件判定为废标。If the bidding sub-module in the bidding document fails to match the bidding keyword tag in the bidding document, the bidding document lacks the bidding keyword tag in the bidding document, and the bidding document is determined to be rejected.

本发明中,根据招标要求在招标文件中设置预设数量的招标关键词标签,招标关键词标签表示招标方对投标企业的要求。需要投标企业满足相应的要求。比如需要投标企业满足投标价格、技术能力、研发能力,企业财务信息、企业信誉、企业业绩、售后服务等方面要求。那么需要投标方在进行投标时,对上述各个项目进行说明。In the present invention, a preset number of bidding keyword tags are set in the bidding document according to the bidding requirements, and the bidding keyword tags represent the requirements of the tenderer for the bidding enterprise. The bidders need to meet the corresponding requirements. For example, the bidding enterprise needs to meet the requirements of bidding price, technical ability, research and development ability, enterprise financial information, enterprise reputation, enterprise performance, and after-sales service. Then the bidder needs to explain each of the above items when bidding.

本发明是将上述要求设置成招标关键词标签,也就是有多少项要求设置多少个招标关键词标签。投标方在制作投标文件时,需要根据招标方的要求,填写相应的项目,比如招标方设置了对投标价格、技术能力、研发能力,企业财务信息、企业信誉、企业业绩、售后服务等方面要求。那么就需要投标方对上述要求提供一一对应的企业信息和投标信息,并形成投标子模块。In the present invention, the above requirements are set as bidding keyword tags, that is, how many bidding keyword tags are set for how many items are required. When making bidding documents, the bidder needs to fill in the corresponding items according to the requirements of the bidder. For example, the bidder has set requirements for bidding price, technical ability, research and development ability, corporate financial information, corporate reputation, corporate performance, after-sales service, etc. . Then, the bidder needs to provide one-to-one corresponding enterprise information and bidding information to the above requirements, and form a bidding sub-module.

本发明可以将投标子模块与招标文件中的招标关键词标签进行匹配。如果投标子模块与招标文件中的招标关键词标签完全匹配,则表示投标方全部相应了招标文件的要求。The present invention can match the bidding sub-module with the bidding keyword tag in the bidding document. If the bidding sub-module completely matches the bidding keyword label in the bidding documents, it means that the bidders all correspond to the requirements of the bidding documents.

如果投标子模块未全部涵盖招标文件的招标关键词标签,则说明投标文件中具有缺失,系统将该投标文件判定为废标。If the bidding sub-module does not fully cover the bidding keyword tags of the bidding document, it means that there is a missing bid in the bidding document, and the system judges the bidding document as an invalid bid.

进一步的讲,本发明涉及的评标方式中,先Further, in the bid evaluation method involved in the present invention, first

通过

Figure BDA0003409902870000071
计算每个评标子模块评标权重系数;pass
Figure BDA0003409902870000071
Calculate the bid evaluation weight coefficient of each bid evaluation sub-module;

P为评标子模块的重要度,n代表评标子模块中涉及的招标关键词标签中的子项目数量。P is the importance of the bid evaluation sub-module, and n represents the number of sub-items in the bidding keyword tag involved in the bid evaluation sub-module.

比如企业的技术能力作为招标关键词标签。具体来讲子项目包括生产能力,研发能力,试验能力,设备状态等等。For example, the technical ability of the enterprise can be used as a keyword tag for bidding. Specifically, the sub-items include production capacity, R&D capacity, test capacity, equipment status and so on.

同样企业财务信息具体涉及企业的资产信息,负债信息,利润信息等等。Similarly, corporate financial information specifically involves the company's asset information, liability information, profit information and so on.

本发明中,为每个评标专家配置评标终端;In the present invention, a bid evaluation terminal is configured for each bid evaluation expert;

获取评标专家通过评标终端对每个投标子模块的评分;Obtain the evaluation expert's score for each bidding sub-module through the evaluation terminal;

基于评标子模块的评标权重系数与投标子模块的评分进行计算得到每个专家的评分,再对所有评价进行加权平均分得到每个投标文件的评分。The evaluation weight coefficient of the bid evaluation sub-module and the score of the bidding sub-module are calculated to obtain the score of each expert, and then the weighted average score of all evaluations is obtained to obtain the score of each bidding document.

通过如下方式来计算每个投标文件的评分;The score for each bid is calculated as follows;

DN=(XA1,XA2,XA3,XA4,XA5)DN=(XA1,XA2,XA3,XA4,XA5)

Figure BDA0003409902870000072
Figure BDA0003409902870000072

A1、A2、A3、A4、A5分别表示不同的投标子模块;A1, A2, A3, A4, and A5 respectively represent different bidding sub-modules;

D1、D2、D3、DN分别表示每个专家的评分。D1, D2, D3, and DN represent the scores of each expert, respectively.

基于上述方法本发明还提供一种实现基于大数据分析的人工智能评标系统,如图2所示,包括:招标投标文件获取模块、标识设置模块、投标匹配评分模块、输出模块以及数据库;Based on the above method, the present invention also provides an artificial intelligence bid evaluation system based on big data analysis, as shown in FIG. 2 , including: a bidding document acquisition module, an identification setting module, a bid matching scoring module, an output module and a database;

招标投标文件获取模块用于按照预设的格式获取招标投标文件,并将获取的招标投标文件储存至数据库中;The bidding document obtaining module is used to obtain the bidding document according to the preset format, and store the obtained bidding document in the database;

标识设置模块用于在招标文件中设置招标关键词标签,在投标文件中设置投标子模块,在评标数据信息中,设置多个评标子模块,对每个评标子模块设置评标标识;The identification setting module is used to set the bidding keyword label in the bidding document, set the bidding sub-module in the bidding document, set multiple bid evaluation sub-modules in the bid evaluation data information, and set the bid evaluation mark for each bid evaluation sub-module ;

投标匹配评分模块用于判断投标文件中的投标子模块是否与招标文件中的招标关键词标签相匹配;如匹配则,启动评分程序,对投标文件中的投标子模块进行评分;The bidding matching scoring module is used to judge whether the bidding sub-module in the bidding document matches the bidding keyword tag in the bidding document; if it matches, start the scoring procedure to score the bidding sub-module in the bidding document;

输出模块用于输出评标的总分。The output module is used to output the total score of the bid evaluation.

一种实现基于大数据分析的人工智能评标方法的设备,包括:存储器,用于存储计算机程序及基于大数据分析的人工智能评标方法;处理器,用于执行所述计算机程序及基于大数据分析的人工智能评标方法,以实现基于大数据分析的人工智能评标方法的步骤。A device for implementing an artificial intelligence bid evaluation method based on big data analysis, comprising: a memory for storing a computer program and an artificial intelligence bid evaluation method based on big data analysis; a processor for executing the computer program and a large data analysis-based bid evaluation method; Artificial intelligence bid evaluation method based on data analysis to realize the steps of artificial intelligence bid evaluation method based on big data analysis.

其中,本发明提供的基于大数据分析的人工智能评标方法主要涉及人工智能的计算机视觉技术和云技术中的人工智能云服务,具体的,利用计算机视觉技术和人工智能云服务实现人工智能处理评标过程数据,可提高人工智能处理招投标的准确度。Among them, the artificial intelligence bid evaluation method based on big data analysis provided by the present invention mainly involves artificial intelligence computer vision technology and artificial intelligence cloud service in cloud technology. Specifically, artificial intelligence processing is realized by using computer vision technology and artificial intelligence cloud service. Bid evaluation process data can improve the accuracy of artificial intelligence processing bidding.

其中,人工智能(Artificial Intelligence,AI)是利用数字计算机或者数字计算机控制的机器模拟、延伸和扩展人的智能,感知环境、获取知识并使用知识获得最佳结果的理论、方法、技术及应用系统。换句话说,人工智能是计算机科学的一个综合技术,它企图了解智能的实质,并生产出一种新的能以人类智能相似的方式做出反应的智能机器。人工智能也就是研究各种智能机器的设计原理与实现方法,使机器具有感知、推理与决策的功能。Among them, artificial intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. . In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, reasoning and decision-making.

本发明涉及的人工智能技术是一门综合学科,涉及领域广泛,既有硬件层面的技术也有软件层面的技术。人工智能基础技术一般包括如传感器、专用人工智能芯片、云计算、分布式存储、大数据处理技术、操作/交互系统、机电一体化等技术。人工智能软件技术主要包括计算机视觉技术、语音处理技术、自然语言处理技术以及机器学习/深度学习等几大方向。其中,计算机视觉技术(Computer Vision,CV)计算机视觉是一门研究如何使机器“看”的科学,更进一步的说,就是指用摄影机和电脑代替人眼对目标进行识别、跟踪和测量等机器视觉,并进一步做图形处理,使电脑处理成为更适合人眼观察或传送给仪器检测的图像。作为一个科学学科,计算机视觉研究相关的理论和技术,试图建立能够从图像或者多维数据中获取信息的人工智能系统。计算机视觉技术通常包括图像处理、图像识别、图像语义理解、图像检索、OCR、视频处理、视频语义理解、视频内容/行为识别、三维物体重建、3D技术、虚拟现实、增强现实、同步定位与地图构建等技术,还包括常见的人脸识别、指纹识别等生物特征识别技术。The artificial intelligence technology involved in the present invention is a comprehensive subject, involving a wide range of fields, including both hardware-level technology and software-level technology. The basic technologies of artificial intelligence generally include technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation/interaction systems, and mechatronics. Artificial intelligence software technology mainly includes computer vision technology, speech processing technology, natural language processing technology, and machine learning/deep learning. Among them, computer vision technology (Computer Vision, CV) computer vision is a science that studies how to make machines "see". Further, it refers to the use of cameras and computers instead of human eyes to identify, track and measure objects. Vision, and further do graphics processing, so that computer processing becomes more suitable for human eyes to observe or transmit images to instruments for detection. As a scientific discipline, computer vision studies related theories and technologies, trying to build artificial intelligence systems that can obtain information from images or multidimensional data. Computer vision technology usually includes image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content/behavior recognition, 3D object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping It also includes common biometric identification technologies such as face recognition and fingerprint recognition.

本发明设就得基于大数据分析的人工智能评标方法可以在终端设备上使用,终端设备可以是指用于提供人工智能服务的设备,用户可以通过API接口的方式来接入或使用该人工智能平台提供的招投标以及评标功能服务。In the present invention, the artificial intelligence bid evaluation method based on big data analysis can be used on terminal equipment, and the terminal equipment can refer to the equipment used to provide artificial intelligence services. Bidding and bid evaluation function services provided by the intelligent platform.

设备还可以是提供云服务、云数据库、云计算、云函数、云存储、网络服务、云通信、中间件服务、域名服务、安全服务、内容分发网络(Content Delivery Network,CDN)、以及大数据和人工智能平台等基础云计算服务。设备可以是平板电脑、笔记本电脑、台式计算机等,但并不局限于此。The device may also provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and basic cloud computing services such as artificial intelligence platforms. The device may be a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto.

所属技术领域的技术人员能够理解,基于大数据分析的人工智能评标方法、系统和设备的各个方面可以实现为系统、方法或程序产品。因此,本公开的各个方面可以具体实现为以下形式,即:完全的硬件实施方式、完全的软件实施方式(包括固件、微代码等),或硬件和软件方面结合的实施方式,这里可以统称为“电路”、“模块”或“系统”。Those skilled in the art can understand that various aspects of the artificial intelligence bid evaluation method, system and device based on big data analysis can be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure can be embodied in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, which may be collectively referred to herein as implementations "circuit", "module" or "system".

对所公开的实施例的上述说明,使本领域专业技术人员能够实现或使用本发明。对这些实施例的多种修改对本领域的专业技术人员来说将是显而易见的,本文中所定义的一般原理可以在不脱离本发明的精神或范围的情况下,在其它实施例中实现。因此,本发明将不会被限制于本文所示的这些实施例,而是要符合与本文所公开的原理和新颖特点相一致的最宽的范围。The above description of the disclosed embodiments enables 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 implemented in 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
Figure FDA0003409902860000021
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)
Figure FDA0003409902860000022
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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