CN114168166B

CN114168166B - Installation configuration method and system of indoor intelligent wireless access equipment

Info

Publication number: CN114168166B
Application number: CN202210127799.5A
Authority: CN
Inventors: ***; 洪琴; 郑伟军
Original assignee: Hangzhou Snooker Technology Co ltd
Current assignee: Hangzhou Snooker Technology Co ltd
Priority date: 2022-02-11
Filing date: 2022-02-11
Publication date: 2022-05-24
Anticipated expiration: 2042-02-11
Also published as: CN114168166A

Abstract

The invention provides an installation configuration method and system of indoor intelligent wireless access equipment, wherein the installation configuration method comprises the following steps: step 1: when a user inputs an installation request, acquiring use requirement information input by the user; step 2: acquiring auxiliary information corresponding to a user based on a preset acquisition rule; and step 3: determining an appropriate installation strategy based on the use requirement information and the auxiliary information; and 4, step 4: and carrying out corresponding installation configuration on the intelligent wireless access equipment based on the installation strategy. According to the installation configuration method and system of the indoor intelligent wireless access equipment, when the installation configuration of the intelligent wireless access equipment is carried out, besides the use requirement information of the user, the auxiliary information corresponding to the user is obtained, and the appropriate installation strategy is cooperatively determined, so that the problem that the user considers the incomplete use during the installation configuration to carry out the subsequent installation configuration again is avoided to the great extent, the convenience is improved, and the user experience is further improved.

Description

Installation configuration method and system of indoor intelligent wireless access equipment

Technical Field

The invention relates to the technical field of Internet of things control, in particular to an installation configuration method and system of indoor intelligent wireless access equipment.

Background

At present, when a user installs and configures intelligent wireless access equipment (such as an internet of things router) at home, the user needs to manually install and configure the intelligent wireless access equipment according to use requirements (such as how to control the internet of things loudspeaker box), when the intelligent wireless access equipment is installed and configured, the user needs to consider the use requirements of the user, if the use requirements are not comprehensive, the user still needs to perform installation and configuration again in the subsequent use, the operation is complicated, and the user experience is also reduced;

therefore, a solution is needed.

Disclosure of Invention

The invention provides an installation configuration method and system of indoor intelligent wireless access equipment, which are used for acquiring auxiliary information corresponding to a user in addition to the use demand information of the user when the installation configuration of the intelligent wireless access equipment is carried out, and cooperatively determining an appropriate installation strategy, thereby greatly avoiding the problem of follow-up installation configuration again caused by incomplete use in the installation configuration of the user, improving convenience and further improving user experience.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, which comprises the following steps:

step 1: when a user inputs an indoor installation request, acquiring use requirement information input by the user;

step 2: acquiring auxiliary information corresponding to the user based on a preset acquisition rule;

and step 3: determining an appropriate installation strategy based on the usage requirement information and the auxiliary information;

and 4, step 4: and carrying out corresponding installation configuration on the intelligent wireless access equipment based on the installation strategy.

Preferably, the step 2: acquiring auxiliary information corresponding to the user based on a preset acquisition rule, wherein the acquisition rule comprises the following steps:

carrying out rule splitting on the acquisition rule to obtain a plurality of first sub-rules;

sequentially traversing the first sub-rule, wherein each traversal time is used for taking the traversed first sub-rule as a second sub-rule;

acquiring a rule weight of the second sub-rule corresponding to the acquisition rule;

inquiring a preset rule weight-necessary threshold library, and determining a necessary threshold corresponding to the rule weight;

acquiring a rule attribute corresponding to the second sub-rule;

inquiring a preset rule attribute-necessary value library, and determining a first necessary value corresponding to the rule attribute;

acquiring at least one rule scene corresponding to the second sub-rule, and acquiring scene weights corresponding to the second sub-rule in the rule scene;

inquiring a preset rule scene-necessary value library, and determining a second necessary value corresponding to the rule scene;

giving the second necessary value corresponding to the scene weight to obtain a third necessary value;

acquiring a plurality of first history acquisition events corresponding to the second sub-rule, and acquiring an acquisition source of the first history acquisition events;

verifying the reliability of the acquisition source, and if the acquisition source passes the verification, taking the corresponding first history acquisition event as a second history acquisition event;

inputting all the second history acquisition events to a preset necessary value determination model to obtain a fourth necessary value;

if the first necessary value is greater than or equal to the necessary threshold value and/or the third necessary value is greater than or equal to the necessary threshold value and/or the fourth necessary value is greater than or equal to the necessary threshold value, taking the corresponding second sub-rule as a third sub-rule;

acquiring an execution process corresponding to the third sub-rule, inputting the execution process to a preset process simulation model, and performing corresponding process simulation based on the process simulation model;

in the process of process simulation, a preset evaluation node set is obtained, and the evaluation node set comprises: a plurality of first evaluation nodes;

obtaining a screening value corresponding to the first evaluation node, if the screening value is greater than or equal to a preset screening threshold value, taking the corresponding first evaluation node as a second evaluation node, and meanwhile, obtaining a node weight corresponding to the second evaluation node;

evaluating the process simulation process through the second evaluation node to obtain a first evaluation value, and giving the first evaluation value corresponding to the node weight to obtain a second evaluation value;

accumulating and calculating all the second evaluation values to obtain evaluation value sums;

if the sum of the evaluation values is greater than or equal to a preset evaluation value and a preset threshold value, taking the corresponding third sub-rule as a fourth sub-rule;

acquiring an auxiliary information item corresponding to the user based on the fourth sub-rule;

and after traversing the first sub-rule is finished, integrating each acquired auxiliary information item to acquire auxiliary information, and finishing acquisition.

Preferably, the verifying the credibility of the acquisition source includes:

acquiring a first credibility corresponding to the acquisition source;

when the obtaining source is unique, if the first credibility is larger than or equal to a preset first credibility threshold value, the credibility verification is passed, otherwise, the credibility verification is not passed;

when the obtaining sources are not unique, obtaining source weight of each obtaining source corresponding to the first historical obtaining event, giving the source weight corresponding to the first credibility, and obtaining second credibility;

and if the second credibility is greater than or equal to a preset second credibility threshold, the credibility verification is passed, otherwise, the credibility verification is not passed.

Preferably, the acquiring the screening value corresponding to the first evaluation node includes:

acquiring a plurality of evaluation records corresponding to the first evaluation node;

obtaining an evaluation type of the evaluation record, wherein the evaluation type comprises: active evaluation and passive evaluation;

when the evaluation type of the evaluation record is active evaluation, dividing the corresponding evaluation record into a plurality of first sub-records;

acquiring record generation time corresponding to the first sub-record, and correspondingly setting the first sub-record on a preset time axis based on the record generation time;

performing feature extraction on the first sub-record to obtain a plurality of first record features;

acquiring a preset detection feature library, matching the first record features with second record features in the detection feature library, if the first record features are matched with the second record features in the detection feature library, taking the corresponding first sub-record as a second sub-record, and acquiring an influence confirmation type and an influence confirmation strategy corresponding to the second record features matched with the first sub-record, wherein the influence confirmation type comprises: individual and associated effects;

when the influence confirmation type is an individual influence, performing corresponding influence confirmation on the second sub-record based on the influence confirmation strategy, and if the confirmation is successful, acquiring a first influence value corresponding to the influence confirmation strategy and associating the first influence value with the first evaluation node;

when the influence confirmation type is the correlation influence, selecting the first sub-record in a preset range before and after the second sub-record on the time axis as a third sub-record;

based on the influence confirmation strategy, carrying out corresponding influence confirmation on the third sub-record, if the confirmation is successful, obtaining a second influence value corresponding to the influence confirmation strategy, and associating the second influence value with the first evaluation node;

accumulating and calculating the first influence value and the second influence value associated with the first evaluation node to obtain an influence value sum;

and taking the reciprocal of the influence value sum as a screening value corresponding to the first evaluation node to finish the acquisition.

Preferably, the step 3: determining an appropriate installation strategy based on the usage requirement information and the auxiliary information, comprising:

and acquiring a proper installation strategy determination model, inputting the use requirement information and the auxiliary information into the installation strategy determination model, acquiring a proper installation strategy, and finishing the determination.

Preferably, the obtaining of the suitable installation strategy determination model includes:

inputting the use requirement information and the auxiliary information into a preset data analysis model to obtain a data analysis result;

performing feature extraction on the data analysis result to obtain a plurality of first data features;

acquiring a preset standby model set, wherein the standby model set comprises: a plurality of first standby models;

acquiring a corresponding feature library corresponding to the first standby model;

matching the first data features with corresponding features in the corresponding feature library, if the first data features are matched with the corresponding features in the corresponding feature library, taking the matched first data features as second data features, and meanwhile, acquiring corresponding capability values corresponding to the matched corresponding features and associating the corresponding first standby models;

integrating third data features except the second data features in the first data features to obtain a first feature set, and endowing the first feature set with model marks corresponding to the first standby model to obtain a second feature set;

accumulating and calculating the corresponding capacity values associated with the first standby model to obtain a capacity value sum;

selecting the maximum capacity value sum as a target value;

if the target value is larger than or equal to a preset target value threshold, taking the corresponding first standby model as a proper installation strategy determination model to finish obtaining;

otherwise, inputting all the second feature sets into a preset collaborative decision model to obtain a decision result, wherein the decision result comprises: a plurality of second backup models of the first backup models;

and combining the models of the second standby model to obtain a proper installation strategy determination model, and finishing the acquisition.

The invention provides an installation configuration system of indoor intelligent wireless access equipment, which comprises:

the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring use requirement information input by a user when the user inputs an indoor installation request;

the second acquisition module is used for acquiring auxiliary information corresponding to the user based on a preset acquisition rule;

a determination module for determining an appropriate installation strategy based on the usage requirement information and the auxiliary information;

and the installation module is used for carrying out corresponding installation configuration on the intelligent wireless access equipment based on the installation strategy.

Preferably, the second obtaining module performs the following operations:

acquiring a rule attribute corresponding to the second sub-rule;

acquiring at least one rule scene corresponding to the second sub-rule, and acquiring scene weight of the rule scene corresponding to the second sub-rule;

acquiring an execution process corresponding to the third sub-rule, inputting the execution process into a preset process simulation model, and performing corresponding process simulation based on the process simulation model;

Preferably, the verifying the credibility of the acquisition source includes:

acquiring a first credibility corresponding to the acquisition source;

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

fig. 1 is a flowchart of an installation configuration method of an indoor intelligent wireless access device according to an embodiment of the present invention;

fig. 2 is a schematic diagram of an installation configuration system of an indoor intelligent wireless access device according to an embodiment of the present invention.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, as shown in figure 1, comprising the following steps:

The working principle and the beneficial effects of the technical scheme are as follows:

when a user inputs an indoor installation request, acquiring use requirement information input by the user (for example, controlling the sound equipment of the Internet of things to play music in the morning); acquiring auxiliary information corresponding to a user based on a preset acquisition rule (for example, acquiring the song listening preference information of the user); determining a proper installation strategy (for example, configuring an Internet of things router to control the Internet of things loudspeaker box to play songs preferred by a user in the morning) based on the use requirement information and the auxiliary information; based on the installation strategy, carrying out corresponding installation configuration on the intelligent wireless access equipment;

when the installation configuration of the intelligent wireless access equipment is carried out, the auxiliary information corresponding to the user is also obtained in addition to the use requirement information of the user, and the appropriate installation strategy is cooperatively determined, so that the problem of follow-up installation configuration again caused by incomplete use in the installation configuration of the user is avoided to a great extent, the convenience is improved, and the user experience is further improved.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, which comprises the following steps: acquiring auxiliary information corresponding to the user based on a preset acquisition rule, wherein the acquisition rule comprises the following steps:

acquiring a rule attribute corresponding to the second sub-rule;

generally, the source of the auxiliary information is not necessarily local (for example, based on a big data technology, the song listening records generated when a user uses a plurality of music platforms are acquired), so when the auxiliary information is acquired, the security and accuracy of the acquisition must be ensured, otherwise, the installation strategy formulation is not suitable, and the acquisition risk is generated, meanwhile, in order to have applicability under the trend of big data development, the acquisition verification is more necessary; in addition, an acquisition verification method for acquiring information based on a big data technology is lacked in the prior art;

therefore, when the auxiliary information corresponding to the user is acquired based on the preset acquisition rule, the acquisition rule is split into a plurality of first sub-rules, the first sub-rules are sequentially traversed, the rule weight of the traversed second sub-rule corresponding to the acquisition rule is acquired during each traversal, and the larger the rule weight is, the more the auxiliary information is acquired based on the second sub-rule; inquiring a preset rule weight-necessary threshold library (necessary thresholds corresponding to different rule weights are stored, wherein the larger the rule weight is, the smaller the necessary threshold is); when the acquisition verification is carried out, the acquisition process simulation is carried out to determine the risk degree, however, if all the rules are subjected to the process simulation, the workload is large, and therefore the rules which need to be subjected to the process model need to be screened out; therefore, the rule attribute corresponding to the second sub-rule is obtained (for example, the second sub-rule is the song listening preference information of the crawling user, and the rule attribute is the crawling information), a preset rule attribute-necessary value library (necessary values corresponding to different rule attributes are stored) is inquired, a first necessary value corresponding to the rule attribute is determined, and the larger the first necessary value is, the more risk is generated in the execution process corresponding to the second sub-rule, and the more necessity for simulation risk verification is generated; acquiring a rule scene (for example, a webpage and a database for information crawling and the like) corresponding to the second sub-rule, acquiring a scene weight corresponding to the second sub-rule in the rule scene, wherein the larger the scene weight is, the more mainly the corresponding second sub-rule executes a corresponding process in the rule scene (for example, the larger the scene weight of the webpage is when the user mainly crawls song listening preference information from a webpage); querying a preset rule scene-necessary value library (a database storing necessary values corresponding to different rule scenes), determining a second necessary value corresponding to the rule scene, wherein the larger the second necessary value is, the larger the risk of executing a corresponding process on the rule scene is (for example, the lower the webpage credibility of a crawled webpage), the more the need of performing simulation risk verification is, giving a scene weight (multiplication) corresponding to the second necessary value, and obtaining a third necessary value (the larger the scene weight is, the smaller the second necessary value corresponding to the rule scene needs to be, so that the safety of rule execution can be ensured); acquiring a first history acquisition event (event record for acquiring auxiliary information historically based on a second sub-rule) corresponding to the second sub-rule, acquiring an acquisition source (such as local and other manufacturers) of the first history acquisition event, verifying the reliability of the acquisition source, inputting the second history acquisition event passing the reliability verification into a preset necessary value determination model (a model which is trained in advance and used for determining the degree of necessity of simulation risk verification corresponding to the second sub-rule based on the history acquisition event, for example, a model generated after learning a large number of records for manually determining the necessity of simulation risk verification by using a machine learning algorithm, for example, if risks occur frequently in the history acquisition event, the simulation verification becomes necessary more frequently), and acquiring a fourth necessary value; if the first necessary value is greater than or equal to the necessary threshold value and/or the third necessary value is greater than or equal to the necessary threshold value and/or the fourth necessary value is greater than or equal to the necessary threshold value, the requirement of simulation verification is indicated, and the corresponding second sub-rule is taken as a third sub-rule; acquiring an execution process (such as a crawling process) corresponding to the third sub-rule, inputting a preset process simulation model (a pre-trained model for process simulation, such as a model generated after learning a large amount of manual process simulation records by using a machine learning algorithm) in the execution process, and performing corresponding process simulation by using the process simulation model; in the process simulation process, a first evaluation node (corresponding to an evaluator responsible for evaluating the process risk, the evaluator can be a pre-trained model for risk evaluation or a manual evaluator) is obtained, meanwhile, a screening value corresponding to the first evaluation node is obtained, the larger the screening value is, the more the evaluation corresponding to the first evaluation node meets the standard, and if the screening value is greater than or equal to a preset screening threshold (constant), the corresponding first evaluation node is taken as a second evaluation node; acquiring node weight corresponding to the second evaluation node, wherein the larger the node weight is, the more the evaluation result corresponding to the second evaluation node can explain how risky the process simulation process is; evaluating the process simulation process through a second evaluation node to obtain a first evaluation value, wherein the larger the first evaluation value is, the smaller the risk of the process simulation process is, and the first evaluation value is given to the node weight (multiplication of the two), so as to obtain a second evaluation value; accumulating (summing) all the second evaluation values to obtain an evaluation value sum; if the sum of the evaluation values is greater than or equal to a preset evaluation value and a preset threshold value, taking the corresponding third sub-rule as a fourth sub-rule, acquiring an auxiliary information item based on the fourth sub-rule, and acquiring auxiliary information by integrating the auxiliary information item;

according to the embodiment of the invention, when the auxiliary information is acquired based on the acquisition rule, the acquisition rule is split and verified respectively, when the auxiliary information is verified, the necessity of simulation verification is firstly determined based on the rule attribute, the rule scene and the historical acquisition event, the resources of the simulation verification are reduced, in addition, the necessary threshold value is determined based on the rule weight, the scene weight corresponding to the second necessary value is given, the setting is reasonable, and the accuracy of the determination of the necessity of the simulation verification is improved; in the simulation verification process, a plurality of evaluation nodes are arranged, the comprehensiveness of risk evaluation in the process simulation process is improved, and the verification quality and the verification efficiency of the simulation verification are improved.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, which is used for verifying the credibility of an acquisition source and comprises the following steps:

acquiring a first credibility corresponding to the acquisition source;

when the acquisition source is unique, if the first credibility is greater than or equal to a preset first credibility threshold, the credibility verification is passed, otherwise, the credibility verification is not passed;

the number of the acquisition sources may be 1 or more, so when the reliability of the acquisition sources is verified, the verification needs to be performed on a case-by-case basis on the number of the acquisition sources, and when the number of the acquisition sources is multiple, the supply ratios of data provided and acquired by different acquisition sources are different, and comprehensive analysis needs to be performed;

therefore, a first confidence level corresponding to the acquisition source is obtained (e.g., the first confidence level can be determined based on the historical truth of the data acquired from the acquisition source); when the acquired sources are unique (the number is 1), if the first credibility is greater than or equal to a preset first credibility threshold (constant), the credibility passes verification, otherwise, the credibility does not pass verification; when the acquisition sources are not unique (the number is more than 1), acquiring the source weight of each acquisition source corresponding to the acquisition event (the acquisition event is provided by the acquisition sources together, the larger the source weight is, the larger the occupation ratio provided by the corresponding acquisition source is, the source weight is more than 0 and less than 1), giving the source weight corresponding to the first credibility (the multiplication of the two), acquiring the second credibility, if the second credibility is more than or equal to a preset second credibility threshold (constant), the credibility passes the verification, otherwise, the credibility does not pass;

when the reliability verification is performed on the acquired sources, the reliability verification is performed respectively based on the number of the acquired sources, the setting is reasonable, and the accuracy of the reliability verification is improved.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, which is used for acquiring a first credibility corresponding to an acquisition source and comprises the following steps:

acquiring credibility verification information corresponding to the acquisition source;

acquiring a preset verification policy set, wherein the verification policy set comprises: a plurality of verification policies;

correspondingly verifying the credibility verification information based on the verification strategy to obtain a plurality of verification values;

obtaining a strategy weight corresponding to the verification strategy;

calculating a first credibility corresponding to the acquisition source based on the policy weight and the verification value, wherein a calculation formula is as follows:

wherein the content of the first and second substances,

a first confidence level corresponding to the acquisition source,

is as follows

The policy weight corresponding to each verification policy,

is based on

The first verification strategy is obtained after the credibility verification information is correspondingly verified

The number of the verification values is determined,

in order to verify the total number of policies,

is based on

And the verification strategies correspondingly verify the credibility verification information to obtain the total number of verification values.

when the first credibility of the acquisition source is acquired, acquiring credibility verification information (such as identity verification information) corresponding to the acquisition source; acquiring a verification strategy (for example, verifying whether the identity verification is new or not), correspondingly verifying the credibility verification information based on the verification strategy, and acquiring a plurality of verification values (obtained by multiple times of verification); acquiring strategy weight corresponding to the verification strategy, wherein the larger the strategy weight is, the more the verification result obtained by adopting the corresponding verification strategy to carry out corresponding verification can be used for acquiring the credibility of the source; calculating a first reliability based on the strategy weight and the verification value, wherein in the formula, the strategy weight and the verification value are positively correlated with the first reliability and are reasonably set;

in the embodiment of the invention, when the first credibility is obtained, a plurality of verification strategies are set to verify the credibility verification information of the obtained source, so that the accuracy of obtaining the first credibility is improved, and in addition, the first credibility is quickly calculated through the formula based on the strategy weight and the verification value, so that the working efficiency of the system is improved.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, wherein the step of acquiring a screening value corresponding to a first evaluation node comprises the following steps:

in order to ensure the reliability of the evaluation of the first evaluation node on the process simulation process and improve the evaluation quality, the first evaluation node needs to be screened to ensure that the finally adopted second evaluation node can be competent for the evaluation task;

therefore, when the first evaluation node is screened, the evaluation record corresponding to the first evaluation node (history evaluation process simulation process risk record) is obtained, and the evaluation types of the evaluation record are divided into active evaluation (the process simulation process is input into the model corresponding to the evaluation party, after the model evaluation, the evaluation result is output, the model corresponding to the evaluation party actively supplements evaluation, the process of the active supplement evaluation is the autonomous process of the model; the risk of the process simulation process can be evaluated by a manual evaluation party) and passive evaluation (the process simulation process is input into the model corresponding to the evaluation party, and the evaluation result is obtained); when the evaluation type of the evaluation record is active evaluation, the active evaluation is a process of model autonomous supplementary evaluation, whether the evaluation is reasonable needs to be confirmed, the corresponding evaluation record is divided into a plurality of first sub-records, record generation time corresponding to the first sub-records is obtained, the first sub-records are arranged on a preset time axis based on the first sub-records, first record features of the first sub-records are extracted (realized based on a feature extraction technology) and are matched with second record features in a preset detection feature library (storing a large number of features suspected to be abnormal in the evaluation process), if the first record features are matched with the second record features, an influence confirmation type and an influence confirmation strategy (a strategy for confirming whether the influence is actually generated) corresponding to the matched second record features are obtained, the influence confirmation type is divided into independent influences (influences are generated on other process features in the second sub-records of the second sub-records, for example, the second sub-records are a certain evaluation process, the second record characteristic matched with the second record characteristic is a process non-standard characteristic in the evaluation process, so that the evaluation is a process of gradual reasoning, and the evaluation has an influence on a process of continuing evaluation later in the evaluation process of the second record characteristic and an associated influence (for example: the second sub-record is an evaluation process, and if the evaluation is not standard, the second sub-record which is an evaluation result determination process is influenced); when the confirmation type is the single influence, performing corresponding influence confirmation on the second sub-record based on a confirmation strategy, and if the confirmation is successful, acquiring a first influence value corresponding to the confirmation strategy, wherein the larger the first influence value is, the larger the influence generated by the confirmation is; when the confirmation type is the correlation influence, selecting a third sub-record item in a preset range (for example, 10 seconds) before and after the second sub-record on the time axis, correspondingly confirming based on a confirmation strategy in the same way, and if the confirmation is successful, acquiring a corresponding second influence value; accumulating and calculating a first influence value and a second influence value associated with the first evaluation node to obtain an influence value sum, wherein the larger the influence value sum is, the more the historical evaluation of the corresponding first evaluation node is not standard, and the reciprocal of the influence value sum is taken as a screening value;

when the screening value corresponding to the first evaluation node is obtained, the screening value is determined based on the evaluation record corresponding to the first evaluation node, and the setting is reasonable; meanwhile, the evaluation records required to be used for screening value determination are screened out based on the types of the evaluation records, so that determination resources are reduced; when the screening value is determined, the detection feature library is set, when influence confirmation is found to be needed, the influence confirmation is carried out, and when the influence confirmation is carried out, the sub-records needing the influence confirmation are quickly selected based on the confirmation type to carry out the influence confirmation, so that the determination efficiency of the screening value determination is improved, and the determination resources are further reduced.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, which comprises the following steps: determining an appropriate installation strategy based on the usage requirement information and the auxiliary information, comprising:

when the appropriate installation strategy is determined, acquiring an appropriate installation strategy determination model (a model for determining the appropriate installation strategy based on the use requirement information and the auxiliary information), inputting the use requirement information and the auxiliary information into the installation strategy determination model, determining the appropriate installation strategy by the installation strategy determination model, and outputting the appropriate installation strategy after the determination of the installation strategy determination model is completed;

the embodiment of the invention determines the appropriate installation strategy based on the installation strategy determination model, improves the working efficiency of the system and is more intelligent.

The invention provides an installation configuration method of indoor intelligent wireless access equipment, wherein the obtaining of a proper installation strategy determination model comprises the following steps:

selecting the maximum capacity value as a target value;

otherwise, inputting all the second feature sets into a preset collaborative decision model to obtain a decision result, wherein the decision result comprises: a plurality of second standby models of the first standby model;

in an actual use situation, a large number of users can send case requests at the same time, if all the first standby models are combined into one model, a large number of installation strategy determination tasks cannot be handled, and waiting can be caused for the users;

therefore, when obtaining a proper installation strategy determination model, the use requirement information and the auxiliary information are input into a preset data analysis model (a pre-trained model for data analysis, for example, a model generated after learning a large amount of records for manual data analysis by using a machine learning algorithm, which can perform data cleaning, effective information extraction and the like on data), and after the data analysis model is analyzed, a data analysis result is output; extracting first data characteristics of a data analysis result; acquiring a first standby model (corresponding to a training group, used for training an alternative installation strategy determination model used for determining a proper installation strategy, for example, training on the basis of a large number of manual determination records through a machine learning algorithm), acquiring a corresponding feature library corresponding to the first standby model (storing data features of the first standby model which are good at the basis when the proper installation strategy is determined), matching the first data features with corresponding features in the corresponding feature library, and if the first data features are matched with the corresponding features, taking the matched first data features as second data features, and acquiring a corresponding capacity value corresponding to the matched corresponding features, wherein the larger the capacity value is, the better the corresponding first standby model is at the basis of the second data features; integrating third data features (data features according to which the first standby model is not deleted) in the first data features except all the second data features to obtain a first feature set, endowing the first feature set with a model mark corresponding to the first standby model (the first standby model is convenient to distinguish by a cooperative decision model), and obtaining a second feature set; accumulating and calculating corresponding capacity values associated with the first standby model to obtain capacity value sums, selecting the maximum target value, if the maximum target value is greater than or equal to a preset target value threshold (constant), indicating that the corresponding first standby model sufficiently corresponds, and using the maximum target value as a proper installation strategy determination model; otherwise (the target value is smaller than the target value threshold), which indicates that the situation cannot be sufficiently responded, all the second feature sets are input into a preset cooperative decision model (a model which is trained in advance and used for cooperative decision making, for example, a model generated after a large number of records of manual cooperative decision making are learned by using a machine learning algorithm, the model can determine a first backup model which can be complemented according to data features on which each first backup model is not good at, after the decision of the cooperative decision model is finished, a decision result is output, the decision result comprises a plurality of second backup models, the second backup models are combined (the combination of the models belongs to the field of the prior art and is not repeated), and then a proper installation strategy determination model is obtained;

when the appropriate installation strategy formulation model is obtained, the use requirement information and the auxiliary updates are firstly input into the data analysis model for data analysis, so that the workload of subsequent feature extraction is reduced; setting a plurality of first standby models, and selecting a proper installation strategy determination model from the first standby models based on corresponding coping feature libraries; when the first standby model is selected, if the first standby model can sufficiently cope with the installation strategy, the first standby model is used as the installation strategy determination model, and if the first standby model cannot sufficiently cope with the installation strategy, the second standby model which is suitable for cooperative work is selected and combined, so that the determination quality of the suitable installation strategy is ensured, the determination efficiency is improved, and the method has high applicability.

The invention provides an installation configuration system of indoor intelligent wireless access equipment, as shown in fig. 2, comprising:

the system comprises a first acquisition module 1, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring use requirement information input by a user when the user inputs an indoor installation request;

the second obtaining module 2 is configured to obtain auxiliary information corresponding to the user based on a preset obtaining rule;

a determining module 3, configured to determine an appropriate installation strategy based on the usage requirement information and the auxiliary information;

and the installation module 4 is used for carrying out corresponding installation configuration on the intelligent wireless access equipment based on the installation strategy.

The working principle and the beneficial effects of the technical scheme are already explained in the method claim, and are not described in detail.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims

1. An installation configuration method of indoor intelligent wireless access equipment is characterized by comprising the following steps:

and 2, step: acquiring auxiliary information corresponding to the user based on a preset acquisition rule;

and 4, step 4: based on the installation strategy, carrying out corresponding installation configuration on the intelligent wireless access equipment;

the step 2: acquiring auxiliary information corresponding to the user based on a preset acquisition rule, wherein the acquisition rule comprises the following steps:

inquiring a preset rule weight-necessary threshold library, and determining an necessary threshold corresponding to the rule weight;

acquiring a rule attribute corresponding to the second sub-rule;

2. The method for installing and configuring an indoor intelligent wireless access device according to claim 1, wherein the verifying the trustworthiness of the acquisition source comprises:

acquiring a first credibility corresponding to the acquisition source;

3. The method for installing and configuring an indoor intelligent wireless access device according to claim 1, wherein the obtaining of the screening value corresponding to the first evaluation node includes:

4. The method for installing and configuring an indoor intelligent wireless access device according to claim 1, wherein the step 3: determining an appropriate installation strategy based on the usage requirement information and the auxiliary information, comprising:

5. The method for configuring an installation of an indoor intelligent wireless access device according to claim 4, wherein the obtaining of the suitable installation policy determination model includes:

selecting the maximum capacity value as a target value;

6. An installation configuration system of indoor intelligent wireless access equipment, comprising:

the installation module is used for carrying out corresponding installation configuration on the intelligent wireless access equipment based on the installation strategy;

the second obtaining module performs the following operations:

acquiring a rule attribute corresponding to the second sub-rule;

inputting all the second history acquisition events into a preset necessary value determination model to obtain a fourth necessary value;

7. The system for installation configuration of an indoor intelligent wireless access device as claimed in claim 6, wherein said verifying the trustworthiness of said acquisition source comprises:

acquiring a first credibility corresponding to the acquisition source;

8. The system for installing and configuring an indoor intelligent wireless access device according to claim 6, wherein the obtaining of the screening value corresponding to the first evaluation node includes: