CN107909376A - A kind of power system customer satisfaction reponse system - Google Patents
A kind of power system customer satisfaction reponse system Download PDFInfo
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- CN107909376A CN107909376A CN201711270693.6A CN201711270693A CN107909376A CN 107909376 A CN107909376 A CN 107909376A CN 201711270693 A CN201711270693 A CN 201711270693A CN 107909376 A CN107909376 A CN 107909376A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/01—Customer relationship services
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention discloses a kind of power system customer satisfaction reponse system, including：Satisfaction investigation module：For obtaining user satisfaction information, consumers' opinions or problem and the feedback result to issue-resolution；And the information of acquisition is sent to service centre's module；Service centre's module, including：Correlation analysis unit：Consumers' opinions or problem are analyzed using correlation analysis method, provide the relevance between variety classes problem；Being there is provided according to question history process experience may effective solution；Suggestion feedback module, including：Feedback result receiving unit：For receiving user to the feedback result information of solution and sending to service centre's module.Beneficial effect of the present invention：User friendly system of the present invention, can ensure that user's comments obtain the answer of satisfaction, and can be reflected by the system and solve the problems, such as that power grid enterprises produce in operation.
Description
Technical field
The present invention relates to computer technology and technical field of power systems, more particularly to a kind of user satisfaction feedback system
System.
Background technology
Client service center of enterprise higher level needs to reply customer problem situation, Yi Jiyong by data target to understand client service center
Family feedback.Present user presents one's view problem and customer service to obtain the mode of client feedback be by phone, Email
The methods of Deng telecommunications approach or writing recommendation letter.Satisfaction investigation mode be also mostly client feedback problem whether solve with
And whether satisfied, some power grid enterprises can provide client's form of marking.
Whether which kind of above-mentioned investigation method, due to no unified opinion form, client service center's statistical problem and opinion
When difficulty it is big and information is not complete.In addition, when user's answer is given after Resolving probiems, since user's contact information is various or scarce
Lose, therefore can not necessarily accomplish to feed back in time, this may cause user to reply and propose problem and opinion repeatedly, shadow
The efficiency of client service center of power grid enterprises processing business is rung, satisfaction can not be made to effectively improve.
In addition, the method for power grid enterprises' statistics opinion problem also have it is very big restricted, it is necessary to which a kind of can be by user's
The method of the statistics of demand and problem occurred frequently, can preferably be supplied to user service, and problem occurred frequently be carried out pre- in advance
Anti- and reply.This needs to focus on consumers' opinions and problem, and feature extraction, and data volume and complexity decide this
The degree of difficulty and necessity of Resolving probiems.
To sum up, nowadays do not have a kind of energy to customer satisfaction survey and feedback in power grid enterprises' customer service system
Enough accomplish the method and system of precise and high efficiency, and interaction effect is unsatisfactory between user.
The content of the invention
The purpose of the present invention is exactly to solve the above-mentioned problems, there is provided a kind of power system customer satisfaction reponse system
And method, the system and method can obtain user satisfaction and to user feedbacks, not only increase the essence of Satisfaction
Degree, and human cost can be saved, moreover it is possible to the user that feeds back to promptly and accurately will be replied, and to institute in power grid enterprises' processing operation
The problem of running into provides rational solution.
To achieve these goals, the present invention adopts the following technical scheme that：
The invention discloses a kind of power system customer satisfaction reponse system, including：
Satisfaction investigation module：For obtaining user satisfaction information, consumers' opinions or problem and to Resolving probiems side
The feedback result of case；And the information of acquisition is sent to service centre's module；
Service centre's module, including：
Correlation analysis unit：Consumers' opinions or problem are analyzed using correlation analysis method, provided not of the same race
Relevance between class problem；Being there is provided according to question history process experience may effective solution；
Suggestion feedback module, including：
Feedback result receiving unit：For receiving user to the feedback result information of solution and sending to service centre
Module.
Further, the satisfaction investigation module is in the form of the either satisfactory value that scores or user's attitude and the mould of experience
Paste form determines user satisfaction；The consumers' opinions or problem include：Place, problem types and problem detailed content letter
Breath.
Further, service centre's module further includes：
Prioritizing unit：For carrying out the division of processing priority according to the satisfaction information of user.
Further, service centre's module further includes：
First statistic of classification unit：For the consumers' opinions received or problem to be carried out statistic of classification, and according to generation
Frequency selects problem occurred frequently.
Further, each department is subjected to statistic of classification according to customer problem species, described problem species includes：Power supply
Reliability, electric meter fault, electricity charge standard, power quality and customer service quality；If each Questions types are divided into according to actual needs
Dry subproblem.
Further, suggestion feedback module is stated to further include：
Second statistic of classification unit：For being sent after the solution provided for consumers' opinions or problem is classified
To satisfaction investigation module.
Further, the suggestion feedback module further includes：
Information cluster unit：For the feedback result information according to user to solution, by site and opinion or
The identical user of problem carries out Density Clustering, by site is close and opinion or the identical user of problem are divided into same area
Domain；
Storage unit：For being stored to cluster result.
Further, the Density Clustering method includes：
Set number of users N and distributing position Pi(xi,yi), meet to be divided into different zones according to user density setting
Radius R and meet region minimum number user density Min；
It is described to meet that being divided into the radius R of different zones is specially：
Wherein,D represents the dimension of data combination D；VolumeDRepresent the area of data acquisition system D.
Further, the value of the Min is arranged between 2~10, is made choice according to actual conditions.
Further, the correlation analysis method is specially：
If D={ χ1,χ2,χjIt is the set of all in D, any subset A of X is known as item collection, | A |=K then claims set A
For K item collections；Then in transaction database D, it includes the support meter that the number of the affairs of certain specific item collection A is known as item collection A
Counting σ (A) is：
Assuming that item collectionAnd A ∩ B=φ, then it is correlation rule to define correlation A → B, A, B respectively into
For the premise and conclusion of correlation rule A → B；The support of A → B correlation rules is that the percentage of A ∪ B is included in database D, note
For
Sup (A → B)=P (A ∪ B)
At this time, support then shows that the correlation degree of premise A and conclusion B are higher closer to 1；
The confidence level of A → B correlation rules is to include comprising A while also the percentage of B, i.e. conditional probability P (B in database D
| A), it is denoted as
Confidence level characterizes the credibility of correlation rule, i.e. confidence level is higher, illustrates that its confidence level is higher；
Based on above-mentioned association rules method, calculate the confidence level and support of each problem, so can try to achieve problem it
Between degree of association situation.
Beneficial effect of the present invention：
User friendly system of the present invention, can ensure that user's comments obtain the answer of satisfaction, and can be by this
System reflects and solves the problems, such as that power grid enterprises produce in operation.
Density clustering is carried out according to user locations and problem, the customer problem for being divided into the same area is united
One solve, be convenient for problem investigation and service work carry out, be recorded into database, when same problem when the ground occurs for
With reference to raising Resolving probiems speed.
Brief description of the drawings
Fig. 1 is power system customer satisfaction feedback system structure schematic diagram of the present invention；
Fig. 2 associates schematic diagram between power system customer satisfaction reponse system modules of the present invention and user；
Fig. 3 is power system customer satisfaction reponse system work flow diagram of the present invention.
Embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other without making creative work
Embodiment, belongs to the scope of protection of the invention.
The present invention provides a kind of power system customer satisfaction reponse system, as shown in Figure 1, including：
Satisfaction investigation module：For obtaining user satisfaction information, consumers' opinions or problem and to Resolving probiems side
The feedback result of case；And the information of acquisition is sent to service centre's module；
In embodiments of the present invention, user fills in satisfaction situation and problem in access customer satisfaction investigation module, its
Text data store is in Computer Database.From Computer Database can according to different user come obtain its it is relevant in
Hold.
The function that satisfaction investigation module it is also required to provide is that design meets power grid enterprises' needs, its investigation result obtains
And processing procedure is as follows：
(1) survey objective
Satisfaction investigation purpose one is in order to obtain user satisfaction, with score the either concrete form such as satisfactory value or
The fuzzy form such as user's attitude and experience determines user satisfaction；The second is in order to obtain there are the problem of and consumers' opinions etc.；
The third is the job performance of power grid enterprises' customer service system can be examined.Therefore design seismic wave problem have to cover it is above-mentioned some
Content, enables user's fill substance to obtain effective information.
(2) investigation method
Investigation method can be various modes, for convenient and efficient, there is provided satisfaction investigation problem it is main with selected as
Form, marking and consumers' opinions part are filled in for user oneself.
Wherein user's marking divides marking grade according to satisfaction.The satisfaction given a mark according to counting user, to its phase
The processing relative importance value of pass problem is divided.
The acquisition form of investigation result can be the various forms such as phone, mail, questionnaire.
(3) problem content
The design of the problem of in investigation result needs the viewpoint and opinion for allowing user to express oneself, and disclosure satisfy that and allow user to expire
Meaning degree system extracts the requirement of effective information.
Consumers' opinions presents one's view and problem for user, and it is detailed that user writes the problem of oneself runs into type, place, problem exactly
Content.
After customer problem solution situation is sent to user for suggestion feedback module to the feedback result of issue-resolution,
The degree of recognition of the user to feedback result.It can be divided into two parts, Part I user's select permeability solution according to being actually needed
Certainly or unresolved, Part II user is according to unresolved situation continued feedback user opinion.
Service centre's module, including：
Correlation analysis unit：Consumers' opinions or problem are analyzed using correlation analysis method, provided not of the same race
Relevance between class problem, answer is provided easy to relevant departments.Can also be after the problem degree of association be set up, according to problem
History process experience provides the set that may effectively solve method for relevant departments' selection, it is possible to increase the efficiency of issue handling
And quality.
The related coefficient that correlation analysis must go wrong is done using relevance between customer problem.For the more of customer problem
Sample, correlation differs between different problems, and ammeter problem may be asked by power quality problem, external damage etc. in actual example
Topic causes, and may not have correlation between some problems.Correlation analysis between problem can be produced preferably in problem analysis
The reason for raw, can be with solution to the problem.
Different Questions types are numbered from I1 to In, then problem set D is { I1, I2, I3 ..., In }, according to degree investigation knot
The problem of fruit, statistical conditions were collected, and D is the set of problem subset δ, D={ δ1,δ2,δN, N is subset affairs in database
Number.Certain subset affairs is denoted as δi={ χ1, χ2..., χi, χ is known as item.If D={ χ1,χ2,χjIt is the collection of all in D
Closing, any subset A of X is known as item collection, | A | then set A is referred to as K item collections to=K.In transaction database D, it is specific that it includes certain
The number of the affairs of item collection A is known as the support counting of item collection A, is denoted as σ (A), can be expressed as in Probability：
Assuming that item collectionAnd A ∩ B=φ, then it is correlation rule to define correlation A → B, A, B respectively into
For the premise and conclusion of correlation rule A → B.The support of A → B correlation rules is that the percentage of A ∪ B is included in database D, note
For：
Sup (A → B)=P (A ∪ B)
At this time, support then shows that the correlation degree of premise A and conclusion B are higher closer to 1.A → B correlation rules are put
Reliability is to include comprising A while also the percentage of B in database D, i.e. and conditional probability P (B | A), it is denoted as：
Confidence level characterizes the credibility of correlation rule, i.e. confidence level is higher, illustrates that its confidence level is higher.
According to above-mentioned association rules method, calculate the confidence level and support of each problem, so can try to achieve problem it
Between degree of association situation.
Prioritizing unit：For carrying out the division of processing priority according to the satisfaction information of user.To user's
Satisfaction is counted, i.e. counting user marking situation, and collecting.The satisfaction given a mark according to counting user is related to it
The processing priority of problem is divided, and priority is set according to user's marking situation, and the high user of priority needs to resit an exam
Consider.
First statistic of classification unit：For the consumers' opinions received or problem to be carried out statistic of classification, and according to generation
Frequency selects problem occurred frequently.
By each department according to customer problem species carry out statistic of classification, selectable Questions types have power supply reliability,
Electric meter fault, electricity charge standard, power quality, customer service quality etc.；Each Questions types are divided into some subproblems according to actual needs,
Such as：Power quality has voltage fluctuation flickering, voltage three-phase imbalance, harmonic wave and humorous in problem involved in actual preference
Ripple, frequency departure etc..
Service centre's module provides possible effective solution according to customer problem and relevant issues and determines method to relevant departments；
Using correlation analysis, problem and its related question are obtained, and method is solved according to history, provides and asks accordingly
Optional solution method is inscribed, due to the diversity of the species of problem, and the difference of proportion, the method that can be provided need to pass through
Weight coefficient selects, and wherein weight coefficient formula is：
Wi in formula, j are the normal weight coefficient of the jth kind subproblem in i-th kind big problem；Ci, j are in i-th kind big problem
The confidence level of jth kind subproblem；Mi is the subproblem number included in i-th kind big problem.
According to above problem weight coefficient, service centre's module can provide corresponding way to solve the problem and give other departments
As reference, and by this it is stored in database.
Suggestion feedback module, including：
Feedback result receiving unit：The answer that other departments provide is fed back into user, i.e., problem and meaning are proposed to user
See and make feedback.User is received to the feedback result information of solution and is sent to service centre's module.
User makes the answer provided evaluation by suggestion feedback module, i.e., in user's degree investigation result of return
Fill in solution or unresolved in feedback result column.If unresolved, an open question is filled in, then investigation result will pass through opinion
Feedback module returns to service centre.
Second statistic of classification unit：For being sent after the solution provided for consumers' opinions or problem is classified
To satisfaction investigation module.
Information cluster unit：For the feedback result information according to user to solution, by site and opinion or
The identical user of problem carries out Density Clustering, by site is close and opinion or the identical user of problem are divided into same area
Domain；
Storage unit：For being stored to cluster result.
Gathered according to the user that user locations and its problem acquired in customer satisfaction survey result are identical into line density
Class, is divided into the same area by adjacent relatively near and generation problem same subscriber, is convenient for problem investigation and service work is carried out；
On the other hand database can be recorded into, when same problem can improve Resolving probiems speed for reference when the ground occurs.This is close
It is according to number of users N and distributing position P to spend clustering methodi(xi,yi), satisfaction is set according to user density and is divided into not same district
The radius R in domain and meet region minimum number user density Min.R and Min sets formula as follows：
Wherein,D represents the dimension of data combination D, is 2.VolumeDRepresent data acquisition system D's
Area.The value of Min generally can be positioned between 2~10, be made choice according to actual conditions, can be selected when user is more compared with
Fractional value, it is on the contrary then select bigger numerical.Proximal subscribers can be divided into according to the method based on density by different regions,
There is preferable effect to problem feedback and results acquisition result.
Associating between power system customer satisfaction reponse system modules and user and systems approach flow are such as
Shown in Fig. 2 and Fig. 3, after getting customer satisfaction survey content, classified by satisfaction investigation module, collected, and by institute
Information submit to service centre's module, service centre's module is classified according to customer problem, type, place, according to marking
Situation sets relative importance value；Service centre is extracted customer problem content using segmenter, is obtained using correlation analysis method
Take the degree of association between customer problem and feasible solution is provided accordingly.
Customer problem is submitted to relevant departments of power grid enterprises by service centre's module, relevant departments will reply content send to
Suggestion feedback module, answer is fed back to user by suggestion feedback module, and obtains field feedback.
In addition, in the embodiment of the user satisfaction reponse system of above-mentioned example, the logical partitioning of each function module is only
It is illustrate, can be as needed in practical application, such as the realization of the configuration requirement or software for corresponding hardware
It is convenient to consider, above-mentioned function distribution is completed by different function modules, will the CSAT evaluation system it is interior
Portion's structure is divided into different function modules, to complete all or part of function described above.Wherein each function mould both may be used
Realize, can also be realized in the form of software function module in the form of using hardware.
One of ordinary skill in the art will appreciate that realizing all or part of flow in above-described embodiment method, being can
To instruct relevant hardware to complete by computer program, the program can be stored in computer read/write memory medium
In, as independent production marketing or use.Described program upon execution, can perform the whole of the embodiment such as above-mentioned each method
Or part steps.Wherein, the storage medium can be magnetic disc, CD, read-only memory, or random access memory
Deng.
Although above-mentioned be described the embodiment of the present invention with reference to attached drawing, model not is protected to the present invention
The limitation enclosed, those skilled in the art should understand that, on the basis of technical scheme, those skilled in the art are not
Need to make the creative labor the various modifications that can be made or deformation still within protection scope of the present invention.
Claims (10)
- A kind of 1. power system customer satisfaction reponse system, it is characterised in that including：Satisfaction investigation module：For obtaining user satisfaction information, consumers' opinions or problem and to issue-resolution Feedback result；And the information of acquisition is sent to service centre's module；Service centre's module, including：Correlation analysis unit：Consumers' opinions or problem are analyzed using correlation analysis method, variety classes is provided and asks Relevance between topic；Being there is provided according to question history process experience may effective solution；Suggestion feedback module, including：Feedback result receiving unit：For receiving user to the feedback result information of solution and sending to service centre's mould Block.
- A kind of 2. power system customer satisfaction reponse system as claimed in claim 1, it is characterised in that the satisfaction tune Module is looked into the form of the either satisfactory value that scores or user's attitude and the fuzzy form of experience determine user satisfaction；The user Opinion or problem include：Place, problem types and problem detailed content information.
- A kind of 3. power system customer satisfaction reponse system as claimed in claim 1, it is characterised in that the service centre Module further includes：Prioritizing unit：For carrying out the division of processing priority according to the satisfaction information of user.
- A kind of 4. power system customer satisfaction reponse system as claimed in claim 1, it is characterised in that the service centre Module further includes：First statistic of classification unit：For the consumers' opinions received or problem to be carried out statistic of classification, and according to occurrence frequency Select problem occurred frequently.
- 5. a kind of power system customer satisfaction reponse system as claimed in claim 4, it is characterised in that press each department Statistic of classification is carried out according to customer problem species, described problem species includes：Power supply reliability, electric meter fault, electricity charge standard, electric energy Quality and customer service quality；Each Questions types are divided into some subproblems according to actual needs.
- A kind of 6. power system customer satisfaction reponse system as claimed in claim 1, it is characterised in that the suggestion feedback Module further includes：Second statistic of classification unit：For being sent after the solution provided for consumers' opinions or problem is classified to full Meaning degree inquiry module.
- A kind of 7. power system customer satisfaction reponse system as claimed in claim 1, it is characterised in that the suggestion feedback Module further includes：Information cluster unit：For the feedback result information according to user to solution, by site and opinion or problem Identical user carries out Density Clustering, by site is close and opinion or the identical user of problem are divided into the same area；Storage unit：For being stored to cluster result.
- A kind of 8. power system customer satisfaction reponse system as claimed in claim 7, it is characterised in that the Density Clustering Method includes：Set number of users N and distributing position Pi(xi,yi), the radius R for meeting to be divided into different zones according to user density setting And meet region minimum number user density Min；It is described to meet that being divided into the radius R of different zones is specially：<mrow> <mi>R</mi> <mo>=</mo> <msup> <mrow> <mo>{</mo> <mfrac> <mrow> <msub> <mi>Volume</mi> <mi>D</mi> </msub> <mo>*</mo> <mi>M</mi> <mi>i</mi> <mi>n</mi> <mo>*</mo> <mi>&Gamma;</mi> <mrow> <mo>(</mo> <mfrac> <mi>d</mi> <mn>2</mn> </mfrac> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> <mrow> <mi>N</mi> <mo>*</mo> <msqrt> <msup> <mi>&pi;</mi> <mi>d</mi> </msup> </msqrt> </mrow> </mfrac> <mo>}</mo> </mrow> <mi>d</mi> </msup> <mo>;</mo> </mrow>Wherein,D represents the dimension of data combination D；VolumeDRepresent the area of data acquisition system D.
- A kind of 9. power system customer satisfaction reponse system as claimed in claim 8, it is characterised in that the value of the Min It is arranged between 2~10, is made choice according to actual conditions.
- A kind of 10. power system customer satisfaction reponse system as claimed in claim 1, it is characterised in that the relevance Analysis method is specially：If D={ χ1,χ2,χjIt is the set of all in D, any subset A of X is known as item collection, | A | then set A is referred to as K to=K Collection；Then in transaction database D, it includes the support counting σ (A) that the number of the affairs of certain specific item collection A is known as item collection A For：<mrow> <mi>&sigma;</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mo>=</mo> <mo>|</mo> <mo>{</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>|</mo> <mi>A</mi> <mo>&SubsetEqual;</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>&SubsetEqual;</mo> <mi>D</mi> <mo>}</mo> <mo>|</mo> <mo>;</mo> </mrow>Assuming that item collectionAnd A ∩ B=φ, then it is correlation rule to define correlation A → B, and A, B respectively become pass Join the premise and conclusion of rule A → B；The support of A → B correlation rules is that the percentage of A ∪ B is included in database D, is denoted asSup (A → B)=P (A ∪ B)At this time, support then shows that the correlation degree of premise A and conclusion B are higher closer to 1；The confidence level of A → B correlation rules is to include comprising A while also the percentage of B in database D, i.e. conditional probability P (B | A), It is denoted as<mrow> <mi>C</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>&RightArrow;</mo> <mi>B</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>P</mi> <mrow> <mo>(</mo> <mi>B</mi> <mo>|</mo> <mi>A</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>P</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>&cup;</mo> <mi>B</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mi>P</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>&times;</mo> <mn>100</mn> <mi>%</mi> </mrow>Confidence level characterizes the credibility of correlation rule, i.e. confidence level is higher, illustrates that its confidence level is higher；Based on above-mentioned association rules method, the confidence level and support of each problem are calculated, and then can try to achieve and close between problem Connection degree situation.
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| CN110888864A (en) * | 2019-11-27 | 2020-03-17 | 北京国腾联信科技有限公司 | Automatic user data collection method and device |
| CN112785346A (en) * | 2021-02-04 | 2021-05-11 | 成都秦川物联网科技股份有限公司 | Natural gas energy metering data information service method and system |
| CN114004457A (en) * | 2021-10-11 | 2022-02-01 | 云南电网有限责任公司 | Accurate positioning method and system for power distribution network planning problem root cause |
| US11847186B2 (en) | 2021-02-04 | 2023-12-19 | Chengdu Qinchuan Iot Technology Co., Ltd. | Methods and systems for obtaining user evulation used in natural gas energy measurement |
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