CN111461574A - User electricity charge clearing risk discovery method based on regional geographical position information - Google Patents
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Abstract
The invention discloses a method for discovering the risk of clearing the electric charge of a user based on regional geographical position information, which organizes users with approximate clearing fee conditions in a certain geographical region range together by utilizing a consistency expansion operator and stores the users in a user clearing region table. And then calculating the clearing risk of a new user based on the distance between the new user and the list item in the clearing area table of the user, and realizing the discovery of the clearing risk of the electric charge of the user. By using the method and the device, the aims of introducing fewer geographical position attributes which are easy to collect and accurately discovering the risk of clearing the arrearage of the electric charge can be achieved under the condition of only inputting the position and the arrearage information of one group of users.
Description
The technical field is as follows:
the invention discloses a user electricity charge clearing risk discovery method based on regional geographical position information, relates to a user electricity charge clearing risk discovery method and belongs to the technical field of electricity consumption management of power grid users.
Background art:
with the economic development and the expansion of power grid users, the risk of clearing the arrearages of part of the users exists, and if more users arrearages, the income of power grid enterprises is greatly influenced. Therefore, it is very necessary to pre-judge and decide the risk of clearing the user's electric charge, and to perform preventive treatment on the possible clearing in advance, so that finding the risk of clearing the user's electric charge is very important for the healthy and orderly operation of the power grid enterprise.
In the traditional field based on big data analysis, the main means of analyzing the arrearages, frauds and default conditions of users in a certain range are as follows: collecting attribute data of a user within a certain time period range, such as: income, occupation, race, age, marital, purchasing power, housing, etc.; meanwhile, artificial intelligence models are introduced, such as neural networks, decision trees and support vector machine learning data to construct decision models, and then other users are judged. The method can be successful in some fields and experimental environments, but a key hypothesis of the method is to master a large amount of basic information data of a user, and if the basic information data does not exist, a decision model is difficult to construct. For the power grid users, as the power grid enterprises are not government agencies or banks, much data (such as family income, age, housing, marital) are difficult to obtain and are collected without rights, and missing data directly causes the failure of the discovery process of the user power charge settlement risk by using the traditional method.
The typical geographical location characteristics of the power grid users exist in distribution, the location information is easily available for power grid enterprises, the approximate type of enterprises and the users are relatively centralized in the possible geographical area, and the economic and industrial influences on the enterprises and the users are relatively converged. Collecting statistics of these geographic locations may reflect the user's usage of power resources over an area, which also implies the user's economy and ability to pay. Therefore, a method can be constructed, the process of decision making and discovery is completed by introducing attribute data of geographic space positions and relations in similar groups, and the user electricity charge credit risk discovery is realized by using fewer attributes.
Disclosure of Invention
The invention provides a method for discovering the risk of clearing the electric charge of a user based on regional geographical position information, which organizes users with approximate clearing charge conditions in a certain geographical region range together by utilizing a consistency expansion operator and stores the users in a user clearing region table. And then calculating the clearing risk of a new user based on the distance between the new user and the list item in the clearing area table of the user, and realizing the discovery of the clearing risk of the electric charge of the user.
The invention relates to a user electricity charge credit clearing risk discovery method based on regional geographical location information, which comprises the following steps:
s1, inputting a power grid user owing condition list History containing geographic positions, inputting an initial calculation range L Dis and a maximum calculation range HDis, acquiring the number QNum of users in the History, and establishing a user owing region table QTable;
s101, inputting a power grid user arrearage condition list History containing geographic positions, wherein each item of the list is a structure body, and the structure body comprises the following fields:
HID: a user number;
HX: longitude coordinates of the geographic location of the user;
HY: latitude coordinates of the geographical position of the user;
HQF: whether the user owes 0 to indicate that the user does not owe the fee, and 1 to indicate that the user owes the fee;
s102, inputting an initial calculation range L Dis, L Dis is an integer number, and the default value is 10;
s103, the number QNum of users = the number of entries in the History;
s104, initializing a user delinquent region table QTable = empty table;
s105, initializing a table counter HCounter = 1;
s106, establishing a region structure QTableStruct, wherein the field content of the QTableStruct is as follows:
QID: the region structure body corresponds to a user number;
QHX: the regional structure corresponds to the longitude coordinate of the geographical position of the user;
QHY: the latitude coordinate of the geographical position of the user corresponding to the regional structure body;
and (3) QDis: the region structure body corresponds to a range value of the user participating in calculation;
QJ L, calculating the distance of the region structure corresponding to the user;
QPr: the arrearage percentage of the corresponding user of the regional structure body in a certain neighborhood range;
QCundu: the purity of the region structure body corresponding to the user in a certain neighborhood range;
s107, setting the value of the QTableStruct internal field,
QTableStruct.QID=History[HCounter]. HID，
QTableStruct.QHX=History[HCounter].HX,
QTableStruct.QHY=History[HCounter].HY,
QTableStruct.QDis=LDis,
QTableStruct.QJL=0,
QTableStruct.QPr=0，
QTableStruct.QCundu=0；
s108, adding QTableStruct into QTable;
s109, HCounter = HCounter +1, going to S110 if HCounter is greater than QNum, otherwise going to S106
S110, ending the process;
s2, establishing a region consistency calculation operator ConsisOperator, wherein the operator inputs consistency integer number variable ConsisPos and outputs consistency result structure ConsisOperatorResult;
s201, a consistency calculation operator first temporary storage variable TS1= QTable [ ConsisPos ];
s202, establishing a spatial neighborhood list consissneighbor = empty list;
s203, a consistency calculation operator counter consishhcounter = 1;
s204, a consistency calculation operator second temporary storage variable TS2= QTable [ ConsisHCounter ];
s205, establishing a spatially adjacent structure ConsissStruct, wherein the fields of the structure are as follows:
ConsisDis: a distance corresponding to an adjacent structure;
ConsisQF, the arrearage condition corresponding to the adjacent structure;
s206, calculating the value of consisstruc.
S207, consissstruct. consissqf = History [ consisshcounter ]. HQF, consissstruct was added to consissneighbor;
s208, consisshcounter = consisshcounter +1, going to S209 if consisshcounter is greater than QNum, otherwise going to S204;
s209, sorting the list contents of the ConsisNeighbor from small to large based on the value of ConsisDis;
s210, the consistency register counter ConsisTCounter =1, the consistency Sum value Sum =0,
the arrearage counter QFCounter =0,
a consistency temporal distance variable consisttempd 1= consissneighbor [ ts1.qdis ]. consissdis;
s211, calculating a consistency arrearage temporary storage variable ConsisTQF, wherein the calculation formula is as follows:
ConsisTQF=
s212, for Sum, by calculating the following formula:
s213, QFCounter = QFCounter +1 if ConsisNeighbor [ ConsisTCounter ]. ConsisQF equals 1
S214, ConsisTCounter = ConsisTCounter +1, going to S215 if ConsisTCounter is greater than ts1.qdis, otherwise going to S211;
s215, establishing a consistency result structure ConsisOperatorResult, wherein the structure comprises the following fields:
ConsistResult: consistency results the described consistency of the structure;
ConsistResultDis is the distance described by the consistency result structure;
ConsisQF: the proportion of the arrearages;
s216, setting the value of each field of ConsisOperatResult,
ConsisOperatorResult.ConsistResult=1-Sum/TS1.QDis；
ConsisOperatorResult.ConsistResultDis=ConsisTempD1；
ConsisOperatorResult.ConsisQF=QFCounter/TS1.QDis；
s217, outputting ConsisOperatorResult as the result of the operator;
s3, establishing a region consistency expansion operator ExpandPos, wherein the input of the operator is a consistency expansion operator processing item variable ExpandPos, and the calculation result of the operator is written into the ExpandPos item of QTable;
s301, establishing a region consistency expansion operator, namely, an expand operator, wherein the input of the operator is expand Pos;
s302, calculating and inputting ConsissPos = ExpandPos by using a result structure variable EConsStruct = of a consistency calculation operator to obtain a result ConsisOperatorResult and returning the result;
s303, if EConsStrect.ConsistResult > QTable [ ExpandPos ]. QCundu, go to S304, otherwise go to S308;
S304，QTable[ExpandPos].QCundu=EConsisStruct.ConsistResult；
S305，QTable[ExpandPos].QJL =EConsisStruct. ConsistResultDis；
S306，QTable[ExpandPos].QPr=EConsisStruct.ConsisQF；
S307，QTable[ExpandPos]. QDis= QTable[ExpandPos]. QDis+LDis；
s308, if QTable [ ExpandPos ]. QDis is greater than HDis, then go to S309, otherwise go to S302;
s309, finishing the calculation process of the operator;
s4, calculating all the entries of the QTable by using an ExpandOperator:
s401, entry counter ECounter = 1;
s402, computing by using an expand operator, wherein the operator inputs expand Pos = ECounter;
s403, ECounter = ECounter +1, if ECounter is greater than QNum, then go to S404, otherwise go to S402
S404, finishing the calculation process;
s5, inputting the longitude ZX and the latitude ZY of the geographical position of a user, and calculating the risk of clearing the electric charge by using QTable;
s501, a risk finding counter variable DCounter =1, a risk summing variable PSum =0, and a risk counter variable PCounter = 0;
S502，QDTemp=QTable[DCounter]；
s503, calculating a risk finding distance variable QD, wherein the calculation formula is as follows:
s504, go to 506 if QD > = qdtemp.qj L, otherwise go to S505;
S505，PSum=PSum+QDTemp.QPr,PCounter=PCounter+1；
s506, DCounter = DCounter +1, if DCounter is larger than QNum, turning to S507, otherwise, turning to S502;
S507，PSum=PSum/PCounter；
s508, if PSum >0.15, outputting to find that the user has the risk of clearing the electric charge, otherwise, outputting that the user does not have the risk of clearing the electric charge;
s509, the calculation process is ended.
The invention has the beneficial effects that:
the invention uses the consistency expansion operator to organize the users with similar defaulting expense condition in a certain geographic area range together and store the users in a user defaulting area table. And then calculating the clearing risk of a new user based on the distance between the new user and the list item in the clearing area table of the user, and realizing the discovery of the clearing risk of the electric charge of the user. By using the method and the device, the aims of introducing fewer geographical position attributes which are easy to collect and accurately discovering the risk of clearing the arrearage of the electric charge can be achieved under the condition of only inputting the position and the arrearage information of one group of users.
Detailed Description
The present invention is further illustrated by the following examples, which do not limit the present invention in any way, and any modifications or changes that can be easily made by a person skilled in the art to the present invention will fall within the scope of the claims of the present invention without departing from the technical solution of the present invention.
Example 1
The invention relates to a user electricity charge credit clearing risk discovery method based on regional geographical location information, which comprises the following steps:
s1, inputting a power grid user owing condition list History containing geographic positions, inputting an initial calculation range L Dis and a maximum calculation range HDis, acquiring the number QNum of users in the History, and establishing a user owing region table QTable;
s101, inputting a power grid user arrearage condition list History containing geographic positions, wherein each item of the list is a structure body, and the structure body comprises the following fields:
HID: a user number;
HX: longitude coordinates of the geographic location of the user;
HY: latitude coordinates of the geographical position of the user;
HQF: whether the user owes 0 to indicate that the user does not owe the fee, and 1 to indicate that the user owes the fee;
s102, inputting an initial calculation range L Dis, L Dis is an integer number, and the default value is 10;
s103, the number QNum of users = the number of entries in the History;
s104, initializing a user delinquent region table QTable = empty table;
s105, initializing a table counter HCounter = 1;
s106, establishing a region structure QTableStruct, wherein the field content of the QTableStruct is as follows:
QID: the region structure body corresponds to a user number;
QHX: the regional structure corresponds to the longitude coordinate of the geographical position of the user;
QHY: the latitude coordinate of the geographical position of the user corresponding to the regional structure body;
and (3) QDis: the region structure body corresponds to a range value of the user participating in calculation;
QJ L, calculating the distance of the region structure corresponding to the user;
QPr: the arrearage percentage of the corresponding user of the regional structure body in a certain neighborhood range;
QCundu: the purity of the region structure body corresponding to the user in a certain neighborhood range;
s107, setting the value of the QTableStruct internal field,
QTableStruct.QID=History[HCounter]. HID，
QTableStruct.QHX=History[HCounter].HX,
QTableStruct.QHY=History[HCounter].HY,
QTableStruct.QDis=LDis,
QTableStruct.QJL=0,
QTableStruct.QPr=0，
QTableStruct.QCundu=0；
s108, adding QTableStruct into QTable;
s109, HCounter = HCounter +1, going to S110 if HCounter is greater than QNum, otherwise going to S106
S110, ending the process;
s2, establishing a region consistency calculation operator ConsisOperator, wherein the operator inputs consistency integer number variable ConsisPos and outputs consistency result structure ConsisOperatorResult;
s201, a consistency calculation operator first temporary storage variable TS1= QTable [ ConsisPos ];
s202, establishing a spatial neighborhood list consissneighbor = empty list;
s203, a consistency calculation operator counter consishhcounter = 1;
s204, a consistency calculation operator second temporary storage variable TS2= QTable [ ConsisHCounter ];
s205, establishing a spatially adjacent structure ConsissStruct, wherein the fields of the structure are as follows:
ConsisDis: a distance corresponding to an adjacent structure;
ConsisQF, the arrearage condition corresponding to the adjacent structure;
s206, calculating the value of consisstruc.
S207, consissstruct. consissqf = History [ consisshcounter ]. HQF, consissstruct was added to consissneighbor;
s208, consisshcounter = consisshcounter +1, going to S209 if consisshcounter is greater than QNum, otherwise going to S204;
s209, sorting the list contents of the ConsisNeighbor from small to large based on the value of ConsisDis;
s210, the consistency register counter ConsisTCounter =1, the consistency Sum value Sum =0,
the arrearage counter QFCounter =0,
a consistency temporal distance variable consisttempd 1= consissneighbor [ ts1.qdis ]. consissdis;
s211, calculating a consistency arrearage temporary storage variable ConsisTQF, wherein the calculation formula is as follows:
ConsisTQF=
s212, for Sum, by calculating the following formula:
s213, QFCounter = QFCounter +1 if ConsisNeighbor [ ConsisTCounter ]. ConsisQF equals 1
S214, ConsisTCounter = ConsisTCounter +1, going to S215 if ConsisTCounter is greater than ts1.qdis, otherwise going to S211;
s215, establishing a consistency result structure ConsisOperatorResult, wherein the structure comprises the following fields:
ConsistResult: consistency results the described consistency of the structure;
ConsistResultDis is the distance described by the consistency result structure;
ConsisQF the arrearage ratio;
s216, setting the value of each field of ConsisOperatResult,
ConsisOperatorResult.ConsistResult=1-Sum/TS1.QDis；
ConsisOperatorResult.ConsistResultDis=ConsisTempD1；
ConsisOperatorResult.ConsisQF=QFCounter/TS1.QDis；
s217, outputting ConsisOperatorResult as the result of the operator;
s3, establishing a region consistency expansion operator ExpandPos, wherein the input of the operator is a consistency expansion operator processing item variable ExpandPos, and the calculation result of the operator is written into the ExpandPos item of QTable;
s301, establishing a region consistency expansion operator, namely, an expand operator, wherein the input of the operator is expand Pos;
s302, calculating and inputting ConsissPos = ExpandPos by using a result structure variable EConsStruct = of a consistency calculation operator to obtain a result ConsisOperatorResult and returning the result;
s303, if EConsStrect.ConsistResult > QTable [ ExpandPos ]. QCundu, go to S304, otherwise go to S308;
S304，QTable[ExpandPos].QCundu=EConsisStruct.ConsistResult；
S305，QTable[ExpandPos].QJL =EConsisStruct. ConsistResultDis；
S306，QTable[ExpandPos].QPr=EConsisStruct.ConsisQF；
S307，QTable[ExpandPos]. QDis= QTable[ExpandPos]. QDis+LDis；
s308, if QTable [ ExpandPos ]. QDis is greater than HDis, then go to S309, otherwise go to S302;
s309, finishing the calculation process of the operator;
s4, calculating all the entries of the QTable by using an ExpandOperator:
s401, entry counter ECounter = 1;
s402, computing by using an expand operator, wherein the operator inputs expand Pos = ECounter;
s403, ECounter = ECounter +1, if ECounter is greater than QNum, then go to S404, otherwise go to S402
S404, finishing the calculation process;
s5, inputting the longitude ZX and the latitude ZY of the geographical position of a user, and calculating the risk of clearing the electric charge by using QTable;
s501, a risk finding counter variable DCounter =1, a risk summing variable PSum =0, and a risk counter variable PCounter = 0;
S502，QDTemp=QTable[DCounter]；
s503, calculating a risk finding distance variable QD, wherein the calculation formula is as follows:
s504, go to 506 if QD > = qdtemp.qj L, otherwise go to S505;
S505，PSum=PSum+QDTemp.QPr,PCounter=PCounter+1；
s506, DCounter = DCounter +1, if DCounter is larger than QNum, turning to S507, otherwise, turning to S502;
S507，PSum=PSum/PCounter；
s508, if PSum >0.15, outputting to find that the user has the risk of clearing the electric charge, otherwise, outputting that the user does not have the risk of clearing the electric charge;
s509, the calculation process is ended.
Example 2
Taking the clearing of the electricity charge of a power grid user of a certain XXXX company as an example:
s1, inputting a power grid user arrearage condition list History containing the geographic position, wherein the table comprises the following contents:
| HID | HX | HY | HQF |
| 71001 | 126.351 | 43.882 | 1 |
| 81022 | 126.317 | 43.882 | 0 |
| 44020 | 126.376 | 43.871 | 0 |
| 35221 | 126.354 | 43.862 | 1 |
| 45214 | 126.343 | 43.833 | 1 |
| … |
inputting an initial calculation range L Dis =10 and a maximum calculation range HDis =200;
the number of users QNum =5021 in the History is acquired,
establishing a user clearing area table QTable, wherein the table comprises the following contents:
| QID | QHX | QHY | Qdis | QJL | QPr | QCundu |
| 71001 | 126.351 | 43.882 | 10 | 0 | 0 | 0 |
| 81022 | 126.317 | 43.882 | 10 | 0 | 0 | 0 |
| 44020 | 126.376 | 43.871 | 10 | 0 | 0 | 0 |
| 35221 | 126.354 | 43.862 | 10 | 0 | 0 | 0 |
| 45214 | 126.343 | 43.833 | 10 | 0 | 0 | 0 |
| … |
s2, establishing a region consistency degree calculation operator ConsisOperator, wherein the operator inputs consistency degree integer number variable ConsisPos and outputs consistency degree result structure ConsisOperatorResult
S3, establishing a region consistency expansion operator, namely, an expansion operator, wherein the input of the operator is a consistency expansion operator processing item variable, namely, expansion Pos, and the calculation result of the operator is written into the ExpandPos items of the QTable
S4, calculating all the items of QTable by utilizing the ExpandOperator
The content of the QTable after this step calculation becomes the following result:
| QID | QHX | QHY | Qdis | QJL | QPr | QCundu |
| 71001 | 126.351 | 43.882 | 100 | 0.14 | 0.06 | 1.352 |
| 81022 | 126.317 | 43.882 | 170 | 0.17 | 0.04 | 1.245 |
| 44020 | 126.376 | 43.871 | 130 | 0.17 | 0.04 | 1.670 |
| 35221 | 126.354 | 43.862 | 120 | 0.16 | 0.17 | 2.112 |
| 45214 | 126.343 | 43.833 | 130 | 0.13 | 0.04 | 2.332 |
| … |
s5, inputting the longitude ZX and the latitude ZY of the geographical position of a user, and calculating the risk of clearing the electric charge by using QTable
The longitude ZX =126.352 and the latitude ZY =43.871 of the user are input, PSum =0.17 is obtained, and the user is output that there is a risk of clearing the electricity charge.
The longitude ZX =126.362 and the latitude ZY =43.880 of the user are input, PSum =0.04 is obtained, and the user is output that there is no risk of clearing the electricity charge.
Example 3
In order to test and compare the effectiveness of the method, 2000 power grid users in a certain area are introduced as test data, the method is compared with the traditional decision tree and neural network method, and arrearages and position data of the power grid users are introduced; the decision tree and the neural network method introduce all possibly opened and collected data in the power grid user management system as data analysis attribute information. The comparative results are as follows:
| method of producing a composite material | Predicting the number of users with risk | User number with missed judgment risk and expense clearing condition |
| Method of the invention | 201 | 13 |
| Decision tree | 1302 | 240 |
| Neural net | 2520 | 179 |
The invention can be seen that the number of users with risks predicted by the invention is less, but the number of missed judgments is also less, which shows that the invention can be used for more effectively predicting the risk of clearing the user's electric charge, and has important practical value for the management of the power grid.
Claims (1)
1. A user electricity charge clearing risk discovery method based on regional geographical location information comprises the following steps:
s1, inputting a power grid user owing condition list History containing geographic positions, inputting an initial calculation range L Dis and a maximum calculation range HDis, acquiring the number QNum of users in the History, and establishing a user owing region table QTable;
s101, inputting a power grid user arrearage condition list History containing geographic positions, wherein each item of the list is a structure body, and the structure body comprises the following fields:
HID: a user number;
HX: longitude coordinates of the geographic location of the user;
HY: latitude coordinates of the geographical position of the user;
HQF: whether the user owes 0 to indicate that the user does not owe the fee, and 1 to indicate that the user owes the fee;
s102, inputting an initial calculation range L Dis, L Dis is an integer number, and the default value is 10;
s103, the number QNum of users = the number of entries in the History;
s104, initializing a user delinquent region table QTable = empty table;
s105, initializing a table counter HCounter = 1;
s106, establishing a region structure QTableStruct, wherein the field content of the QTableStruct is as follows:
QID: the region structure body corresponds to a user number;
QHX: the regional structure corresponds to the longitude coordinate of the geographical position of the user;
QHY: the latitude coordinate of the geographical position of the user corresponding to the regional structure body;
and (3) QDis: the region structure body corresponds to a range value of the user participating in calculation;
QJ L, calculating the distance of the region structure corresponding to the user;
QPr: the arrearage percentage of the corresponding user of the regional structure body in a certain neighborhood range;
QCundu: the purity of the region structure body corresponding to the user in a certain neighborhood range;
s107, setting the value of the QTableStruct internal field,
QTableStruct.QID=History[HCounter]. HID，
QTableStruct.QHX=History[HCounter].HX,
QTableStruct.QHY=History[HCounter].HY,
QTableStruct.QDis=LDis,
QTableStruct.QJL=0,
QTableStruct.QPr=0，
QTableStruct.QCundu=0；
s108, adding QTableStruct into QTable;
s109, HCounter = HCounter +1, going to S110 if HCounter is greater than QNum, otherwise going to S106
S110, ending the process;
s2, establishing a region consistency calculation operator ConsisOperator, wherein the operator inputs consistency integer number variable ConsisPos and outputs consistency result structure ConsisOperatorResult;
s201, a consistency calculation operator first temporary storage variable TS1= QTable [ ConsisPos ];
s202, establishing a spatial neighborhood list consissneighbor = empty list;
s203, a consistency calculation operator counter consishhcounter = 1;
s204, a consistency calculation operator second temporary storage variable TS2= QTable [ ConsisHCounter ];
s205, establishing a spatially adjacent structure ConsissStruct, wherein the fields of the structure are as follows:
ConsisDis: a distance corresponding to an adjacent structure;
ConsisQF, the arrearage condition corresponding to the adjacent structure;
s206, calculating the value of consisstruc.
S207, consissstruct. consissqf = History [ consisshcounter ]. HQF, consissstruct was added to consissneighbor;
s208, consisshcounter = consisshcounter +1, going to S209 if consisshcounter is greater than QNum, otherwise going to S204;
s209, sorting the list contents of the ConsisNeighbor from small to large based on the value of ConsisDis;
s210, the consistency register counter ConsisTCounter =1, the consistency Sum value Sum =0,
the arrearage counter QFCounter =0,
a consistency temporal distance variable consisttempd 1= consissneighbor [ ts1.qdis ]. consissdis;
s211, calculating a consistency arrearage temporary storage variable ConsisTQF, wherein the calculation formula is as follows:
ConsisTQF=
s212, for Sum, by calculating the following formula:
s213, QFCounter = QFCounter +1 if ConsisNeighbor [ ConsisTCounter ]. ConsisQF equals 1
S214, ConsisTCounter = ConsisTCounter +1, going to S215 if ConsisTCounter is greater than ts1.qdis, otherwise going to S211;
s215, establishing a consistency result structure ConsisOperatorResult, wherein the structure comprises the following fields:
ConsistResult: consistency results the described consistency of the structure;
ConsistResultDis is the distance described by the consistency result structure;
ConsisQF the arrearage ratio;
s216, setting the value of each field of ConsisOperatResult,
ConsisOperatorResult.ConsistResult=1-Sum/TS1.QDis；
ConsisOperatorResult.ConsistResultDis=ConsisTempD1；
ConsisOperatorResult.ConsisQF=QFCounter/TS1.QDis；
s217, outputting ConsisOperatorResult as the result of the operator;
s3, establishing a region consistency expansion operator ExpandPos, wherein the input of the operator is a consistency expansion operator processing item variable ExpandPos, and the calculation result of the operator is written into the ExpandPos item of QTable;
s301, establishing a region consistency expansion operator, namely, an expand operator, wherein the input of the operator is expand Pos;
s302, calculating and inputting ConsissPos = ExpandPos by using a result structure variable EConsStruct = of a consistency calculation operator to obtain a result ConsisOperatorResult and returning the result;
s303, if EConsStrect.ConsistResult > QTable [ ExpandPos ]. QCundu, go to S304, otherwise go to S308;
S304，QTable[ExpandPos].QCundu=EConsisStruct.ConsistResult；
S305，QTable[ExpandPos].QJL =EConsisStruct. ConsistResultDis；
S306，QTable[ExpandPos].QPr=EConsisStruct.ConsisQF；
S307，QTable[ExpandPos]. QDis= QTable[ExpandPos]. QDis+LDis；
s308, if QTable [ ExpandPos ]. QDis is greater than HDis, then go to S309, otherwise go to S302;
s309, finishing the calculation process of the operator;
s4, calculating all the entries of the QTable by using an ExpandOperator:
s401, entry counter ECounter = 1;
s402, computing by using an expand operator, wherein the operator inputs expand Pos = ECounter;
s403, ECounter = ECounter +1, if ECounter is greater than QNum, then go to S404, otherwise go to S402
S404, finishing the calculation process;
s5, inputting the longitude ZX and the latitude ZY of the geographical position of a user, and calculating the risk of clearing the electric charge by using QTable;
s501, a risk finding counter variable DCounter =1, a risk summing variable PSum =0, and a risk counter variable PCounter = 0;
S502，QDTemp=QTable[DCounter]；
s503, calculating a risk finding distance variable QD, wherein the calculation formula is as follows:
s504, go to 506 if QD > = qdtemp.qj L, otherwise go to S505;
S505，PSum=PSum+QDTemp.QPr,PCounter=PCounter+1；
s506, DCounter = DCounter +1, if DCounter is larger than QNum, turning to S507, otherwise, turning to S502;
S507，PSum=PSum/PCounter；
s508, if PSum >0.15, outputting to find that the user has the risk of clearing the electric charge, otherwise, outputting that the user does not have the risk of clearing the electric charge;
s509, the calculation process is ended.
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