CN110490352A - A kind of urban education service facility evaluation optimization method - Google Patents
A kind of urban education service facility evaluation optimization method Download PDFInfo
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Abstract
The present invention provides a kind of urban education service facility evaluation optimization method, basic data and traffic big data including the geographical national conditions element of extraction are simultaneously integrated, calculate the basic evaluation index system for determining urban education service facility, it carries out service ability analysis, approachability analysis and education equalization analysis, various dimensions quantitative measure educational alternative and supplies degree；Based on traffic big data, education services facility blind area is identified according to school in city and community's distribution situation；Using concordance rate index, school's space advantage degree index, unserviceable area, school district service scale, service population quantity and the feature size of population come overall merit school district scribing reasonability；Based on blind area and traffic big data, school's situation of all cell ownership, distributes the school of planning unit subordinate rationally according to majority principle in planning unit.The present invention can carry out Assessment and prediction to the status that the education services in city configure, and propose configuration scheme.
Description
Technical field
The present invention relates to the education in urban facilities Assessment optimization field more particularly to city public services facility
The evaluation optimization method of service facility.
Background technique
Education services facility includes space, environment required for educational work and related education and instruction equipment, is city
Important a part in city's service facilities.To make educational alternative preferably serve the public, the evaluation of education services facility
It is pith in URBAN PLANNING STUDY with distributing rationally, is conducive to the level for analyzing existing education services facility, and be new
Planning provide auxiliary and reference.The evaluation of education services facility and distribute rationally and not only need to investigate quantity, quality, also with ground
It is closely bound up to manage spatial information, is the combination of thematic information and spatial information, evaluation index is for reflecting education services facility
Single statistics is horizontal and reasonability spatially, suitability and cheap degree.Since it is with stronger spatial dependence,
And need to be quantified from stage construction multi-angle, the evaluation and optimization of education services facility are geographical space problem and city
Hot issue in planning.
Geographical spatial data and associated thematic data are the valuable data source of programmed decision-making analysis, but the education of early stage
Service facility evaluates the statistical analysis for often pertaining only to thematic information, lacks the thinking to geographical Spatial Dimension.It is taken about education
Be engaged in facility evaluation be mostly individual facilities scale, reflect the quantitative index of individual facilities, such as occupied area, teacher, per capita
Area etc..This kind of special topic statistical information is more and mixed and disorderly, it is difficult to and the service level of combined reaction educational alternative lacks spatial information,
And it cannot reflect the convenience degree of educational administration's facility from global.Classification grade scale, energy are established thereafter through to statistical information
The problem of enough reflecting the quality of education services facility in regional scale, but not being regarded as space statistics yet.As geography is believed
The development of breath technology, the theory and method of GIS is more and more used in the research of urban planning, in education services facility
Spatial information gradually incorporate in evaluation index, but evaluate angle it is single, not enough diversification and stratification, it is difficult to formed perfect
Assessment indicator system.Therefore, urgently there is the technical solution of Practical significance to occur for this field.
Summary of the invention
The present invention mainly solves the problems, such as existing, provides the education services facility in a kind of city public services facility
Evaluate optimization method.
Technical solution of the present invention provides a kind of urban education service facility evaluation optimization method, includes the following steps:
Step 1, it extracts the basic data of geographical national conditions element and traffic big data and is integrated, the basic data
Including community data, school's data, school district data and statistic unit thematic data；
Step 2, calculate determine urban education service facility basic evaluation index system, carry out service ability analysis, can
Equalization analysis is analyzed and educated up to property, and various dimensions quantitative measure educational alternative supplies degree；
Step 3, it is based on traffic big data, it is blind according to school in city and community's distribution situation identification education services facility
Area；
Step 4, the basic evaluation index system calculated based on step 2, is referred to using concordance rate index, school's space advantage degree
Mark, unserviceable area, school district service scale, service population quantity and the feature size of population carry out overall merit school district scribing reasonability；
Step 5, the blind area obtained based on step 3 and traffic big data, school's feelings of all cells ownership in planning unit
Condition distributes the school of planning unit subordinate rationally according to majority principle.
Moreover, in the step 1, when integral data, unified standard processing is first carried out, is then registrated, is arranged
Consistent georeferencing coordinate.
Moreover, identifying data source traffic big data provided by internet of blind area in the step 3.
Moreover, the evaluation rational process of school district scribing includes following sub-step in the step 4,
Step 4.1. input calculates data, including range data, cell data, school's data and school district data '
Step 4.2. initializes parameters, total cell number including counting each school district obtains by reading input data
In school district each cell distance most from school ID1 and they with a distance from, obtain school ID2 as defined in current area, statistics
The total number of people that area receives an education；
The total distance value of step 4.3. statistics in-zone cell school, it is whether consistent with ID2 to judge ID1, if unanimously, increasing
Into the statistics of the concordance rate index of school district, if inconsistent, judge whether cell is less than threshold distance to school's minimum distance.
School district is increased by the statistical value of service children's number and cell number if being less than；
Step 4.4. calculates school district concordance rate index according to above-mentioned statistical result, calculates school district and corresponds to school's serving cell
Average distance, calculate school's space advantage degree index；
Step 4.5. loop iteration exports result after every evaluation index of all school districts calculates.
Moreover, being met the school district of " entering a school nearest to one's home " when evaluating reasonability using Voronoi diagram in the step 4
It divides, carries out overall merit with existing school district, provide decision for the analysis of further school district Partitioning optimization and school's Optimizing Site Selection
It supports and suggests.
Moreover, the process that educational alternative is distributed rationally includes following sub-step in the step 5.
Step 5.1, input calculates data, including cell table, school's table and cell school relation database table.
Step 5.2, by reading input data, cell school table is arranged by the descending of association score, whether judges school
Have and reaches maximum number of students；
If it is not, first selection is classified as 0 row in selection cell table, distance is obtained in cell number and school's cell table most
Close row, is added new school's cell table, and label selection is classified as 2；
If so, finding out the item that selection in school's cell table of corresponding school is classified as 0, obtains school's number and cell is compiled
Number, marking the options of the row is 1, and judges whether to reach maximum number of students, and the selective value for not up to then setting cell table is 1,
The number of student for setting school's table is the sum of the value of current value and cell number of students, otherwise searches other not up to maximum numbers of students
School continues to judge.
Step 5.3, configuration result is exported.
Evaluation optimization method provided by the invention covers existing using single education services facility as point of research object
Evaluation index is analysed, this external enwergy compensates in previous evaluation index from the level of large scale overall merit Regional Education service facility
Problem is ignored to spatial information, the geospatial information of facility is integrated into service ability, more can comprehensively reflect city
The convenience of city's education services facility, and facility configuration strategy is provided using Optimized model automation, it is not necessarily to manual analysis institute
The manpower and material resources needed, the analysis result of model facilitate the formulation of urban development planning strategy.
Detailed description of the invention
Fig. 1 is service ability of embodiment of the present invention analysis flow chart diagram.
Fig. 2 is approachability analysis of embodiment of the present invention flow chart.
Fig. 3 is equalization of embodiment of the present invention analysis flow chart diagram.
Fig. 4 is that school district of the embodiment of the present invention divides analysis on its rationality flow chart.
Fig. 5 is that the facility of the embodiment of the present invention distributes analysis flow chart diagram rationally.
Specific embodiment
Technical solution for a better understanding of the present invention with reference to the accompanying drawings and examples does further the present invention
It is described in detail.
The present invention makes full use of existing spatial geography data and space thematic data, and realization is commented towards public service status
Estimate, the analysis and evaluation system of fundamental analysis model is covered in research and development, provides scientific reference for government decision, fine administer.Model with
Based on geographical national conditions information, in conjunction with thematic data, traffic big data, educational alternative equalization Comprehensive Analysis Model of Unit is constructed.Mould
Type takes school eduaction establishment type, walking property of cell space type, population differentiated demand and scale effect into account, from service energy
The equalization degree of the various dimensions quantitative measure educational alternatives such as power, accessibility, equalization, school district scribing reasonability supply, identification
Current school district urgently improves region under dividing, disclose present education resource provision and space configuration there are the problem of, and to future
School district planning optimizes addressing.
A kind of urban education service facility evaluation Optimal Design method provided in an embodiment of the present invention include step such as
Under:
Step 1 extracts basic data (community data, school's data, the school district data, statistic unit of geographical national conditions element
Thematic data) and traffic big data and integrated；
The basic data of geographical national conditions element can be obtained by geographical national conditions findings of the survey.Integral data refers to geographical national conditions
The various basic datas and traffic big data of element are the data in a variety of sources, different-format, to be carried out to these spatial datas
Unified standardization processing, is then registrated these spatial datas, consistent georeferencing coordinate is arranged.
Step 2 calculates and determines urban education service facility assessment indicator system, is modeled and (proposes service in embodiment
Capacity Analysis Model, approachability analysis model and equalization analysis), different processing units are selected according to different indexs, are calculated each
Item base values, model take school eduaction establishment type, walking property of cell space type, population differentiated demand and scale effect into account
It answers, supplies degree from the various dimensions quantitative measure educational alternative such as service ability, accessibility, equalization.
Explanation is realized in service ability, accessibility, the equalization analysis for providing embodiment further below.
1. service ability is analyzed
Based on accessibility fair evaluation be considered as school eduaction facility space distribution social benefit, choose with
Effective service area of the 500 meters of walking ranges of national regulation as primary school, and be based on service coverage rate, enjoy educational alternative per capita
The indexs such as quantity, feature population accounting carry out service ability evaluation.
Index explanation:
(1) coverage rate is serviced
Service coverage rate refers to that the number of cells covered in the effective service range of primary school accounts for the total cell number of survey region
The ratio of amount, for understanding the difference of service level between the efficiency and evaluation unit that primary school education facility covers, calculation formula
See (Eq.1).Coverage rate is bigger, shows that educational alternative space layout is more balanced, and area of being benefited is wider, and population of being benefited is more.
Wherein, C indicates service coverage rate；∑ PA indicates all total cell numbers of the effective service range of primary school in survey region
Amount；A indicates the total number of cells of survey region.Quantity service coverage rate in residential quarter is chosen in this research as effective space
Service coverage rate index.
(2) educational alternative quantity is enjoyed per capita
Facility quantity is enjoyed per capita and measures the practical potentiality for enjoying primary school education facility resource of resident, and evaluation facility is actual
Service level and the degree of crowding, calculation formula are shown in (Eq.2)
Wherein, PNiExpression residential area i (the facility quantity that residential quarter point i) is enjoyed per capita, m indicate the number in residential area,
NiIndicate the facility quantity in residential area i raying coverage；PiIndicate the total population of residential area i.In our current research, it chooses
The feature population that children service as primary school, statisticallys analyze in effective service range that (children) enjoy primary school education per capita respectively
Facility quantity.
(3) feature population accounting
Wherein, C indicates that the children's quantity covered in the effective service range of primary school accounts for the ratio of the total children's quantity of survey region
Example；∑ PA indicates children's quantity of the cell in survey region in the effective service range of primary school；A indicates the total youngster of survey region
Virgin number.The education services coverage rate of children is chosen in this research as effective feature population accounting index.
The flow chart that service ability is analyzed in embodiment is as shown in Figure 1:
Step 1. calculates data, respectively range data, cell data, school's data according to model calculation demand, input
And street data；Distance threshold S is set, determines the attribute field in input data for calculating.Finger can be passed through when specific implementation
Path input data and output are determined as a result, for example providing the path school's data (* .shp), the path, traffic cell data (* .shp)
The range data path (* .shp) and the path output file (* .html).
Step 2. is by reading input data, initialization parameters, including following sub-step:
Step 2.1. initializes street index value i=0；
The initial cell step 2.2. indexes m=0, total number of cells tNum=0 of street i, by serving cell csNum=
0, by service children's number schild=0, total children's number tchild=0；
Step 2.3. obtains the cell m of street i from school minimum range D, children number childnum according to range data,
Initial cell m enjoys facility quantity facnum=0；
Minimum range D of the step 3. according to cell each in street from school, judges whether the distance is less than distance threshold S.
If being less than, count in street in the cell number for facilities services of receiving an education, the education services facility statistical number enjoyed in street
Also increase with the statistics by service number.Even cell m enjoys facility quantity by serving cell csNum=csNum+1
Facnum=facnum+1, by service children's number schild=schild+childnum.Otherwise step 4.2. is carried out.
Step 4. calculates facility number, the street service covering that cell is enjoyed per capita according to every statistical data, according to formula
Feature population accounting in rate, street, including following sub-step:
Step 4.1. calculates the facility quantity pn=facnum/peonum that cell m people enjoys；
Step 4.2. enables total number of cells tNum=tNum+1 of street i, total children's number tchild=tchild+
childnum；
Does step 4.3. judge whether that all cells of street i have been calculated if otherwise enabling cell index m=m+1, it is back to step
2.3, if then calculating street service coverage rate csNum/tNum, calculates in street and enjoy all cells of educational alternative quantity per capita
(children) enjoy the average value of primary school education facility quantity (pn) per capita, calculate feature population accounting schild/ in street
Tchild, and enter step 4.4；
Step 4.4. judges whether that all streets have been calculated, if otherwise enabling street index i=i+1, return step 2.2, if
It is that index calculating terminates.
Step 5. increases to the index result of calculating in the attribute list of street, is output in specified file.
2. approachability analysis
Utilize accessibility Distance evaluation cell to the accessibility of counterpart school.Based on actual traffic data, according to each inhabitation
Cell corresponds to the walking distance of school under pedestrian traffic mode to it, judges whether to meet the standard of entering a school nearest to one's home.
The flow chart of approachability analysis is as shown in Figure 2 in embodiment:
Step 1. calculates data, including range data, cell data and school district data according to model calculation demand, input,
Distance threshold S is set, determines the attribute field in input data for calculating.When specific implementation number can be inputted by specified path
According to output as a result, for example providing the path cell data (* .shp), the traffic range data path (* .shp) and output file (*
.html) path.
Step 2. initializes parameters, including following sub-step:
Step 2.1. initializes street and indexes i=0；
The initial cell step 2.2. indexes m=0；
Step 2.3. obtains the cell m of street i from school minimum range D, whether initial cell is blind according to range data
Area field isblind=0；
Step 3. judges the distance according to minimum range D of each cell from school in the street of range data statistics acquisition
Whether blind area distance threshold S, including following sub-step are less than:
Step 3.1. judges whether distance D is less than blind area distance threshold S, if being less than, education services facility is blind in street
The statistical data in area increases, enable cell whether blind area field isblind=1, subsequently into step 3.2；Otherwise it is directly entered step
Rapid 3.2；
Does step 3.2. judge whether that all cells of street i have been calculated if it is not, enabling cell index m=m+1, return step
2.3；If then entering step 3.3；
Step 3.3. judges whether that all streets have been calculated, if it is not, street index i=i+1 is enabled, return step 2.2, if
Then index calculating terminates；
Step 4. exports a new cell shapefile file, and the accessibility index calculated (blind area statistics) is tied
Fruit increases in the attribute information of each cell, is output in specified file.
3. equalization is analyzed
Primary school education equalization analysis model is established, by the fair for the educational resource that overall merit resident enjoys,
Single-point is assessed from multi-angles such as the teacher resource quality of school establishment, primary school, school position, accessibility and service population features
School composite preponderance.And the population characteristic of school district internal services is combined, further identify that educational alternative supply is relatively weak, resource
Configuration urgently optimizes and lifting region.
Primary school is constructed using schoolman's resource assessment, school's evaluating models, school's Bearing Capacity Evaluation and accessibility index
Educational alternative composite preponderance evaluation index.The composite preponderance index of each street scale primary school is that each primary school education is set in region
The interior average value for the composite preponderance applied.
Dominance score based on street is coupled with urban economy system (the horizontal construction land rate in street), passes through two
Performance fairness of the coupled relation evaluation urban education public service facility of system under administrative street scale.
Index explanation:
(1) schoolman's resource assessment
Including teacher's number, teacher, high academic title the indexs such as leads and asks flat after the normalization of all field datas in teacher
Mean value.
Normalize formula:
X0For primary data, XmaxFor maximum value, XminMinimum value, X are data after normalization.
(2) school's evaluating models
Whether school's position noise figure, minimum distance of the school apart from major trunk roads, ground rail traffic meet " middle and primary schools
Design specification " specified in 80 meters or more, be set as 1, be otherwise 0；
(3) school's Bearing Capacity Evaluation
School's size of the student body index: averagely possess including existing student's quantity, estimated enrollment quantity, school's area, student
The indexs such as school's area are averaged after all field data normalization (formula is same as above).
(4) accessibility index
The average value of each practical road network walking distance of cell, data normalization in each school to its school district.
(5) overlapping index
The composite preponderance index of single-point primary school, the primary school of each administrative area (street scale) are calculated in conjunction with index (1)~(4)
The composite preponderance of educational alternative is the average value of the composite preponderance of all schools in the region.Then it calculates and is based on administrative area
The dominance score drawn and urban economy system (construction land accounting under administrative division level) overlapping index are by two
Performance fairness of the coupled relation evaluation urban education public service facility of system under administrative division scale.
The degree of coupling C calculation formula of index A and index B are as follows:
The degree of coupling between educational development and economic development system refers to when educational development and economic development are in certain level
Under the conditions of when, the degree of development level between the two coupling.Coupling angle value more levels off to 1, then the coupling degree between system is got over
Greatly, it indicates to reach between educational development and economic development and effectively couples coordinated development level, system tends to orderly coordination
Development., whereas if coupling angle value more levels off to 0, then the coupling degree between system is smaller, educational development and economic development system
Don't care state is between system, system tends to development disorder.According to difference section locating for system coupling degree value, divide
3 different coupling degree grades: the coupling of coordination type, the coupling of adjustment type, low-level coupling.
The flow chart that equalization is analyzed in embodiment is as shown in Figure 3:
For step 1. according to model calculation demand, input calculates data, including range data, cell data, school's data,
Area's data, road net data and street data determine the attribute field in input data for calculating.Finger can be passed through when specific implementation
Path input data and output are determined as a result, for example providing the path school's data (* .shp), the path, traffic cell data (* .shp)
The path road net data (* .shp), traffic range data (* .shp), street data (* .shp) path, path and output file
The path (* .html).
Step 2. indexes i=0, obtains student's quantity, the school of each school by reading input data, initialization school district
Area, classroom number, the statistical data such as high academic title's number in teacher.Including following sub-step:
High academic title leads, student averagely has the indexs such as school's area in step 2.1. calculating teacher, teacher.According to formula,
Academic title high in classroom number, teacher, teacher is led index to normalize and average, classroom's resource assessment is obtained and refers to
Mark；
Student's quantity, school's area, student are averagely possessed the normalization of school's area index by step 2.2., are averaged,
Obtain school's Bearing Capacity Evaluation index.
Step 3. is made comparisons by the nearest space length of calculating school and road network with distance threshold.Distance in embodiment
Does is threshold value set as 80, judges school away from road network 80m or more if more than threshold value, then school position is evaluated as 1, is otherwise 0.
Step 4. obtains minimum distance of each cell from school in school district according to range data, and statistics school district cell is total
Number obtains school's accessibility index, and normalize by calculating the average value of distance in each school district.Including following sub-step:
Step 4.1. initialization, including cell index m=0 is enabled, school district cell sum tNum=0, walking total distance tDis
=0；
Step 4.2. obtains the cell m of school district i from school minimum range D according to range data；
Step 4.3. enables school cell sum tNum=tNum+1, walking total distance tDis=tDis+D；
Does step 4.4. judge whether that all cells of school district i have been calculated if it is not, then enabling cell index m=m+1, return step
4.2, school's accessibility index tDis/tNum is otherwise calculated, and normalize, subsequently into step 4.5；
Does step 4.5. judge whether that all educational alternative points have been calculated if it is not, school district is then enabled to index i=i+1, return step
4.1, if then entering step 5；
Step 5. calculates the evaluation of school's teacher resource, school's evaluating models, four school's Bearing Capacity Evaluation, accessibility indexs
Average value A calculate the construction land ratio value B in each street in conjunction with street architecture area and the gross area.It is counted with A, B value
Calculate overlapping index C.
Step 6. exports primary school's point .shp according to calculated result, increases schoolman's resource assessment (faculty), school newly
Evaluating models (location), school's Bearing Capacity Evaluation (capacity), 4 fields of school's accessibility index (access) and
Street overlapping index codegree is exported, is respectively outputted in specified file.
Step 3 is based on traffic big data, education services facility is identified according to school in city and community's distribution situation
Blind area.
Identify data source traffic big data provided by internet of blind area.
It can be divided according to existing school district on the basis of the accessibility measure of step 2, identify that educational alternative can in existing school district
Up to blind area.If distance of embodiment proposition cell to its correspondence school is more than 500 meters, then it is assumed that the cell belongs to existing school district
Blind area under planning.
Step 4 utilizes concordance rate index, school's space advantage degree based on the basic evaluation index system that step 2 calculates
It is reasonable that index, unserviceable area, school district service scale, service population quantity and the feature size of population carry out the scribing of overall merit school district
Property.
Embodiment is based on the above analysis as a result, further establishing school district scribing analysis on its rationality model, and exploration and analysis is existing
The division reasonability of school district is divided using the school district that Voronoi diagram is met " entering a school nearest to one's home ", is integrated with existing school district
Evaluation provides decision support and suggestion for the analysis of further elementary education district Partitioning optimization and school's Optimizing Site Selection.
Selecting index and explanation:
(1) concordance rate index
By based on specification divide lower cell correspond to school district and based on the school district under traffic data and Voronoi diagram division into
Row comparison, calculates the quantitatively evaluating index of concordance rate.Will the corresponding school of each cell be compared, if handed over based on practical
It is identical that the school district of logical distance divides and specification school district divides, then is assigned a value of 1, is otherwise 0；It is sought on the scale of school district average
Value, it is more reasonable (having taken into account existing zoning and reach distance) closer to 1 configuration, inside school district can be evaluated accordingly
It is optimal whether area's distribution reaches accessibility simultaneously.
(2) school's space advantage degree index
Calculate separately specification school district and the in-zone cell based on traffic data and Voronoi diagram division to counterpart school
Average traffic distance calculates the space advantage of its accessibility, and the score P:P=1/ (i of the accessibility of each school is calculated by counting backward technique
Primary school's average distance/all primary schools average distance minimum value) * 100, score section is 1~100.Score is higher, represents school
Space advantage degree is higher, then the accessibility for corresponding to resident's admission is also relatively preferable.
(3) school district service scale, service population quantity and the feature size of population.
The index of correlation within the scope of school district is corresponded to school to evaluate service of the school in its existing school district division range
Ability: the i.e. cell sum (cell of reachable corresponding school in 500 meters of traffic distance) of school's service, the population of service
And children's population.
(4) service range external zones
Under cognometrics Division, the practical walking distance of each cell to counterpart primary school.And with reference to corresponding specification, identify small
" external zones " outside 500 meters of effective service ranges is learned, resource, but accessibility are gone to school by although primary school that counterpart is enjoyed in these regions
It is relatively weak, it is the region for urgently optimizing improvement in future plan.
The flow chart of embodiment middle school Division analysis on its rationality is as shown in Figure 4:
For step 1. according to model calculation demand, input calculates data, including range data, cell data, school's data and
School district data determine the attribute field in input data for calculating.When specific implementation can by specified path input data and
Output divides the path data (* .shp), the path cell data (* .shp), traffic range data (* as a result, for example providing school district
) and the path output file (* .html) .shp.
Step 2. initializes parameters by reading input data.Including following sub-step:
Step 2.1. initialization, enables school district index i=0；
The initial cell step 2.2. indexes m=0, total number of cells tNum=0 of school district i, by service children's sum
Tchild=0, total population tPeo, concordance rate total value tsem=0, total distance tDis=0；
Step 2.3. counts total cell number of each school district, obtain each cell distance in school district most from school ID1 and he
Distance, obtain school ID2 as defined in current area, the statistics total number of people Peo that receives an education of school district, children's number
childnum。
The total distance value of step 3. statistics in-zone cell school.Including following sub-step:
Whether step 3.1. judges ID1 consistent with ID2, if unanimously, increasing in the statistics of concordance rate index of school district, i.e.,
Enable concordance rate total value tsem=tsem+1；
Step 3.2. judges whether cell is less than threshold distance S to school minimum distance cDis.School district is taken if being less than
The statistical value of business children's number and cell number increases, even by service children's sum tchild=tchild+childnum, school district i
Total number of cells tNum=tNum+1, total population tPeo=tPeo+Peo, total distance tDis=tDis+cdis, subsequently into
Step 3.3；Otherwise it is directly entered step 3.3.
Does step 3.3. judge whether that all cells of school district i have been calculated if it is not, enabling then cell index m=m+1, return step
2.3；If then entering step 4；
Step 4. calculates school district concordance rate index according to above-mentioned statistical result and calculation formula, calculates school district and corresponds to school
The average distance of serving cell calculates school's space advantage degree index.Including following sub-step:
Step 4.1. calculates school district concordance rate index a1=tsem/tNum, calculates school district and corresponds to the flat of primary school's serving cell
Distance pDis=tDis/tNum is calculated school's space advantage degree index a2=1/ (pDis/mindis), and wherein mindis is
All primary school's average distance minimum values；
Does step 4.2. judge whether that all school districts have been calculated if it is not, school district index i=i+1 is then enabled, return step 2.2, if
It is that then index calculating terminates；
Step 5. exports school district .shp into specified file according to calculated result, increase concordance rate index (samerate),
School's space advantage degree index (adv), the cell total (comsernum) of school's service, the cell sum in school district
(comnum), children's size of population (childsum) index is serviced.
Step 5, the blind area obtained based on step 3 and traffic big data, school's feelings of all cells ownership in planning unit
Condition, according to the school of majority principle configuring unit subordinate.
When optimizing to elementary education district, it is considered as primary school's situation of all cell ownership in planning unit, according to majority
The primary school of principle configuring unit subordinate.Since under the policy of compulsory education, the teenager of each cell and children must be selected
Corresponding primary school.Therefore in foundation " cell-primary school " this incidence relation, it is necessary to consider the maximum capacity of educational alternative.
The purpose distributed rationally is that more balanced teacher is guided during reconfiguring school district.In order to guarantee school
That distributes is relatively scientific, it is contemplated that distributing to preferable school apart from nearest cell in research, when the most university of school
Corresponding cell no longer just is distributed for this school when raw number reaches the upper limit, is accommodated when all schools all have reached the maximum student
When amount, the cell consideration of still unassigned school at this time is gone to school nearby.
Embodiment proposes that the flow chart of facility Optimal Allocation Model is as shown in Figure 5:
Step 1. calculates data, including cell table, school's table and cell school relationship number according to model calculation demand, input
According to table.When specific implementation the road calibration data (* .xls) can be learned as a result, for example providing by specified path input data and output
Diameter, cell table data (* .xls), the school district cell relations table data path (* .xls) and the path output file (* .html).
Step 2. initialization, the train value that selects including setting in cell school relation table is 0, the existing number of students in primary school's table
It is 0, if reaching maximum number of students is 0；Selection in cell table is classified as 0.
Step 3. arranges cell school table by the descending of association score by the input data read.According in primary school's table
Existing number of students, judge whether school has and reach maximum number of students.If it is not, step 3.1 is then carried out, if so, carrying out step
3.2。
Step 3.1. judges that cell table is classified as 0 row with the presence or absence of selection, if otherwise process terminates, if selecting cell
First selection is classified as 0 row in table, obtains the row that distance is nearest in cell number and school's cell table, it is small that new school is added
Area's table, label select to be classified as 2 (be revised as the value not for 0, it is right when all schools all have reached the maximum student's saturation
Gone to school nearby in the cell consideration of still unassigned school at this time), it then successively handles next selection in cell table and is classified as 0
Row terminates to calculate, enters step 5 until being disposed.
Step 3.2. finds out the item that selection in school's cell table of corresponding school is classified as 0, obtains school's number and cell is compiled
Number, marking the options of the row is 1, and judges whether to reach whether maximum number of students (" reaches maximum in i.e. corresponding primary school's table
Number of students " column value be 1),
Not up to then enter step 4；
Otherwise return step 3.2 continue to search the school of other not up to maximum numbers of students, are judged.
Step 4；The selective value for setting cell table is 1, and the existing number of student for setting school's table is current value and cell number of students
The sum of value, judge whether to reach maximum number of student again, if then marking what school's table corresponded to the row " whether to reach maximum
Number of students " is classified as 1, return step 3, if otherwise direct return step 3.2.
Step 5. optimizes school and distributes Excel file with the cell postponed, including small according to calculated result
Area ID (CID) and optimization after its corresponding primary school ID (SID), be output in the file of formulation.
When it is implemented, software technology, which can be used, in process of the present invention realizes automatic running.The device of the invention is executed also to answer
When within the scope of the present invention.
Specific embodiment described herein is only an example for the spirit of the invention.The neck of technology belonging to the present invention
The technical staff in domain can make various modifications or additions to the described embodiments or replace by a similar method
Generation.
Claims (6)
1. a kind of urban education service facility evaluates optimization method, which comprises the steps of:
Step 1, it extracts the basic data of geographical national conditions element and traffic big data and is integrated, the basic data includes
Community data, school's data, school district data and statistic unit thematic data；
Step 2, the basic evaluation index system for determining urban education service facility is calculated, service ability analysis, accessibility are carried out
Analysis and education equalization analysis, various dimensions quantitative measure educational alternative supply degree；
Step 3, it is based on traffic big data, education services facility blind area is identified according to school in city and community's distribution situation；
Step 4, based on step 2 calculate basic evaluation index system, using concordance rate index, school's space advantage degree index,
Unserviceable area, school district service scale, service population quantity and the feature size of population carry out overall merit school district scribing reasonability；
Step 5, the blind area obtained based on step 3 and traffic big data, school's situation of all cells ownership, is pressed in planning unit
Distribute the school of planning unit subordinate rationally according to majority principle.
2. a kind of urban education service facility according to claim 1 evaluates optimization method, it is characterised in that: the step
In rapid 1, when integral data, unified standard processing is first carried out, is then registrated, consistent georeferencing coordinate is set.
3. a kind of urban education service facility according to claim 1 evaluates optimization method, it is characterised in that: the step
In rapid 3, data source traffic big data provided by internet of blind area is identified.
4. a kind of urban education service facility according to claim 1 evaluates optimization method, it is characterised in that: the step
In rapid 4, the evaluation rational process of school district scribing includes following sub-step,
Step 4.1. input calculates data, including range data, cell data, school's data and school district data '
Step 4.2. initializes parameters, total cell number including counting each school district obtains school district by reading input data
Interior each cell distance most from school ID1 and they with a distance from, obtain school ID2 as defined in current area, statistics school district by
The total number of people of education；
The total distance value of step 4.3. statistics in-zone cell school, it is whether consistent with ID2 to judge ID1, if unanimously, increasing to
In the statistics of the concordance rate index in area, if inconsistent, judge whether cell is less than threshold distance to school's minimum distance.If small
Increased in then school district by the statistical value of service children's number and cell number；
Step 4.4. calculates school district concordance rate index according to above-mentioned statistical result, calculates school district and corresponds to the flat of school's serving cell
Equal distance calculates school's space advantage degree index；
Step 4.5. loop iteration exports result after every evaluation index of all school districts calculates.
5. a kind of urban education service facility according to claim 4 evaluates optimization method, it is characterised in that: the step
It in rapid 4, is divided, is carried out with existing school district comprehensive using the school district that Voronoi diagram is met " entering a school nearest to one's home " when evaluating reasonability
Evaluation is closed, provides decision support and suggestion for the analysis of further school district Partitioning optimization and school's Optimizing Site Selection.
6. a kind of urban education service facility evaluation optimization method, feature described according to claim 1 or 2 or 3 or 4 or 5
Be: in the step 5, the process that educational alternative is distributed rationally includes following sub-step.
Step 5.1, input calculates data, including cell table, school's table and cell school relation database table.
Step 5.2, by reading input data, cell school table is arranged by the descending of association score, judges whether school has and reaches
To maximum number of students；
If it is not, first selection is classified as 0 row in selection cell table, it is nearest to obtain distance in cell number and school's cell table
Row, is added new school's cell table, and label selection is classified as 2；
If so, finding out the item that selection in school's cell table of corresponding school is classified as 0, school's number and cell number, mark are obtained
The options for remembering the row is 1, and judges whether to reach maximum number of students, and the selective value for not up to then setting cell table is 1, sets school
The number of student of table is the sum of the value of current value and cell number of students, otherwise searches the school of other not up to maximum numbers of students,
Continue to judge.
Step 5.3, configuration result is exported.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111582764A (en) * | 2020-06-01 | 2020-08-25 | 重庆市规划设计研究院 | Modeling method for different-level homogeneous service balance configuration |
| CN112036640A (en) * | 2020-08-31 | 2020-12-04 | 河南大学 | Division method and device for public facility service area |
| CN112734607A (en) * | 2020-12-25 | 2021-04-30 | 临沂大学 | Accessibility analysis and evaluation method based on basic education facilities |
| CN113962497A (en) * | 2021-12-22 | 2022-01-21 | 深圳市华师兄弟教育科技有限公司 | Teacher resource analysis is accuse system based on internet education |
| CN114580773A (en) * | 2022-03-15 | 2022-06-03 | 城云科技（中国）有限公司 | Academic district pressure assessment method, device and application |
| CN114817427A (en) * | 2022-02-28 | 2022-07-29 | 中国城市建设研究院有限公司 | Method and device for screening suitable old cell, electronic equipment and computer readable medium |
| CN115809825A (en) * | 2022-12-13 | 2023-03-17 | 广州市城市规划勘测设计研究院 | Method, device and medium for division and evaluation of school districts |
| CN116957305A (en) * | 2023-09-20 | 2023-10-27 | 安徽互联智库数据技术有限公司 | Regional service resource intelligent adaptation method and system based on big data |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107403238A (en) * | 2017-07-21 | 2017-11-28 | 江西和壹科技有限公司 | The optimization method of county domain Balanced Development of Compulsory Education based on population |
| CN107679663A (en) * | 2017-10-09 | 2018-02-09 | 中国电子科技集团公司第二十八研究所 | A kind of educational resource monitoring and warning system |
| CN109345101A (en) * | 2018-09-21 | 2019-02-15 | 常州工学院 | Evaluation in Education Quality analysis method based on comprehensive evaluation analysis method |
-
2019
- 2019-05-31 CN CN201910470342.2A patent/CN110490352A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107403238A (en) * | 2017-07-21 | 2017-11-28 | 江西和壹科技有限公司 | The optimization method of county domain Balanced Development of Compulsory Education based on population |
| CN107679663A (en) * | 2017-10-09 | 2018-02-09 | 中国电子科技集团公司第二十八研究所 | A kind of educational resource monitoring and warning system |
| CN109345101A (en) * | 2018-09-21 | 2019-02-15 | 常州工学院 | Evaluation in Education Quality analysis method based on comprehensive evaluation analysis method |
Non-Patent Citations (2)
| Title |
|---|
| 潘炎炎: "基于 GIS 的徐州市农村义务教育资源布局优化研究———以丰县为例", 《测绘与空间地理信息》 * |
| 翁 敏 ，罗 馨，李维庆，苏世亮，李永鑫: "地理国情辅助决策综合分析专题图：概念框架、 设计理念与表达模式", 《地理信息世界》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111582764A (en) * | 2020-06-01 | 2020-08-25 | 重庆市规划设计研究院 | Modeling method for different-level homogeneous service balance configuration |
| CN112036640A (en) * | 2020-08-31 | 2020-12-04 | 河南大学 | Division method and device for public facility service area |
| CN112036640B (en) * | 2020-08-31 | 2022-10-28 | 河南大学 | Division method and device for public facility service area |
| CN112734607A (en) * | 2020-12-25 | 2021-04-30 | 临沂大学 | Accessibility analysis and evaluation method based on basic education facilities |
| CN113962497A (en) * | 2021-12-22 | 2022-01-21 | 深圳市华师兄弟教育科技有限公司 | Teacher resource analysis is accuse system based on internet education |
| CN114817427A (en) * | 2022-02-28 | 2022-07-29 | 中国城市建设研究院有限公司 | Method and device for screening suitable old cell, electronic equipment and computer readable medium |
| CN114580773A (en) * | 2022-03-15 | 2022-06-03 | 城云科技（中国）有限公司 | Academic district pressure assessment method, device and application |
| CN115809825A (en) * | 2022-12-13 | 2023-03-17 | 广州市城市规划勘测设计研究院 | Method, device and medium for division and evaluation of school districts |
| CN116957305A (en) * | 2023-09-20 | 2023-10-27 | 安徽互联智库数据技术有限公司 | Regional service resource intelligent adaptation method and system based on big data |
| CN116957305B (en) * | 2023-09-20 | 2024-02-27 | 合肥工业大学 | Regional service resource intelligent adaptation method and system based on big data |
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