KR102225813B1 - Welfare facility demand forecast management device and method - Google Patents

Abstract

The present invention relates to a welfare facility demand forecast management device and a method thereof. The device includes: a data set construction unit which collects analysis data including facility data and population data for a specific area and builds a data set for predicting a demand for welfare facilities; a supply and demand status derivation unit for deriving the current status of a facility supply and demand for the specific area from the data set; a facility supply and demand adequacy calculation unit for predicting the future population of the specific area based on the analysis data and updating the facility supply and demand status to calculate supply and demand adequacy for each facility; and a density analysis performing unit which performs density analysis on areas with insufficient facilities and areas with oversupply based on the adequacy of supply and demand for the facilities. According to the present invention, it is possible to support a simulation according to the presence or absence of the facilities through the analysis of supply and demand of the welfare facilities according to population changes.

Description

Welfare facility demand forecast management device and method {WELFARE FACILITY DEMAND FORECAST MANAGEMENT DEVICE AND METHOD}

The present invention relates to a welfare facility demand prediction management technology, and more particularly, to a welfare facility demand prediction management apparatus and method capable of supporting a simulation according to the presence or absence of the facility through the analysis of the supply and demand of welfare facilities according to the population change.

As our society is aging, the number of elderly people nationwide is increasing very rapidly. Although the number of people simply classified as the elderly population is increasing, the number of elderly people aged 80 and over, the main age group using welfare facilities for the elderly, is also increasing rapidly. Accordingly, it is predicted that the demand for welfare facilities for the elderly will increase.

On the contrary, the fertility rate is falling day by day. The number of infants and toddlers is decreasing due to the continuing low birth rate, and for this reason, many daycare centers that cannot maintain a garden are closing every year.

As such, all welfare facilities have a close relationship with the number of beneficiaries, and therefore, it is necessary to maintain an appropriate number of welfare facilities for each region in consideration of fertility rates and regional conditions.

Among the various welfare facilities, senior citizens' halls and daycare centers, in particular, are closely located in the lives of beneficiaries and should be easily and universally used. Accordingly, there is a need for the development of technology that can support appropriate demand and supply for target facilities, reflecting regional characteristics and rapidly changing demographic structures.

Korean Patent Publication No. 10-2014-0056461 (2014.05.12)

An embodiment of the present invention is to provide an apparatus and method for predicting and managing a demand for welfare facilities that can support a simulation according to the presence or absence of a facility through the analysis of supply and demand of welfare facilities according to a change in population.

An embodiment of the present invention is to provide an apparatus and method for predicting and managing a demand for welfare facilities capable of deriving the total area of a facility and a total real demand in units of buildings, and calculating the adequacy of supply and demand for facilities with respect to the supply and demand ratio for each facility.

An embodiment of the present invention is to provide an apparatus and method for predicting and managing a demand for a welfare facility that can recommend a location for a new facility by performing a density analysis on a facility shortage area and an excess supply area based on adequacy of facility supply and demand.

Among the embodiments, the apparatus for predicting demand for welfare facilities includes a data set construction unit configured to construct a data set for predicting demand for welfare facilities by collecting analysis data including facility data and population data about a specific area, the Supply and demand status derivation unit that derives the supply and demand status of facilities in the specific area from the data set, and the supply and demand adequacy of facilities that predicts the future population of the specific area based on the analysis data and updates the supply and demand status of the facilities to calculate the supply and demand adequacy for each facility It includes a calculation unit and a density analysis performing unit that performs density analysis on areas with insufficient facilities and areas with excess supply based on the appropriateness of supply and demand for the facilities.

The apparatus for predicting and managing a demand for welfare facilities may further include a facility allocation analysis unit configured to determine a new location for distributing welfare facilities in the specific area by performing a network analysis according to the result of the density analysis.

The data set construction unit refines data for facility supply and demand analysis, and from the analysis data (a) facility information on the location, area, and capacity of each facility, (b) population information on the number of population by age and (c) according to the published land price. By deriving income information on income level and (d) road information on road connectivity, and refining data for location analysis, (e) demographic information on birth rate, moving population and mortality rate, and (f) traffic accident points And it is possible to build the data set by deriving the hazardous area information on the hazardous facilities.

The supply and demand status derivation unit is a first step of allocating the population by age to each residential building in proportion to the gross floor area for each count, a second step of calculating the first real demand for each building by applying a weight according to the facility utilization rate by age to the allocation result; and By performing the third step of calculating the second real demand for each building by applying a weight according to the facility utilization rate for each income to the first real demand, it is possible to derive the real demand for each building for welfare facilities.

The supply and demand status derivation unit may derive the total area of facilities available for each building and total real demands of the facilities by integrating the real demand for each building and a service area for each facility.

The facility supply and demand adequacy calculation unit may predict the future population by performing a time series analysis on the fertility rate, mortality rate, and population movement in a specific age section based on statistics of the analysis data.

The facility supply and demand adequacy calculation unit may determine, as the facility supply and demand adequacy, a supply/demand ratio for each facility calculated through the following equation based on the facility area and total real demand of the facility.

[Equation]

Among the embodiments, the method for predicting and managing welfare facilities demand comprises the steps of constructing a data set for forecasting welfare facilities demand by collecting analysis data including facility data and population data related to a specific area, from the data set. Deriving the supply and demand status of facilities for the specific area, predicting the future population of the specific area based on the analysis data and updating the supply and demand status of the facilities to calculate the supply and demand adequacy for each facility, based on the supply and demand adequacy of the facilities And performing a density analysis on a facility shortage area and an excess supply area, and performing a network analysis according to a result of the density analysis to determine a new location for distributing welfare facilities in the specific area.

The disclosed technology can have the following effects. However, since it does not mean that a specific embodiment should include all of the following effects or only the following effects, it should not be understood that the scope of the rights of the disclosed technology is limited thereby.

The apparatus and method for predicting and managing the demand for welfare facilities according to an embodiment of the present invention may derive a total area of a facility and a total real demand for each building, and calculate a facility supply and demand adequacy with respect to a supply and demand ratio for each facility.

The apparatus and method for predicting and managing the demand for welfare facilities according to an embodiment of the present invention may recommend a location for a new facility by performing density analysis on a facility shortage area and an excess supply area based on the facility supply and demand adequacy.

1 is a block diagram illustrating an apparatus for predicting and managing a demand for welfare facilities according to the present invention.
FIG. 2 is a flow chart illustrating a process of predicting and managing a demand for welfare facilities using data analysis performed by the apparatus for predicting and managing a demand for welfare facilities of FIG. 1.
FIG. 3 is a diagram illustrating data types related to population movement, survival rate, and fertility rate among time series analysis for population prediction in the process of predicting and managing demand for welfare facilities according to the present invention.
4 is a diagram illustrating a cohort-factor method for predicting population in the process of predicting and managing demand for welfare facilities according to the present invention.
5 to 7 are diagrams illustrating an embodiment of a population prediction result performed by the apparatus for predicting and managing a demand for welfare facilities in FIG. 1.
8 is a diagram illustrating a process of analyzing a service area for each facility in the process of predicting and managing a demand for welfare facilities according to the present invention.
9 and 10 are diagrams for explaining the allocation of population by building and calculation of real demand in the process of predicting and managing demand for welfare facilities according to the present invention.
11 and 12 are diagrams for explaining the summation of end users for each facility and calculation of total end users in the process of predicting and managing the demand for welfare facilities according to the present invention.
13 is a view for explaining the calculation of supply and demand adequacy for each facility in the process of predicting and managing the demand for welfare facilities according to the present invention.
14 is a diagram illustrating a density analysis in the process of predicting and managing a demand for welfare facilities according to the present invention.
15 is a diagram illustrating a demand increase area derived as a result of density analysis in the process of predicting and managing a demand for welfare facilities according to the present invention.
16 is a diagram illustrating an oversupply area derived as a result of density analysis in the process of predicting and managing a demand for welfare facilities according to the present invention.

Since the description of the present invention is merely an embodiment for structural or functional description, the scope of the present invention should not be construed as being limited by the embodiments described in the text. That is, since the embodiments can be variously changed and have various forms, the scope of the present invention should be understood to include equivalents capable of realizing the technical idea. In addition, since the object or effect presented in the present invention does not mean that a specific embodiment should include all or only such effects, the scope of the present invention should not be understood as being limited thereto.

Meanwhile, the meaning of terms described in the present application should be understood as follows.

Terms such as "first" and "second" are used to distinguish one component from other components, and the scope of rights is not limited by these terms. For example, a first component may be referred to as a second component, and similarly, a second component may be referred to as a first component.

When a component is referred to as being "connected" to another component, it should be understood that although it may be directly connected to the other component, another component may exist in the middle. On the other hand, when it is mentioned that a component is "directly connected" to another component, it should be understood that there is no other component in the middle. On the other hand, other expressions describing the relationship between components, that is, "between" and "just between" or "neighboring to" and "directly neighboring to" should be interpreted as well.

Singular expressions are to be understood as including plural expressions unless the context clearly indicates otherwise, and terms such as "comprises" or "have" refer to implemented features, numbers, steps, actions, components, parts, or It is to be understood that it is intended to designate that a combination exists and does not preclude the presence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

In each step, the identification code (e.g., a, b, c, etc.) is used for convenience of explanation, and the identification code does not describe the order of each step, and each step has a specific sequence clearly in the context. Unless otherwise stated, it may occur differently from the stated order. That is, each of the steps may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

The present invention can be implemented as computer-readable code on a computer-readable recording medium, and the computer-readable recording medium includes all types of recording devices storing data that can be read by a computer system. . Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tapes, floppy disks, and optical data storage devices. Further, the computer-readable recording medium is distributed over a computer system connected through a network, so that computer-readable codes can be stored and executed in a distributed manner.

All terms used herein have the same meaning as commonly understood by one of ordinary skill in the field to which the present invention belongs, unless otherwise defined. Terms defined in commonly used dictionaries should be construed as having meanings in the context of related technologies, and cannot be construed as having an ideal or excessively formal meaning unless explicitly defined in the present application.

The apparatus 100 for predicting demand for welfare facilities may be implemented as a server corresponding to a computer or program capable of supporting a simulation according to the presence or absence of a facility through the analysis of supply and demand of welfare facilities according to a change in population. The apparatus 100 for predicting demand for welfare facilities may be wirelessly connected to various user terminals through Bluetooth, WiFi, a communication network, and the like, and may exchange data with user terminals through a network.

In an embodiment, the apparatus 100 for predicting demand for welfare facilities may store data necessary for predicting and managing demand for welfare facilities in connection with a database. The apparatus 100 for predicting demand for welfare facilities may be implemented by including a database therein. In addition, the apparatus 100 for predicting demand for welfare facilities may be implemented including a processor, a memory, a user input/output unit, and a network input/output unit, and a detailed description thereof will be omitted.

The database may correspond to a storage device that stores various information necessary in the process of predicting and managing the demand for welfare facilities. For example, the database may store analysis data including collected facility data and population data, and store statistical information of the collected data and facility supply and demand status information derived through analysis. In addition, the database may be composed of a plurality of database modules to store and manage each information, and each database module may be connected to a network to form one database group.

1 is a block diagram illustrating an apparatus for predicting and managing a demand for welfare facilities according to the present invention.

Referring to FIG. 1, the apparatus 100 for predicting demand for welfare facilities 100 includes a data set construction unit 110, a supply and demand status derivation unit 120, a facility supply and demand adequacy calculation unit 130, a density analysis execution unit 140, and a facility. The allocation analysis unit 150 and the control unit 160 may be included.

The data set construction unit 110 may collect analysis data including facility data and population data on a specific area to build a data set for predicting demand for welfare facilities. Facility data may correspond to data on welfare facilities existing in a specific area, and population data may correspond to data on population living in a specific area. For example, the facility data may include data on daycare centers, per route, etc. existing in a specific area, and the population data may include the number of populations per counting ward in a specific area.

On the other hand, the analysis data may correspond to the information necessary to predict the demand for welfare facilities, and may include facility data and population data. It may include traffic accident and building data. That is, the data set construction unit 110 may collect data for welfare facility demand prediction from external systems or public data and store it in a database, and refine and process the data so that it can be easily used in the process of demand forecasting and analysis. You can do it.

In one embodiment, the data set construction unit 110 purifies data for facility supply and demand analysis, and (a) facility information on the location, area, and capacity of each facility and (b) population information on the number of populations by age per aggregate section. And (c) income information on income level according to the published land price and (d) road information on road connectivity, and through data refining for location analysis, (e) demographic information on birth rate, moving population and mortality rate, and (f) A data set can be constructed by deriving information on hazardous areas on frequent traffic accident points and hazardous facilities.

More specifically, the data set construction unit 110 may derive (a) facility information about the location, area, and capacity of each facility through data purification. For example, among the collected welfare facility information, since the address is expressed as a lot number or street name address, the data set construction unit 110 converts the text address into the coordinates of the desired coordinate system. ) Can be performed. Geocoding may correspond to a technique of obtaining coordinate values of latitude and longitude with a unique name (address, mountain, lake, etc.). The data set construction unit 110 may obtain coordinate data for a welfare facility through geocoding, convert it into pointer data on a spatial coordinate system, and store it in a database.

Meanwhile, the data set construction unit 110 may calculate a coordinate value replaced with a neighboring coordinate or a road center coordinate when the address of the welfare facility is changed or not registered.

In addition, the data set construction unit 110 may derive (b) population information on the number of populations by age for each aggregated section through data purification. The data set construction unit 110 may derive population number data in units of 5 years of age for each aggregated section based on the collected population data. In this case, each counting section may be identified by a counting section code, and the number of age-specific populations corresponding to each counting section may include the number of populations calculated for each age section.

Meanwhile, the data set construction unit 110 may estimate and distribute the 5-year-old population based on the 5-year-old data and the 0-4-year-old data for each counting section from the population number data in the 5-year-old age unit. For example, it can be assumed that the total population of 5-9 years old is about 32,000 people, and if this is divided by 5, about 6400 people are about 5 years old. Then, to allocate 6,400 people, a 5-year-old estimate can be calculated by multiplying the ratio obtained by dividing the 0-4 year old population in each counting area by the total local 0-4 year old population.

The final infant (0-5 years old) population can be calculated by adding the 0-4 year old population to the 5 year old population estimate obtained through this.

In addition, the data set construction unit 110 may derive (c) income information about the income level according to the published land price through data purification. The data set construction unit 110 may classify the individual publicly announced price data into any one of a plurality of grades. In addition, the data set construction unit 110 may derive (d) road information regarding road connectivity through data refinement. In the case of a pedestrian road, the data set construction unit 110 may reconstruct road information by adding a crosswalk and connecting lines in an apartment housing complex based on the road name road data. In addition, the data set construction unit 110 may derive demographic information about (e) the birth rate, the moving population, and the mortality rate through data purification.

In addition, the data set construction unit 110 may derive (f) dangerous area information about traffic accident points and hazardous facilities through data purification. The data set construction unit 110 may extract only data classified as dangerous facilities from the entire building information, and in this case, the dangerous facilities may correspond to facilities that cannot be built close to welfare facilities. The data set construction unit 110 can extract only buildings that include'dangerous goods','factory','entertainment', and'entertainment' based on the building usage code, and create a 50m buffer based on the location of the building. Can be generated. The data set construction unit 110 may extract only vehicle-to-person accident types from traffic accident data and convert them into data to generate traffic accident frequent points.

The supply and demand status derivation unit 120 may derive the supply and demand status of facilities for a specific region from the data set. The supply and demand status of facilities may correspond to the supply and demand status of welfare facilities located within a specific area. The supply and demand status derivation unit 120 may derive the supply and demand status of welfare facilities based on the current time based on the collected information.

In one embodiment, the supply and demand status derivation unit 120 may derive a service area for each facility through road network analysis. 8 is a diagram illustrating a process of analyzing a service area for each facility in the process of predicting and managing a demand for welfare facilities according to the present invention. Referring to FIG. 8, the supply and demand status derivation unit 120 may derive through a network analysis to which area a service is available based on a diplopia facility (eg, a route or a daycare center).

For example, if you walk for 10 minutes based on the average walking speed of 2.16km/h of people over 65 years old, the distance you can go is about 360m. The daycare center can go about 222m in 5 minutes, taking into account the slowing speed when walking with a stroller at the average walking speed of 4km/h for adults, calculated at 2.67km/h. The supply and demand status derivation unit 120 may derive a service area based on each facility in order to analyze whether there is a senior citizen within 10 minutes and a daycare center within 5 minutes based on each building.

In Fig. 8 (a), in the case of a facility that is not close to a road, as a result of analysis based on the nearest road, there may be a problem that a service area is not displayed in a nearby building. Accordingly, the supply and demand status derivation unit 120 may generate a 100m buffer around the facility. In this case, creating a buffer of too large a range may make network analysis meaningless. The supply and demand status derivation unit 120 may widen the boundary of the service area for each facility after merging the 100m buffer and the boundary node resulting from the network analysis.

On the other hand, the supply and demand status derivation unit 120 completes the construction of the minimum boundary figure for the service area (the rightmost picture in Fig. 8 (a)), and then the facility-related properties (for example, facility area) in each facility service area. , Garden, etc.).

In the figure (b) of FIG. 8, the supply and demand status derivation unit 120 calculates the total demand for each facility. In order to subtract the number of times (if the facility service area overlaps several times), an overlapping area of the facility service area can be derived. At this time, if the polygon is overlapped 3 times, it can be confirmed that 3 polygons are created in the overlapping part.

In the figure (c) of FIG. 8, the supply and demand status derivation unit 120, if there is an overlapped area 3 times, the demand of the area needs to be subtracted only 2 times, so that it is possible to create a layer that intersects all overlapping areas only once. As a result, only one overlapping polygon remains.

In one embodiment, the supply and demand status derivation unit 120 is a first step of allocating the population by age to each residential building in proportion to the total floor area for each count, and applying a weight according to the facility utilization rate by age to the allocation result, By performing the second step of calculating the real demand and the third step of calculating the second real demand for each building by applying a weight according to the facility utilization rate by income to the first real demand, the real demand for each building for welfare facilities can be derived.

More specifically, the supply and demand status derivation unit 120 may allocate the population by age for each counting zone to each residential building in proportion to the total floor area. The supply and demand status derivation unit 120 may allocate the population in smaller units based on the population information calculated in units of counting wards. That is, the supply and demand status derivation unit 120 can allocate the population in proportion to the total floor area of each building, and more specifically, the total floor area of each building is divided by the total gross area of all buildings in the county area where the building is located, and the population for each building is Distribution weights can be calculated. The supply and demand status derivation unit 120 may calculate a population value proportional to the total floor area of the building by multiplying the total population of the aggregated area in which the corresponding building is located by the population distribution weight for each building.

For example, FIGS. 9 and 10 are diagrams for explaining the population distribution and real demand calculation for each building in the process of predicting and managing the demand for welfare facilities according to the present invention, and FIG. 9 (a) is a total floor area for each building (floor * area). It may correspond to the population weight (area_weight) for each building derived by the supply and demand status derivation unit 120 based on the total gross floor area (t_area) of the building in the county area.

In addition, the supply and demand status derivation unit 120 may calculate the first real demand for each building by applying a weight according to the facility utilization rate for each age to the allocation result. For example, the figure (b) of FIG. 9 may correspond to the utilization rate per route by age, and the supply and demand status derivation unit 120 applies the utilization rate per route by age to the number of prospective users per building allocated for each building. Can be calculated. That is, the first real demand for each building may correspond to the current demand in consideration of the facility utilization rate for each age in a building unit within a specific area.

In addition, the supply and demand status derivation unit 120 may calculate the second real demand for each building by applying a weight according to the facility utilization rate for each income to the first real demand. That is, the second real demand for each building may correspond to a demand situation that considers both the facility use rate by age and the facility use rate by income in a building unit within a specific area. Meanwhile, the figure (c) of FIG. 9 may correspond to the utilization rate per channel for each income. In this case, the income quintile can be determined based on the publicly announced land price of each building, and can be classified so that the elderly population allocated for each income quintile is the same.

For example, if the total population of elderly people allocated to a building is about 80432 people, it can be calculated as 16086 by dividing this by 5. Dividing the value of the publicly announced land price so that approximately 16086 elderly people are allocated to each quintile, the publicly announced land price is in the 5th quintile, those less than 646750 and more than 510000 are in the quartile, those less than 510000 and more than 410100 are in the third quintile, and those less than 410100 and more than 307150 are in the 2nd and less than 307150. It can be calculated in the first quartile. After that, in order to calculate the weight value for each quintile, the ratio of the average utilization rate per route, 23%, and the utilization rate of other quartiles, is calculated. It can be calculated as 0.95 for silver, 0.79 for the quartile, and 0.67 for the quintile.

As a result, the supply and demand status derivation unit 120 can calculate the second real demand for each building by multiplying the first real demand by the weight according to the facility utilization rate for each income, and FIG. 10 shows the final real demand for each building in a specific area (the second real demand). It may correspond to the result of the calculation for. 10 may correspond to the final real demand for each building at a specific time point (left) and the final real demand for each building 5 years later (right).

In one embodiment, the supply and demand status derivation unit 120 may derive the total area of facilities available for each building and the total real demands of the corresponding facilities by integrating the real demand for each building and the service area for each facility. 11 and 12 are diagrams for explaining the summation of end users for each facility and calculation of total end users in the process of predicting and managing the demand for welfare facilities according to the present invention.

Referring to FIGS. 11 and 12, the supply and demand status derivation unit 120 may calculate how many end users reside within an area that can reach the facility in order to compare the supply and demand for each facility. The supply and demand status derivation unit 120 may perform the final calculation on a per building basis to calculate the total amount of the facility area available in each building and the total number of end users who can use the facility. Through this, the supply and demand status derivation unit 120 may provide information for analysis, such as whether there is more real demand compared to the supply amount of the facility, or whether the supply is excessive compared to the surrounding demand.

In the figure (a) of FIG. 11, the supply and demand status derivation unit 120 may spatially join the facility service area and the real demand for each building.

In the figure (b) of FIG. 11, the supply and demand status derivation unit 120 is a facility service area overlapping area ( Intersect) can be space-joined with the same building-specific real demand.

In the figure (c) of FIG. 12, the supply and demand status derivation unit 120 needs to subtract only two times when there is an overlapped area three times, so that the layer (dissolve) intersects the overlapped area of the facility service area only once. Space-joined real demand for each building.

In Fig. 12 (d), the supply and demand status derivation unit 120 can calculate the total amount of facility area available in each building and the total number of end users who can use the facility by integrating the results of Figs. (a) to (c). have.

Total real demand calculation result[result_b] = service area[total_b]-service area overlapping area (intersect)[minus_b] + overlapping area(dissolve)[plus_b]

The facility supply and demand adequacy calculation unit 130 may predict the future population of a specific region based on the analysis data and update the supply and demand status of the facility to calculate the supply and demand adequacy for each facility. The facility supply and demand adequacy calculation unit 130 may derive the supply and demand adequacy for each facility as a result of quantifying whether the level of supply and demand for welfare facilities in the corresponding area can be maintained at an appropriate ratio through population prediction for a specific area.

In an embodiment, the facility supply/demand adequacy calculation unit 130 may predict a future population by performing a time series analysis on the fertility rate, mortality rate, and population movement in a specific age section based on statistics of the analysis data. Hereinafter, it will be described in more detail based on FIGS. 3 to 7.

FIG. 3 is a diagram illustrating data types related to population movement, survival rate, and fertility rate among time series analysis for population prediction in the process of predicting and managing demand for welfare facilities according to the present invention. 4 is a diagram illustrating a cohort-factor method for predicting population in the process of predicting and managing demand for welfare facilities according to the present invention. 5 to 7 are diagrams illustrating an embodiment of a population prediction result performed by the apparatus for predicting and managing a demand for welfare facilities in FIG. 1.

Time series can correspond to data recorded by observing and recording one event or several events at regular intervals according to the passage of time. It may correspond to a method of predicting by establishing a model under the assumption that such a pattern will repeat without losing its characteristics.

The facility supply and demand adequacy calculation unit 130 may perform population prediction using an approach based on a time series model that extrapolates a process of population change such as fertility rate, mortality rate, and population movement. In this case, the time series model used may include an ARIMA model. The ARIMA model combines AR (autoregression: a finite number of past values to describe the current value) and MA (moving average: a linear combination of past and present errors, and an error value to describe the current value) models are combined. In this form, the concept of difference (difference between observed values at different points in time, trend removal) may be included therein.

In the figure (a) of FIG. 3, the facility supply and demand adequacy calculation unit 130 may build the number of population movements in a 5-year-old age unit for a specific area based on the collected population data. In the figure (b) of FIG. 3, the facility supply and demand adequacy calculation unit 130 may build a 5-year-old age unit for a specific area based on the collected population data. In this case, the mortality rate and the number of deaths can be derived in units of 100,000. In the figure (c) of FIG. 3, the facility supply and demand adequacy calculation unit 130 may establish a birth rate in a 5-year-old age unit for a specific area. In this case, the fertility rate may correspond to the fertility rate per hundred.

In FIG. 4, the facility supply/demand adequacy calculation unit 130 may perform population prediction using a cohort-factor method. The cohort-factor method may correspond to a method of estimating the population through the equation P(t + n) = P(t) + B-D + IM-OM. Here, P(t + n) is the population of t + n, P(t) is the population of t, B is the birth population from t to t + n, and D is from t to t + n The mortality population up to, IM may correspond to the influent population from t to t + n, and OM may correspond to the outflow population from t to t + n.

In addition, the facility supply and demand adequacy calculation unit 130 may calculate the total number of deaths, births, and population movements for five years without deriving a result value by calculating the next year five times based on the base year.

In the figure (a) of FIG. 5, the facility supply and demand adequacy calculation unit 130 may add up the amount of population movement for 5 years and then reflect it in the 2023 population forecast. At this time, the population aged 0-4 in 2018 can be used to predict the population aged 5-9 in 2023. Similarly, the population aged 60-64 as of 2018 can be used to predict the population aged 65-69 in 2023.

In the figure (b) of FIG. 5, the facility supply and demand adequacy calculation unit 130 may reflect the net moving population, and then reflect the survival rate (1-mortality rate). The 5-9 year old population in 2023 can be calculated by reflecting the amount of population migration and the survival rate to the population aged 0-4 in 2018. In the case of a population aged 80 or older, the value obtained by multiplying the survival rate by the population that was previously classified as 80 or older and the population newly entering the 80s can be classified as the final population in the 80s.

In the figure (c) of FIG. 6, the facility supply and demand adequacy calculation unit 130 may estimate the number of births for five years by reflecting the fertility rate based on the predicted population for women. If the total number of births for each age group for five years plus the net moving population aged 0-4 over five years, the population aged 0-4 in 2023 can be calculated.

In the figure (d) of FIG. 6, the facility supply and demand adequacy calculation unit 130 may reflect the future population prediction result in the population data for each age unit of a counting unit constructed in the process of refining and processing the data. The estimated population value for each age group of each count may be calculated by multiplying the population data by age group per count by the estimated value derived from the population prediction result.

More specifically, the facility supply and demand adequacy calculation unit 130 can derive a population increase or decrease rate as a ratio between the current population and the estimated population by reflecting the mortality rate, survival rate, and fertility rate. Can be predicted. Figure 7 (a) is a comparison of the population aged 0-5 years after the base year and 5 years, and Figure (b) of Figure 7 corresponds to the comparison of the population aged 80 or older after the base year and 5 years. I can.

In an embodiment, the facility supply/demand adequacy calculation unit 130 may determine a supply/demand ratio for each facility, calculated through the following equation, based on the facility area and the total actual demand for the facility, as the facility supply/demand adequacy.

[Equation]

In this case, if there is a capacity, the capacity is substituted instead of the facility area, and the standard area per person is not considered. The standard area per person per senior is 2 m ² , and daycare centers can be calculated by substituting the capacity for the facility area.

In addition, the facility supply and demand adequacy calculation unit 130 excludes the building in which the'total real facility demand' value is 0 (there is no facility to use, so there is no total real demand value of the facility) by the above equation. And can be calculated. Meanwhile, the facility supply and demand adequacy calculation unit 130 may input a value of'-real demand for each building' for a building in which the'total real demand for facilities' value is 0. Through this, a positive value can be entered for buildings with available facilities, and a -value can be entered for buildings that do not have facilities but are in demand.

Therefore, if the calculated ratio value is greater than 1, the facility supply received by the building is excessive compared to the local demand, and if it is greater than 0 and less than 1, it is receiving the facility supply, and there is a degree of difference depending on the ratio, and if it is less than 0, it is the corresponding This could mean that the building is in demand but the facility is not being supplied. 13 may show the result of calculating the supply and demand adequacy for each facility in the process of predicting and managing the demand for welfare facilities according to the present invention. Figure 13 (a) corresponds to the appropriateness of supply and demand for senior citizens, and Figure 13 (b) corresponds to the appropriateness of supply and demand for daycare centers.

The density analysis performing unit 140 may perform density analysis on a facility shortage area and an excess supply area based on the facility supply and demand adequacy. The density analysis performing unit 140 may perform density analysis for a specific region as a useful analysis when trying to make a relative evaluation of the supply amount and demand of facilities by region.

14 is a diagram illustrating a density analysis in the process of predicting and managing a demand for welfare facilities according to the present invention.

In the figure (a) of FIG. 14, the density analysis performing unit 140 may perform consumer density analysis for a building without facilities. In this case, as a density analysis method, kernel density may be used. The density analysis performing unit 140 may convert only buildings without available facilities into points, and may derive regional changes by performing density analysis based on data from the base year and 5 years later.

In the figure (b) of FIG. 14, the density analysis performing unit 140 may perform density analysis on buildings with a greater supply than demand. In this case, as a density analysis method, kernel density may be used. The density analysis performing unit 140 may derive regional changes by performing density analysis based on data from the base year and 5 years later. On the other hand, in the case of a path, a radius of 500 meters may be additionally reflected in the density analysis process, and in the case of a daycare center, a radius of 300 meters may be additionally reflected.

The facility allocation analysis unit 150 may perform a network analysis according to the result of the density analysis to determine a new location for distributing welfare facilities in a specific area. The facility allocation analysis unit 150 may perform network analysis while changing the facility location to select a location in consideration of the number of beneficiaries and facility area. The facility allocation analysis unit 150 may select an analysis target site by referring to a density analysis result performed for an area without facilities. That is, the facility allocation analysis unit 150 may perform a facility allocation network analysis by selecting a region where demand is expected to increase in the future.

For example, FIG. 15 is a diagram illustrating a demand increase area derived as a result of density analysis in the process of predicting demand for welfare facilities according to the present invention, and FIG. 15 (a) is a result of the density analysis. In addition, the figure (b) of FIG. 15 may correspond to the result of analysis of the allocation network for the region of increasing demand.

That is, the facility allocation analysis unit 150 may convert the demand for each building in a polygonal format into points, and then perform an allocation network analysis during network analysis to select a facility size and location. The facility allocation analysis unit 150 may finally determine whether a location is located after confirming whether the corresponding area is within 50m of a dangerous facility or is not a traffic accident-prone area.

In addition, FIG. 16 is a diagram illustrating an oversupply area derived from a density analysis result in the process of predicting and managing a demand for welfare facilities according to the present invention, and FIG. 16 (a) is a result of the density analysis. It may correspond to, and Figure (b) of FIG. 16 may correspond to an area that is oversupply in the future as a result of the density analysis.

In the figure (a) of FIG. 16, facilities in an area that is currently in an oversupply area but is expected to increase in demand in the future may not correspond to an oversupply area. Overall, urban areas are in the trend of increasing future demand for Senior Citizens, and there may be a number of areas that fall under such a situation. In addition, the oversupply area, mainly in the outlying area, may not change significantly over time.

In the figure (b) of FIG. 16, facilities in an area that is not currently an oversupply area but is expected to decrease in demand in the future may correspond to an oversupply area. In addition, in the case of daycare centers, due to a decrease in demand, there may be a trend of an increase in oversupply areas.

The control unit 160 controls the overall operation of the welfare facility demand prediction management apparatus 100, and a data set construction unit 110, a supply and demand status derivation unit 120, a facility supply and demand adequacy calculation unit 130, a density analysis execution unit The control flow or data flow between the 140 and the facility allocation analysis unit 150 may be managed.

FIG. 2 is a flow chart illustrating a process of predicting and managing a demand for welfare facilities using data analysis performed by the apparatus for predicting and managing demand for welfare facilities of FIG. 1.

Referring to FIG. 2, the apparatus 100 for predicting demand for welfare facilities collects analysis data including facility data and population data for a specific area through the data set construction unit 110 to predict the demand for welfare facilities. (Data set) can be built (step S210). The welfare facility demand prediction management apparatus 100 may derive the supply and demand status of facilities for a specific region from the data set through the supply and demand status derivation unit 120 (step S230).

In addition, the welfare facility demand prediction management apparatus 100 may predict the future population of a specific area based on the analysis data through the facility supply/demand adequacy calculation unit 130 and update the facility supply/demand status to calculate the supply and demand adequacy for each facility ( Step S250). The apparatus 100 for predicting demand for welfare facilities may perform a density analysis on a facility shortage area and an excess supply area based on the facility supply and demand adequacy through the density analysis performing unit 140 (step S270). The apparatus 100 for predicting demand for welfare facilities may perform a network analysis according to the result of the density analysis through the facility allocation analysis unit 150 to determine a new location for distributing welfare facilities in a specific area (step S290).

The welfare facility demand prediction management device 100 can predict the population in five years through population prediction in a space unit smaller than the existing one, and can perform two analyzes for each facility, each of the present and the future by reflecting the trend of the future demographic structure. have. The apparatus 100 for predicting demand for welfare facilities may introduce a time-series approach to spatial analysis to perform supply and demand analysis on welfare facilities that are greatly affected by changes in the demographic structure over time.

In addition, the welfare facility demand prediction management apparatus 100 can minimize the problem of redundant estimation caused by performing analysis in a small space unit called a building, and by distributing the population data of the counting ward to the residential building unit, each service It is possible to alleviate the problem of slightly different from the reality as buildings are counted over and over in the area. Meanwhile, the apparatus 100 for predicting demand for welfare facilities can be extended and applied to analysis of supply and demand for living SOCs other than welfare facilities.

Although the above has been described with reference to preferred embodiments of the present invention, those skilled in the art will variously modify and change the present invention within the scope not departing from the spirit and scope of the present invention described in the following claims. You will understand that you can do it.

100: welfare facility demand forecast management device
110: data set construction unit 120: supply and demand status derivation unit
130: facility supply and demand adequacy calculation unit 140: density analysis execution unit
150: facility allocation analysis unit 160: control unit

Claims (8)

A data set construction unit for constructing a data set for predicting demand for welfare facilities by collecting analysis data including facility data and population data on a specific area;
A supply and demand status derivation unit for deriving a supply and demand status of facilities for the specific area from the data set;
A facility supply and demand adequacy calculation unit that predicts a future population of the specific region based on the analysis data and updates the supply and demand status of the facility to calculate a supply and demand adequacy for each facility; And
Including a density analysis performing unit that performs density analysis on the facility shortage area and the supply excess area on the basis of the facility supply and demand adequacy,
The facility supply and demand adequacy calculation unit determines a supply and demand ratio for each facility, which is calculated through the following equation, based on the facility area and the total real demand of the facility, as the facility supply and demand adequacy.
[Equation]

(Here, if there is a capacity of the facility, the capacity is substituted instead of the facility area, and the standard area per person is not considered.)
The method of claim 1,
And a facility allocation analysis unit configured to perform a network analysis according to the result of the density analysis to determine a new location for distributing welfare facilities in the specific area.
The method of claim 1, wherein the data set construction unit
From the above analysis data through data purification for facility supply and demand analysis, (a) facility information on the location, area, and capacity of each facility, (b) population information on the number of populations by age by counting section, and (c) income on income level according to the published land price Information and (d) derivation of road information on road connectivity, and through data refining for location analysis, (e) demographic information on birth rate, moving population and mortality rate, and (f) traffic accident points and hazardous facilities. Welfare facility demand prediction management apparatus, characterized in that by constructing the data set by deriving dangerous area information.
The method of claim 1, wherein the supply and demand status derivation unit
The first step of allocating the population by age to each residential building in proportion to the total floor area for each count, the second step of calculating the first real demand for each building by applying a weight according to the facility utilization rate for each age to the allocation result, and the first real demand. A welfare facility demand prediction management device, characterized in that by performing the third step of calculating the second real demand for each building by applying a weight according to the facility utilization rate for each income, the real demand for each building for welfare facilities is derived.
The method of claim 4, wherein the supply and demand status derivation unit
The apparatus for predicting and managing welfare facilities demand, characterized in that by integrating the real demand for each building and the service area for each facility to derive the total area of facilities available for each building and the total real demands of the corresponding facilities.
The method of claim 1, wherein the facility supply and demand adequacy calculation unit
The apparatus for predicting and managing welfare facilities demand, characterized in that for predicting the future population by performing a time series analysis on the fertility rate, mortality rate, and population movement in a specific age section based on statistics of the analysis data.
delete In the method performed in the welfare facility demand forecasting management device,
Collecting analysis data including facility data and population data on a specific area to establish a data set for predicting demand for welfare facilities;
Deriving a supply and demand status of facilities for the specific area from the data set;
Predicting a future population of the specific area based on the analysis data and updating the supply and demand status of the facilities to calculate a supply and demand adequacy for each facility;
Performing a density analysis on areas with insufficient facilities and areas with excess supply based on the appropriateness of supply and demand for each facility; And
Comprising the step of determining a new location for the placement of welfare facilities in the specific area by performing a network analysis according to the result of the density analysis,
The step of calculating the supply and demand adequacy for each facility comprises determining a supply and demand ratio for each facility, which is calculated through the following equation, based on the facility area and total real demand of the facility, as the supply and demand adequacy for each facility. Way.
[Equation]

(Here, if there is a capacity of the facility, the capacity is substituted instead of the facility area, and the standard area per person is not considered.)

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