JP2018180996A - Prediction device, prediction method, and prediction program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To predict highly precisely a feature area value of a predetermined area.SOLUTION: A prediction device comprises: an individual prediction part; and a value prediction part. The value prediction part predicts a future economic state of an economic agent on the basis of economic information of the economic agent performing activity in a predetermined area. The value prediction part predicts a feature area value of the predetermined area on the basis of the future economic state of the economic agent predicted by the individual prediction part.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a prediction device, a prediction method, and a prediction program.

  There is a need for a technology for predicting the future value (hereinafter referred to as area value) of a given area, such as real estate prices. Conventionally, prediction of future area value is made based on the economy, exchange rate, and the like.

JP 2007-102340 A

  The conventional method only predicts the area value based on macroeconomic information such as the economy and exchange rate, and the prediction accuracy is not very high.

  The present application has been made in view of the above, and has an object to accurately predict the future area value of a predetermined area.

  The prediction device according to the present application includes an individual prediction unit and a value prediction unit. The individual prediction unit predicts the future economic status of the economic entity based on the economic information of the economic entity operating in the predetermined area. The value prediction unit predicts the future area value of the predetermined area based on the future economic condition of the economic entity predicted by the individual prediction unit.

  According to one aspect of the embodiment, it is possible to accurately predict the future area value of a predetermined area.

FIG. 1 is a diagram showing an outline of the operation of the prediction device according to the embodiment. FIG. 2 is a diagram illustrating an exemplary configuration of a prediction device according to the embodiment. FIG. 3 is a diagram showing an example of the configuration of the economic information storage unit. FIG. 4 is a diagram showing a configuration example of the individual economic storage unit. FIG. 5 is a diagram showing an example of the configuration of the area economic storage unit. FIG. 6 is a diagram showing an example of the configuration of the area value storage unit. FIG. 7 is a functional block diagram of the control unit. FIG. 8 is a flowchart of the area value calculation process. FIG. 9 is a diagram for explaining an area economic state. FIG. 10 is a diagram showing an output example of the area value. FIG. 11 is a hardware configuration diagram showing an example of a computer for realizing the function of the prediction device.

  Hereinafter, a prediction apparatus, a prediction method, and a mode for carrying out a prediction program (hereinafter, referred to as “embodiment”) according to the present application will be described in detail with reference to the drawings. Note that the prediction device, the prediction method, and the prediction program according to the present application are not limited by the following embodiments. Moreover, the same code | symbol is attached | subjected to the same site | part in the following each embodiment, and the overlapping description is abbreviate | omitted.

[1. Outline of operation of prediction device]
First, an outline of the operation of the prediction device 10 of the present embodiment will be described. The prediction device 10 is a device for predicting the future area value of real estate in a predetermined area.

  The predetermined area is an area set by a user or a device designer (hereinafter, the predetermined area is referred to as a setting area). The setting area is an area of a predetermined range such as Akasaka or Nagatacho. The setting area may be a range set based on administrative divisions such as a prefecture, a city, a district, a town, a village, or may be a range set based on an economic zone. Also, the setting area may be a range set based on the consumption trend. The setting area can be arbitrarily set by the user or the device designer. There may be a plurality of setting areas set in the prediction device 10.

  Also, area value is the value of a set area for real estate (eg, land, buildings). For example, the area value is real estate price or real estate rent (eg, rent, tenant fee, rental fee, parking fee). Of course, the area value is not limited to real estate prices and real estate rents. For example, the area value may be the store opening value (for example, a profit in a reference period assumed when opening in a predetermined area). The area value may be calculated using a monetary amount, or may be calculated using an index (for example, a numerical value when the value at the reference time is 100). Of course, the area value may be calculated by ranks such as A, B and C.

  FIG. 1 is a diagram showing an outline of the operation of the prediction device 10 according to the embodiment. The prediction device 10 is connected to the terminal device 1 and the server 2 via a network. The terminal device 1 and the server 2 connected to the prediction device 10 may be plural. The terminal device 1 is, for example, a user terminal such as a smartphone, a mobile phone, a tablet terminal, or a personal computer. The server 2 is a server host computer that provides various services such as SNS (Social Network Service) and settlement service to the user. The server 2 stores various user information. The user information may be user attribute information or user behavior information. Attribute information includes, for example, information such as age, occupation, income, property, address, address of work, number of languages used, family structure, friend relationship, life cycle, values, lifestyle, personality, preference (for example, demo Graphic information and psychographic information). The action information is, for example, information such as a purchase history and a payment history. Of course, user information may be information other than these. Hereinafter, the outline of the operation of the prediction device 10 will be described with reference to FIG.

  First, the prediction device 10 acquires, from the server 2, economic information of an economic entity (for example, an individual who lives or works in the setting area) performing an activity in the setting area (step S1a). The prediction device 10 may obtain economic information directly from the terminal device 1 of the economic entity (step S1 b). Note that the prediction device 10 may specify an economic entity that performs an activity in the setting area from the position information of the terminal device 1. For example, the prediction device 10 acquires position information from the terminal device 1 at regular intervals, and when the terminal device 1 stays in the setting area for a predetermined time or more, when the economic entity lives or works in the setting area You may judge. The economic entity may be an individual (natural person) or a corporation (eg, a company). In the following description, an economic entity may be called a user. The economic information is, for example, the current income of the economic entity (for example, the income of the last year, the income of the last month). The prediction device 10 stores the acquired economic information in association with the identification information of the economic entity. In the example of FIG. 1, the prediction device 10 stores information of the user 1's current income of 5 million yen, the user 2's current income of 2 million yen, and so on. The prediction device 10 may be configured to acquire economic attribute information and behavior information from the terminal device 1 or the server 2.

  Subsequently, the prediction device 10 predicts the future economic state of the economic entity based on the economic information of the economic entity that performs activities in the set area (step S2). For example, the prediction device 10 predicts future income of the economic entity from the current income of the economic entity. At this time, future income may be expected income derived from attribute information (for example, age, occupation) of the economic entity. The expected income may be, for example, an average value of income at corresponding ages of other economic entities having similar attributes. The future income may be, for example, the income of the year (for example, 15 years later) in which the prediction device 10 predicts the area value. In the example of FIG. 1, the prediction device 10 predicts that the income of the user 1 in the future (for example, after 15 years) is 6 million yen, the future income of the user 2 is 1 million yen,.

  Subsequently, the prediction device 10 predicts the future area economic state of the set area based on the future economic states of the plurality of economic agents who live or work in the set area (step S3). The area economic condition is, for example, future income of the set area (e.g., income after 15 years). The prediction device 10 may predict, as the future income of the set area, a value calculated by multiplying the average value of the future incomes of the plurality of economic agents by the population of the set area. In the example of FIG. 1, the prediction device 10 predicts that the future (for example, after 15 years) of the set area has revenue of ¥ 75 billion. Of course, the future area economic conditions predicted by the prediction device 10 may include the future expenditure of the set area.

  Subsequently, the prediction device 10 predicts the future area value regarding the real estate in the set area based on the area economic condition (step S4). Various methods can be used to calculate the future area value. For example, the prediction device 10 may use, as the area value, the future income of the set area as it is or as an index. In addition, the prediction device 10 may use, as the area value, a weighted sum of future income and future expenditure of the set area. Also, the prediction device 10 may predict the area value of the setting area based on the rate of increase of future income (for example, 75 billion yen) based on the current income (for example, 50 billion yen) of the setting area. Good. At this time, the area value may be, for example, a numerical value (index) indicating the future value when the current value is 100. For example, it is assumed that the current income of the set area is 50 billion yen and the future income of the set area is 75 billion yen. In this case, the prediction device 10 may predict the future area value when the current value of the setting area is 100 as “150” based on the increase rate of income.

  Subsequently, the prediction device 10 corrects the area value based on the macroeconomic information that affects the setting area (step S5). Macroeconomic information is macro information such as the population growth rate of an area. For example, if the population in the set area after 15 years is predicted to be 1.53 times the current one, the prediction device 10 multiplies the area value calculated in step S4 by 1.53 in the set area. It may be a future area value. In the example of FIG. 1, the prediction device 10 predicts that the area value of the setting area is "230" as a result of the correction.

  As described above, the prediction device 10 predicts the future area economic status of the setting area based on the future economic status of the economic entity performing the activity in the setting area, and the area value of the setting area based on the predicted area economic status Predict. Area value depends on the economic condition of the economic entity operating in the set area. The prediction device 10 can predict the area value of the set area with high accuracy, unlike the prediction method that relies heavily on macroeconomic information.

[2. Configuration Example of Prediction Device]
Next, the configuration of the prediction device 10 of the present embodiment will be described in detail. The prediction device 10 is a computer that processes various types of information. For example, the prediction device 10 is a server host computer (hereinafter, simply referred to as a “server”) that processes a request from a client computer (for example, the terminal device 1 or the server 2). The prediction device 10 may be a PC server, a midrange server, or a mainframe server. Further, the prediction device 10 may be configured by one server, or may be configured by a plurality of servers cooperatively executing processing. When the prediction device 10 is configured by a plurality of servers, the installation locations of these servers may be remote. These servers can be regarded as one prediction device 10 if the processing is performed in cooperation, even if the installation locations are separated.

  FIG. 2 is a diagram showing a configuration example of the prediction device 10. As shown in FIG. The prediction device 10 includes a communication unit 11, an output unit 12, a storage unit 13, and a control unit 14. The configuration shown in FIG. 2 is a functional configuration, and the hardware configuration may be different from this.

(Communication unit 11)
The communication unit 11 is a communication interface that communicates with an external device. The communication unit 11 may be a network interface or a device connection interface. For example, the communication unit 11 may be a LAN interface such as a NIC (Network Interface Card), or may be a USB interface configured by a USB (Universal Serial Bus) host controller, a USB port, or the like. The communication unit 11 may be a wired interface or a wireless interface. The communication unit 11 functions as a communication unit of the prediction device 10. The communication unit 11 communicates with an external device according to the control of the control unit 14.

(Output unit 12)
The output unit 12 is an output device for notifying a user of information. The output unit 12 is, for example, a display device such as a liquid crystal display (Liquid Crystal Display) or an organic EL display (Organic Electroluminescence Display). Of course, the output unit 12 is not limited to the display device. For example, the output unit 12 may be a sound generator such as a speaker or a buzzer, or may be a lighting device such as a light emitting diode (LED) lamp. The output unit 12 functions as an output unit (notification unit) of the prediction device 10. The output unit 12 outputs various types of information to the user based on the control of the control unit 14.

(Storage unit 13)
The storage unit 13 is a storage device capable of reading and writing data, such as a dynamic random access memory (DRAM), a static random access memory (SRAM), a flash memory, and a hard disk. The storage unit 13 functions as a storage unit of the prediction device 10. The storage unit 13 includes an economic information storage unit 131, an individual economic storage unit 132, an area economic storage unit 133, and an area value storage unit 134.

(Economic information storage unit 131)
The economic information storage unit 131 is a storage area for storing current economic information of the economic entity. FIG. 3 is a view showing a configuration example of the economic information storage unit 131. As shown in FIG. The economic information storage unit 131 stores identification information (user 1, user 2, user 3,...) Of the economic entity and economic information of the economic entity specified by the identification information in association with each other. The economic information is, for example, the current income of the economic entity (for example, the income of the last year, the income of the last month). The information acquisition unit 141 described later acquires and stores these pieces of information from the server 2 and the like. Although not shown in the figure, in the economic information storage unit 131, information such as the current expenditure of the economic entity, the address of the economic entity, and the address of the work place of the economic entity are associated with the identification information as the economic information. May be stored.

(Individual economic storage unit 132)
The individual economic storage unit 132 is a storage area for storing the future economic status of the economic entity. FIG. 4 is a view showing a configuration example of the individual economic storage unit 132. As shown in FIG. The individual economic storage unit 132 stores the identification information (user 1, user 2, user 3, ...) of the economic entity and the future economic status of the economic entity specified by the identification information in association with each other. . In the following explanation, the economic condition of each economic agent is called "individual economic condition". The individual economic condition is, for example, the future income of the economic agent (eg, the income after 15 years). These pieces of information are generated and stored by an individual prediction unit 142 described later. In the individual economic storage unit 132, in addition to the information on the future income of the economic entity, information such as the future expenditure on the economic entity may be stored in association with the identification information. Future spending of economic agents is also one of the individual economic conditions.

(Area economic storage unit 133)
The area economic storage unit 133 is a storage area for storing the future area economic state of the set area. FIG. 5 is a view showing a configuration example of the area economic storage unit 133. As shown in FIG. The area economic storage unit 133 stores identification information (area A, area B,...) Of the set area in association with the future economic state of the area specified by the identification information. In the following description, the economic condition of the set area is referred to as "area economic condition". The area economic condition is, for example, future income of the set area (e.g., income after 15 years). These pieces of information are generated and stored by the area prediction unit 143 described later. In addition, in the area economic storage unit 133, information such as future spending of the set area may be stored as the area economic state in association with the identification information. Future spending on the set area is also one of the area economic conditions.

(Area value storage unit 134)
The area value storage unit 134 is a storage area for storing the future area value of the set area. FIG. 6 is a view showing a configuration example of the area value storage unit 134. As shown in FIG. The area value storage unit 134 stores identification information of the setting area (area A, area B,...) And the future area value of the area specified by the identification information in association with each other. These pieces of information are generated and stored by the value prediction unit 144 described later. The area value is, for example, a numerical value (index) indicating the future value when the current value is 100. Of course, the area value may be a value other than an index such as money. For example, the area value may be an amount per unit area of land or a tenant fee per unit area of a store.

(Control unit 14)
The control unit 14 is a controller that controls each unit of the prediction device 10. The control unit 14 may be a processor such as a central processing unit (CPU) or a micro processing unit (MPU), or an integrated circuit such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC). It is also good. The control unit 14 functions as a control unit of the prediction device 10. Control part 14 may be constituted by one element, and may be constituted by a plurality of elements. For example, the control unit 14 may be configured by one processor or may be configured by a plurality of processors. When the control unit 14 is configured by a plurality of elements, the plurality of elements may be disposed at a distant place in the prediction device 10. For example, a plurality of elements may be mounted on separate substrates. Control unit 14 includes an “area value calculation process” described later by operating according to a program stored in ROM (Read Only Memory) or RAM (Random Access Memory) inside or outside control unit 14. Implement various operations. The concept of program includes not only OS (Operating System) and application programs, but also microprograms.

  FIG. 7 is a functional block diagram of the control unit 14. The control unit 14 includes an information acquisition unit 141, an individual prediction unit 142, an area prediction unit 143, a value prediction unit 144, and an information generation unit 145. The blocks (the information acquisition unit 141 to the information generation unit 145) that constitute the control unit 14 are functional blocks that indicate the functions of the control unit 14, respectively. These functional blocks may be software blocks or hardware blocks. For example, the functional blocks described above may be one software module implemented by software (including a microprogram) or one circuit block on a semiconductor chip (die). Of course, each functional block may be one processor or one integrated circuit. The configuration method of the functional block is arbitrary. Note that the control unit 14 may be configured in functional units different from these functional blocks, as long as the “area value calculation process” described later is realized.

(Information acquisition unit 141)
The information acquisition unit 141 acquires economic information of an economic entity performing an activity in the setting area. The operation of the information acquisition unit 141 will be described in detail in the description of the area value calculation process described later.

(Individual prediction unit 142)
The individual prediction unit 142 predicts the future economic status of the economic entity based on the economic information of the economic entity operating in the set area. The operation of the individual prediction unit 142 will be described in detail in the description of the area value calculation process described later.

(Area prediction unit 143)
The area prediction unit 143 predicts the future area economic condition of the set area based on the future economic condition of the economic entity predicted by the individual prediction unit 142. The operation of the area prediction unit 143 will be described in detail in the description of the area value calculation process described later.

(Value prediction unit 144)
The value prediction unit 144 predicts the future area value of the set area based on the area economic condition predicted by the area prediction unit 143. Furthermore, the value prediction unit 144 corrects the predicted area value based on macroeconomic information that affects the set area. The value prediction unit 144 may have the function of the area prediction unit 143. In this case, the value prediction unit 144 may predict the future area value of the set area based on the future economic state of the economic entity predicted by the individual prediction unit 142. The future area value predicted by the value prediction unit 144 may be the future area economic state of the set area. The operation of the value prediction unit 144 will be described in detail in the description of the area value calculation process described later.

(Information generation unit 145)
The information generation unit 145 generates information to be output to the user based on the prediction result of the value prediction unit 144. The operation of the information generation unit 145 will be described in detail in the description of the area value calculation process described later.

[3. Details of operation of prediction device]
Next, the operation of the prediction device 10 will be described in detail. FIG. 8 is a flowchart of the area value calculation process. The area value calculation process is a process of predicting the future area value of real estate in the set area. When the control unit 14 of the prediction device 10 receives the process start instruction from the user via the communication unit 11 together with the information on the setting area, the control unit 14 starts the area value calculation process. The information on the setting area may be an administrative division name such as Akasaka or Nagata-cho, or may be one selected by the user from among a plurality of areas prepared by the device designer in advance in the prediction device 10. The setting area may be one or more. Hereinafter, the area value calculation processing will be described with reference to FIG.

  First, the information acquisition unit 141 of the control unit 14 acquires economic information of the economic entity (step S11). Economic information is information on the current income or expenditure of the economic entity. Also, the economic agent is an individual (natural person) or a corporation (for example, a company). In the following description, the economic entity is described as being an individual (natural person), but the economic entity may be a corporation (for example, a company). In this case, the "individual" appearing in the following description is appropriately replaced with the "corporate". Note that the information acquisition unit 141 may specify an economic entity that performs an activity in the setting area based on the position information of the terminal device 1 owned by the economic entity (for example, an individual). For example, the information acquisition unit 141 acquires position information from the terminal device 1 at fixed time intervals. At this time, the position information acquired by the information acquisition unit 141 may be information on the current position of the terminal device 1 determined by the terminal device 1 based on the GPS (Global Positioning System) function of the terminal device 1. Then, when the terminal device 1 stays in the setting area for the preset time or more during the preset period, the information acquisition unit 141 causes the economic entity holding the terminal device 1 to reside or work in the setting area. It may be determined that the entity is an economic entity (eg, an individual). Then, the information acquisition unit 141 may acquire the economic information of the economic entity that owns the terminal device 1 as the economic information of the economic entity that performs the activity in the setting area.

  The information acquisition unit 141 determines the current income and expenses of the individual based on the data acquired from the terminal device 1 or the server 2. For example, it is assumed that the server 2 is a server that provides a bank account management service, and the information acquisition unit 141 acquires personal account data from the server 2. At this time, the information acquisition unit 141 may determine a one-year or one-month payroll transfer amount from the account data, and determine an individual's one-year or one-month expenditure based on the payroll transfer amount. In addition, it is assumed that the server 2 is a server that provides a household accounting service, and the information acquisition unit 141 acquires household accounting data from the server 2. At this time, the information acquisition unit 141 may determine the expenditure for one year or one month of the individual from the household account data. Of course, the information acquisition unit 141 may determine the income and expenditure of an individual using a method other than these. For example, the information acquisition unit 141 may determine the expenditure of the individual from the credit card use history of the individual. Also, the information acquisition unit 141 may determine personal income from household account data. The income and expenses may be directly input to the prediction device 10 by the individual using the terminal device 1. Hereinafter, the income and expenditure of each economic agent will be referred to as the “individual balance”.

  Further, the information acquisition unit 141 may acquire personal attribute information and personal behavior information from the terminal device 1 or the server 2. Attribute information is information (for example, demographic information or psychographic information) related to an attribute of an individual. For example, attribute information is information such as age, occupation, income, property, address, address of work, number of languages used, family structure, friend relationship, life cycle, values, lifestyle, character, preference and the like. In addition, the action information is information including an individual's action-related feature (or an element determining the action). For example, the action information is information on an interest in skill-up, information on an intention to change jobs, or information on a way of thinking about how to use an individual's money (saver, spender, etc.). Specifically, the action information is information such as purchase history, payment history, search history, history of attending school (for example, preparatory school, technical school), history of correspondence education, financial information (for example, household account data), etc. is there. If the server 2 is a server that functions as an SNS site, the information acquisition unit 141 may acquire personal attribute information based on self-introduction data input by the individual to the SNS site. In addition, if the server 2 is a server that implements a questionnaire, the information acquisition unit 141 may determine a feature related to an individual's behavior based on the questionnaire result, and acquire the determination result as individual's behavior information.

  The information acquisition unit 141 associates the information of the current individual balance of the individual with the identification information of the individual, and stores the information in the economic information storage unit 131. The individual whose information acquisition unit 141 is to acquire economic information may include an individual who performs an activity outside the set area. In this case, since the information acquisition unit 141 can later determine the information of the individual performing the activity in the setting area from among the plurality of pieces of information stored in the information acquisition unit 141, the identification information is Address or work address may be associated and stored. The same applies to the case where there are a plurality of setting areas. Of course, the information associated with the identification information may include attribute information other than the personal address or work address. Further, the information associated with the identification information may include behavior information.

  Next, the individual prediction unit 142 of the control unit 14 predicts the future economic state of the individual based on the current individual economic state of the individual who performs activities in the setting area (step S12). The future economic condition may be the economic condition of the individual (for example, the economic condition after 15 years) in a certain future year, or the economic condition of the individual over several years (for example, 30 years per year) Economic condition). The individual prediction unit 142 predicts the future economic status of all individuals who perform activities in the setting area among the plurality of individuals whose information is stored in the economic information storage unit 131. Whether all individuals who perform activities in the setting area are determined based on the address or work address of the individual associated with the identification information.

  At this time, the individual prediction unit 142 may predict the future individual balance of the individual based on the current individual balance of the individual performing the activity in the setting area. For example, the individual prediction unit 142 may calculate the individual's future individual balance by multiplying the current income and expenditure of the individual by a predetermined coefficient. The predetermined coefficient may be calculated based on the attribute information or the action information.

  For example, the individual prediction unit 142 calculates a coefficient by which the current income of the individual is multiplied (hereinafter referred to as an income coefficient) as follows.

  First, the individual prediction unit 142 extracts, from the attribute information and the action information, a consideration element considered to be highly correlated with income increase. The factor to be considered is, for example, an element for determining "whether or not there is an interest in skill up", "whether or not there is an intention to change jobs", "whether or not the number of languages used is more than a predetermined threshold" is there. The factor to be considered may be the attribute information such as “educational background” or “job history” as it is. At this time, the factor to be considered may be binary information or may be values of several levels such as 0, 1, and 2 (rank information). For example, the individual prediction unit 142 sets element values as “whether or not there is an interest in skill up”, “whether or not there is an intention to change jobs”, and “whether or not the number of used languages is equal to or more than a predetermined threshold”. A value of either “0” or “1” is given, and one of the element values “0”, “1” and “2” is given for “education history” and “job history”. Of course, consideration factors and factor values are not limited to the above.

  The individual prediction unit 142 determines the element value based on the attribute information or the action information. For example, the individual prediction unit 142 determines “whether or not there is an interest in skill up” based on the purchase history or the history of attending school to a preparatory school, vocational school, etc. (for example, payment history of tuition fees etc.) . In addition, the individual prediction unit 142 determines whether or not there is an intention to change jobs based on the search history of the Web page (for example, whether the number of times the change sites have been viewed within a predetermined period in the past is a threshold or more). . Further, the individual prediction unit 142 determines whether “the number of used languages is equal to or more than a predetermined threshold” based on the number of languages used in the page of the corresponding individual of the SNS site.

  Then, the individual prediction unit 142 calculates a revenue factor by weighting and adding a plurality of element values. The weights given to each element value are stored in advance in the prediction device 10. The weight may be determined, for example, by causing a computer to learn, as teacher data, the value of the consideration factor of a person who has actually made a profit in the past or in the past. At this time, an element having a high correlation with the income increase is given a large weight, and an element having a low correlation with the income increase is given a small weight. Note that the weight given to the element value may be determined by the prediction device 10 (for example, the individual prediction unit 142), or it may be determined by the device designer using another device (computer) in advance. It may be.

  In addition, the individual prediction unit 142 calculates a coefficient (hereinafter referred to as an expenditure coefficient) by which the current expenditure of the individual is multiplied, for example, as follows.

  First, the individual prediction unit 142 extracts, from the attribute information and the action information, a consideration factor that seems to be involved in the spending tendency of the individual. The factor to be considered is, for example, a factor for determining "whether or not it has a costly hobby", "whether it is a saver, a standard or a spender" and the like. At this time, the factor to be considered may be binary information or may be values of several levels such as 0, 1, and 2 (rank information). For example, the individual prediction unit 142 gives an element value of either “0” or “1” as to “whether or not the user has a costly hobby”, For "wasteful", any one of "0" "1" "2" is given as an element value. Of course, consideration factors and factor values are not limited to the above. The individual prediction unit 142 determines the element value based on the attribute information or the action information. For example, the individual prediction unit 142 determines the element value based on the payment history and the like.

  Then, the individual prediction unit 142 calculates an expenditure coefficient by weighting and adding a plurality of element values. The weights given to each element value are stored in advance in the prediction device 10. The weight is determined, for example, by causing a computer to learn, as teacher data, the value of the consideration factor of a person who has a high tendency to be wasted (or a person who has a high tendency to save) determined from the past settlement history. It is also good. Elements that are highly correlated with the spending trend are given greater weight, and elements that are less correlated with the spending trend are given less weight.

  The individual prediction unit 142 stores the calculated individual economic state (future income and expenses) in the individual economic storage unit 132 in association with individual identification information. When there are a plurality of setting areas, the individual prediction unit 142 may associate information indicating an area with each piece of identification information. The information indicating the area may be identification information of the area, or may be an address of a person or a work address.

  Next, the area prediction unit 143 of the control unit 14 predicts the future area economic condition of the set area based on the future economic condition of the individual predicted by the individual prediction unit 142 (step S13). If there are a plurality of setting areas, the area prediction unit 143 predicts the future economic status of each of the plurality of setting areas. The future economic condition may be the economic condition of the setting area in a certain future year (for example, the economic condition after 15 years), or the economic condition of the setting area over several years (for example, 30 per year) Economic condition of the year) may be. The area economic condition is, for example, future income and expenditure of the set area. Hereinafter, the income and expenses of the set area are referred to as "area balance".

  FIG. 9 is a diagram for explaining an area economic state. In the case of FIG. 9, 2016 is at present. In the area A, a user 1 with an income of 5 million yen, a user 2 with an income of 2 million yen, and a user 3 with an income of 100 million yen reside. In addition, there is a company Z in the area A, and a user 4 and the like with an income of 2,000,000 yen work. In area B, user 5 and the like with an income of 10 million yen live. The area income of area A comprised of users 1 to 4 is 50 billion, and the area income of area B comprised of users 5 is 100 billion. The area income is, for example, an accumulation of the income of the economic entity who lives or works in the area. Area income is also one of the area economic conditions.

  When this is 2031, area A is in a state where user 3 and the like having income of 120 million yen resided. In addition, Company Z continues in area A, and user 1 of income 6 million yen and user 4 and the like of income 3 million yen work. In area B, user 2 and the like with income of 1 million yen are in a state of residence. In 2031, the online market has grown to 10 billion yen. The area prediction unit 143 predicts that the area income of the area A is 75 billion and the area income of the area B is 5 billion based on the future economic condition of the individual predicted by the individual prediction unit 142. The individual prediction unit 142 may not predict the movement of the area of the individual. The area movement of the user 2 etc. in FIG. 9 is just an example. The area prediction unit 143 may predict the area economic state on the assumption that individuals do not move in the area.

  The area prediction unit 143 may calculate the future area balance of the set area based on the individual future individual balance calculated in step S12. If the income of all individuals who live or work in the set area is calculated in step S12, the area prediction unit 143 adds the sum of the plurality of incomes calculated in step S12 to the future income of the set area. It may be predicted as In addition, if the expenditure of all individuals who live or work in the set area is calculated in step S12, the area prediction unit 143 adds the sum of the plurality of expenditures calculated in step S12 to the future of the set area. It may be forecast as the expenditure of

  If the income of all individuals who live or work in the set area is not calculated at step S12, the area prediction unit 143 sets the average value and the set area of the future income of the plurality of users calculated at step S12. The future population of H may be multiplied as the future income of the set area. In addition, if the expenditures of all individuals who live or work in the setting area are not calculated in step S12, the area prediction unit 143 calculates the average value of the plurality of expenditures calculated in step S12 and the population of the setting area. It may be predicted as future expenditure of the setting area multiplied by. The population may be the current population or the population expected in the area in the future. In addition, the area prediction unit 143 may calculate the future area balance of the set area using a statistical method.

  The area prediction unit 143 stores the calculated area economic state (future area income and area expenditure) in the area economic storage unit 133. If there are a plurality of setting areas, the area prediction unit 143 calculates the area economic state of each area, and stores each of the plurality of area economic states in association with the identification information of the area.

  Next, the value prediction unit 144 of the control unit 14 predicts the future area value regarding the real estate in the set area based on the area economic state predicted by the area prediction unit 143 (step S14). If there are a plurality of setting areas, the value prediction unit 144 predicts the future area value of each of the plurality of setting areas. The future area value may be the area value of the setting area in a certain future year (for example, the area value after 15 years), or the area value of the setting area over several years (for example, 30 per year) Area value for the year may be). The area value may be the future real estate value (trading value) of real estate located in the set area. Also, the area value may be the future rent of the real estate in the set area, the tenant fee, the rental fee, or the parking lot rent.

  Also, the area value may be an index or an amount. For example, the area value may be a numerical value indicating the future value when the current value is 100. At this time, the area value may be a value calculated on the assumption that the price does not rise in consideration of the rise in the price.

  The value predicting unit 144 may calculate the future area value of the set area based on the area balance calculated at step S13. For example, the value prediction unit 144 may use the future income of the set area as it is as the future area value of the set area. In addition, the value prediction unit 144 may set an amount calculated by weighted addition of future income and future expenditure of the setting area as the future area value of the setting area. The value prediction unit 144 may convert the amount into an index.

  Also, the value prediction unit 144 may calculate the future area value of the set area based on the increase rate of the income and / or the expenditure. For example, the value prediction unit 144 calculates an increase rate of future income based on the current income of the set area (for example, “1”). For example, assuming that the current income of the set area is 50 billion yen and the future income is 75 billion yen, the value prediction unit 144 calculates the increase rate "1.5" of the future income. Similarly, the value prediction unit 144 calculates an increase rate (for example, “1.3”) of future expenditure based on the current expenditure of the set area. Then, the value prediction unit 144 performs weighted addition of the future income increase rate “1.5” of the set area and the increase rate “1.3” of the future expenditure. At this time, a weight of a higher value may be given to the income that is considered to be highly correlated with the real estate purchase. For example, a weight of 0.8 may be given to income and a weight of 0.2 may be given to expenditure. Then, the value prediction unit 144 may calculate a value obtained by multiplying the weight-added value by 100 as a future area value of the setting area.

  The value prediction unit 144 stores the calculated area value in the area value storage unit 134. If there are a plurality of setting areas, the area prediction unit 143 calculates the area economic state of each area, and stores the calculated area economic state in association with the identification information of the area.

  Subsequently, the value prediction unit 144 corrects the predicted area value based on macroeconomic information that affects the setting area (step S15). Macroeconomic information is macroscopic information such as the population growth rate of a set area. Macroeconomic information includes the change trend (rate of change) of the company located in the set area, the rate of increase in land value in the set area, the rate of increase in rent in the set area, the rate of increase in tenant charges in the set area, and the occurrence of earthquakes in the set area It may be the possibility and the possibility of occurrence of disaster in the setting area.

  The value prediction unit 144 may correct the area value by multiplying the area value calculated in step S15 by the coefficient calculated based on the macroeconomic information. For example, if the expected population increase rate in the future of the set area based on the current is 1.53, the value prediction unit 144 may calculate 1.53 as a coefficient. Then, the value prediction unit 144 may use the area value calculated in step S15 multiplied by 1.53 as the corrected area value. Also about "the increase and decrease trend (change rate) of the company located in the setting area", "the increase rate of the land price of the setting area", "the increase rate of the rent of the setting area" and "the increase rate of the tenant fee of the setting area" A process similar to the "population growth rate" of is applicable. For “probability of earthquake occurrence in the set area” and “probability of occurrence of disaster in the set area”, the information generation unit 145 may set, for example, coefficients 0.8, 1.0, and 1. according to the occurrence probability. It may be changed to 2 mag.

  If the area value predicted in step S14 is a real estate value (for example, the trading value of the land), the value prediction unit 144 selects the rate of increase of the land value of the set area as macroeconomic information for area value correction. You may In addition, if the area value predicted in step S14 is the future rent of a real estate or the tenant fee, the value forecasting unit 144 determines “rate of increase in rent in the set area” or “rate of increase in tenant fee in the set area” It may be selected as macroeconomic information for area value correction. In addition, the value prediction unit 144 may select macroeconomic information in accordance with the area value to be predicted. For example, if the area value predicted in step S14 is the future landlord charge and parking lot rent, the value prediction unit 144 sets the macroeconomic information used for correction to “rate of increase in landlord rent” or “parking lot rent”. The rate of increase may be used. These rates of increase may be rates of increase excluding price increases to facilitate the determination of the user's investment value.

  Next, the information generation unit 145 of the control unit 14 generates information to be output to the user based on the prediction result of the value prediction unit 144 (step S16). At this time, the value prediction unit 144 may use the index calculated in step S15 as the information to be output to the user as it is. In addition, the information generation unit 145 may use information in which a graph of indices of a plurality of years is output to the user. FIG. 10 is a diagram showing an output example of the area value. Specifically, FIG. 10 is a graph of the transition of the area value (index) of the area A and the area B when 2016 is 100. In the graph shown in FIG. 10, the value (the value assuming that the price does not increase) is calculated in consideration of the price increase. The user does not have to consider price increases, so the user can easily determine the actual investment value. In the example of FIG. 10, it can be seen that the area B has a low investment value since the index shows a decreasing trend. The information generation unit 145 outputs the generated information to the output unit 12. The information generation unit 145 may transmit the generated information to the terminal device 1 via the communication unit 11.

  When the output of the information is completed, the control unit 14 ends the area value calculation process.

[4. effect〕
According to the present embodiment, the prediction device 10 includes the individual prediction unit 142, the area prediction unit 143, and the value prediction unit 144. The individual prediction unit 142 predicts the future economic status of the economic entity based on the economic information of the economic entity operating in the set area. The value prediction unit 144 predicts the future area value regarding the real estate in the set area based on the future economic condition of the economic entity predicted by the individual prediction unit 142. The prediction device 10 further includes an area prediction unit 143. The area prediction unit 143 predicts the future area economic condition of the set area based on the future economic condition of the economic entity predicted by the individual prediction unit 142. At this time, the value prediction unit 144 predicts the future area value regarding the real estate in the set area based on the area economic state predicted by the area prediction unit 143.

  That is, the prediction device 10 predicts the future upsurge of the area based on the future economic condition of the economic entity, and predicts the future area value of the set area based on the prediction. Therefore, the prediction device 10 can accurately predict the future area value of the set area.

  In addition, the value prediction unit 144 corrects the predicted area value based on macroeconomic information that affects the setting area. The macroeconomic information includes the population increase rate of the set area, the increase and decrease trend of the company located in the set area, the increase rate of the land price of the set area, the increase rate of the set area rent, and the increase rate of the set area tenant fee At least one information selected from among the possibility of earthquake occurrence in the setting area and the possibility of disaster occurrence in the setting area is included.

  Since the correction is performed based on the macroeconomic information, the prediction device 10 can reduce the deviation of the area value from the reality, such as the predicted area value deviates from the actual state and falls excessively. As a result, the prediction device 10 can improve the prediction accuracy of the future area value of the set area.

  In addition, the value prediction unit 144 predicts the future real estate value of the real estate located in the set area based on the area economic state predicted by the area prediction unit 143. In addition, the value prediction unit 144 predicts the future rent, tenant fee, leased land fee, or parking lot rent of the real estate in the set area based on the area economic condition predicted by the area prediction unit 143.

  Thereby, the prediction device 10 can provide the user with various predictions regarding real estate.

  Also, the individual prediction unit 142 predicts the future individual balance of the economic entity based on the individual balance of the economic entity. Then, the area prediction unit 143 predicts the future area balance of the predetermined area based on the future individual balance of the economic entity predicted by the individual prediction unit. Then, based on the area balance predicted by the area prediction unit 143, the value prediction unit 144 predicts the future area value of real estate in the set area. The area prediction unit 143 predicts the future area balance of the predetermined area by integrating the future individual balances of the economic agent.

  Since the future area value is predicted based on the balance, the prediction device 10 can improve the prediction accuracy of the future area value of the set area.

  Also, the economic agent is an individual who lives or works in the set area. Then, the individual prediction unit 142 predicts the individual's future individual balance based on the individual's individual balance and the individual's attribute information or behavior information.

  Since the personal individual's attribute information or behavior information is used to predict the individual's future individual balance, the prediction device 10 can make the prediction accuracy of the future area value of the setting area high. The prediction device 10 can further improve the prediction accuracy of the future area value of the set area by using not only the individual who lives in the set area but also the information of the individual who works in the set area.

  Further, the individual prediction unit 142 predicts the individual's future individual balance by multiplying the current individual balance of the individual by a coefficient derived based on the attribute information or the behavior information of the individual. The attribute information includes at least one piece of information selected from among age, occupation, property, education, career, number of languages used. In addition, the action information includes at least one information selected from information on an interest in skill up, information on a career change intention, and information on a way of thinking about money.

  Thereby, the prediction device 10 can further improve the prediction accuracy of the future area value of the setting area.

  The prediction device 10 further includes an information acquisition unit 141. The information acquisition unit 141 identifies the economic entity performing the activity in the setting area based on the position information of the terminal device 1 owned by the economic entity, and the economic information of the economic entity performing the economic information of the identified economic entity in the setting area Acquire as information. The prediction device 10 can acquire the economic information of the economic entity performing the activity in the setting area with high accuracy.

[5. Modified example]
The above embodiment is an example, and various modifications and applications are possible.

  For example, in the above-described embodiment (step S12), the individual prediction unit 142 predicts the future economic state of the individual based on the current individual economic state of the individual who performs the activity in the setting area. However, the individual prediction unit 142 may predict the future economic status of the individual based on the past individual economic status of the individual performing the activity in the set area. The individual prediction unit 142 may predict the future economic state of the individual based on the current and past individual economic states of the individual who operates in the set area. At this time, the individual economic condition may be an individual balance.

  Further, in the above-described embodiment (step S12), the individual prediction unit 142 calculates the future expenditure of the individual based on the current expenditure of the individual. However, the individual prediction unit 142 may calculate future income based on the current and / or past income of the individual, and may calculate past expenditure based on the calculated future income.

  Further, in the above-described embodiment (step S13), the area prediction unit 143 predicts the future area economic state based on the future economic state of the individual. However, the area prediction unit 143 may predict the future area economic status based on the future economic status of a corporation (for example, a company) located in the set area. In addition, the area prediction unit 143 may predict the future area economic state based on the future economic states of the individual and the corporation located in the set area.

  When a corporation is added to the prediction of the area economic state, the area prediction unit 143 may take into consideration the transfer or disappearance of the corporation. For example, the area prediction unit 143 may predict the area economic state on the basis of the average number of years of relocation of a corporation (company) or the average lifetime of a corporation, as the target corporation is not in the set area after the average number of years. The entry of a new corporation into the set area is also considered. Therefore, the area prediction unit 143 may predict the area economic state on the assumption that there is a new corporation entry in the set area with a certain probability every year. The size of the corporation (the size of income and expenses) may be fixed. In addition, when a corporation moves or disappears, although the area economy is greatly reduced temporarily, it is considered that a substitute corporation will immediately enter the area. Rather, it is considered to be easy to enter. Therefore, the area prediction unit 143 may predict the area economic state as having a high probability of new entry.

  Further, in the above-described embodiment (step S13), the area prediction unit 143 predicts the future area economic state of the set area based on the future individual economic state of the individual who lives or works in the set area. The relationship between the setting area is considered to be different between an individual who lives in the setting area and an individual who works in the setting area. Therefore, the area prediction unit 143 may give different weights to individuals living in the setting area and individuals working in the setting area in predicting the area economic state. For example, if the future future income of the individual is integrated to be the future area income of the set area, the area prediction unit 143 may multiply the income of the individual who works in the set area by 0.5 before the integration. Good. At this time, the income of the individual who lives in the set area may remain unchanged. The same process can be applied to calculation of the spending of the set area. The prediction device 10 can predict the area economic state more accurately.

  Further, in the above-described embodiment (step S15), the value prediction unit 144 corrects the area value based on the macroeconomic information. However, the value prediction unit 144 may not necessarily correct the area value.

  The control device for controlling the prediction device 10 of the present embodiment may be realized by a dedicated computer system or may be realized by a normal computer system. For example, a program for executing the above-described operation is stored in a computer-readable recording medium such as an optical disk, semiconductor memory, magnetic tape, flexible disk, etc. and distributed, the program is installed in a computer, and the above-described processing is performed. The control device may be configured by execution. The control device may be an external device (for example, a personal computer) outside the prediction device 10 or an internal device (for example, the control unit 14). In addition, the program may be stored in a disk device provided in a server device on a network such as the Internet so that the program can be downloaded to a computer. In addition, the above-described functions may be realized by cooperation of an OS (Operating System) and application software. In this case, the part other than the OS may be stored in the medium and distributed, or the part other than the OS may be stored in the server apparatus and downloaded to the computer.

[6. Hardware configuration]
The prediction device 10 according to the embodiment and the modification can also be realized by, for example, a computer 1000 configured as shown in FIG. FIG. 11 is a hardware configuration diagram showing an example of a computer that implements the function of the prediction device 10. The computer 1000 includes a central processing unit (CPU) 1100, a RAM 1200, a ROM 1300, a hard disk drive (HDD) 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F). ) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 to control each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores a program executed by the CPU 1100, data used by the program, and the like. The communication interface 1500 receives data from another device via the network N, sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to the other device via the network N.

  The CPU 1100 controls output devices such as a display and a printer and input devices such as a keyboard and a mouse via the input / output interface 1600. The CPU 1100 acquires data from an input device via the input / output interface 1600. The CPU 1100 also outputs the generated data to the output device via the input / output interface 1600.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the CPU 1100 with the program via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700 and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a digital versatile disc (DVD) or a phase change rewritable disc (PD), an optical magnetic recording medium such as a magneto-optical disk (MO), a tape medium, a magnetic recording medium Etc.

  For example, when the computer 1000 functions as the prediction device 10 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 14 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from another device via the network N.

  Although some of the embodiments of the present application have been described in detail based on the drawings, these are only examples, and various modifications can be made based on the knowledge of those skilled in the art, including the aspects described in the rows of the disclosure of the invention. It is possible to implement the invention in other improved forms.

[7. Other]
Further, among the processes described in the above-described embodiments, all or part of the process described as being automatically performed may be manually performed, or the process described as being manually performed. All or part of can be performed automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above-mentioned documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

  Further, each component of each device illustrated is functionally conceptual, and does not necessarily have to be physically configured as illustrated. That is, the specific form of the distribution and integration of each device is not limited to the illustrated one, and all or a part thereof may be functionally or physically dispersed in any unit depending on various loads, usage conditions, etc. It can be integrated and configured.

  Moreover, it is possible to combine suitably each embodiment mentioned above in the range which does not contradict process content.

  In addition, the "section (module, unit)" described above can be read as "means" or "circuit". For example, the value prediction unit can be read as a value prediction means or a value prediction circuit.

DESCRIPTION OF SYMBOLS 1 ... Terminal device 2 ... Server 10 ... Prediction apparatus 11 ... Communications part 12 ... Output part 13 ... Storage part 131 ... Economic information storage part 132 ... Individual economic storage part 133 ... Area economic storage part 134 ... Area value storage part 14 ... Control Part 141 ... information acquisition part 142 ... individual prediction part 143 ... area prediction part 144 ... value prediction part 145 ... information generation part

Claims (16)

An individual prediction unit for predicting the future economic status of the economic entity based on the economic information of the economic entity operating in a predetermined area;
A value prediction unit that predicts the future area value of the predetermined area based on the future economic condition of the economic entity predicted by the individual prediction unit;
The prediction apparatus characterized by having. The area prediction unit further comprises an area prediction unit that predicts a future area economic condition of the predetermined area based on the future economic condition of the economic entity predicted by the individual prediction unit.
The value prediction unit predicts the future area value of the predetermined area based on the area economic condition predicted by the area prediction unit.
The prediction device according to claim 1, characterized in that: The value prediction unit predicts the future real estate value of the real estate located in the predetermined area based on the area economic condition predicted by the area prediction unit.
The prediction device according to claim 2, characterized in that: The value prediction unit predicts the future rent, tenant fee, land lease fee, or parking lot rent of real estate in the predetermined area based on the area economic condition predicted by the area prediction unit.
The prediction device according to claim 2, characterized in that: The individual prediction unit predicts the future individual balance of the economic entity based on the individual balance of the economic entity,
The area prediction unit predicts the future area balance of the predetermined area based on the future individual balance of the economic entity predicted by the individual prediction unit;
The value prediction unit predicts future area value regarding real estate of the predetermined area based on the area balance predicted by the area prediction unit.
The prediction device according to any one of claims 2 to 4, characterized in that. The area prediction unit predicts the future area balance of the predetermined area by integrating the future individual balances of the economic entity.
The prediction device according to claim 5, characterized in that: The economic entity is an individual who lives or works in the predetermined area.
The prediction apparatus of Claim 5 or 6 characterized by the above-mentioned. The individual prediction unit predicts a future individual balance of the individual based on the individual balance of the individual and attribute information or behavior information of the individual.
The prediction device according to claim 7, characterized in that: The individual prediction unit predicts the individual's future individual balance by multiplying the current individual balance of the individual by a coefficient derived based on attribute information or behavior information of the individual.
The prediction device according to claim 8, characterized in that: The attribute information includes at least one piece of information selected from among age, occupation, property, education, career, number of languages used, and the like.
The prediction device according to claim 9, characterized in that: The behavior information includes at least one piece of information selected from information on an interest in skill up, information on a career change intention, and information on a way of thinking about money.
The prediction device according to claim 9, characterized in that: The value prediction unit corrects the predicted area value based on macroeconomic information that affects the predetermined area.
The prediction device according to any one of claims 1 to 11, characterized in that: The macroeconomic information includes a population increase rate of the predetermined area, an increase and decrease trend of a company located in the predetermined area, an increase rate of land value of the predetermined area, an increase rate of rent of the predetermined area, and the predetermined value. At least one piece of information selected from the rate of increase in tenant charges in the area, the possibility of earthquake occurrence in the predetermined area, and the possibility of disaster occurrence in the predetermined area,
The prediction device according to claim 12, characterized in that. The economic entity of the economic entity performing activity in the predetermined area, identifying the economic entity performing the activity in the predetermined area based on the position information of the terminal device owned by the economic entity, and identifying the economic information of the identified economic entity in the predetermined area The information acquisition unit further acquired as information
The prediction device according to any one of claims 1 to 13, characterized in that: A prediction method performed by the prediction device,
An individual prediction step of predicting the future economic status of the economic entity based on the economic information of the economic entity operating in a predetermined area;
A value prediction step of predicting the future area value of the predetermined area based on the future economic condition of the economic entity predicted in the individual prediction step;
Forecasting method characterized in that it includes. An individual prediction procedure for predicting the future economic status of the economic entity based on the economic information of the economic entity operating in a predetermined area;
A value prediction procedure for predicting the future area value of the predetermined area based on the future economic condition of the economic entity predicted by the individual prediction procedure;
A prediction program that causes a computer to execute.

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