Information processing device, information processing method

Abstract

To provide an information processing device and an information processing method for predicting increases and decreases in natural capital stocks due to human activities and non-human ecosystem and non-ecosystem activities.SOLUTION: An information processing device 1 includes: an input unit for inputting a human influence parameter 2 influenced by a human activity and a natural environment parameter 3 influenced by non-human ecosystem and non-ecosystem activities; a computing unit that calculates a natural capital stock prediction value 8 from the human influence parameter and the natural environment parameter, using a function 7 representing an integration of an amount of change per unit time in natural capital stock, which has elements of internal factors 6 that may change over time and external factors 5 including the human influence parameter and the natural environment parameter; and an output unit for outputting the natural capital stock prediction value 8 calculated by the computing unit.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an information processing apparatus and an information processing method for predicting natural capital stocks.

Background Art

[0002] Conventionally, in the field of economics, production prediction has been performed using the Cobb-Douglas function, which assumes that production is carried out using human capital related to the amount of labor and artificial capital related to production facilities, etc. as production factors. However, in actual production activities, it is obvious that in addition to human capital and artificial capital, various natural capital stocks such as oil, natural gas, minerals, forests, soil, and marine resources are also input as production factors. A method for evaluating and predicting sustainable economic activities using an improved Cobb-Douglas type production function considering the input of natural capital stocks is known.

[0003] In the evaluation and prediction of sustainable economic activities using such an improved Cobb-Douglas type production function, it is necessary to consider the consumption and conservation of natural capital stocks due to human activities, or the increase and decrease of natural capital stocks due to climate change, wildfires, etc. caused by activities of natural phenomena other than humans. Among them, regarding climate change, a method of introducing a meteorological model that expresses the temperature rise of the atmosphere and the ocean due to the influence of greenhouse gases emitted by human economic activities and predicting the depletion of natural capital stocks due to warming is known.

[0004] Also, for example, Patent Document 1 discloses a method for predicting natural capital stocks using a linear model or a non-linear model with solar radiation amount, precipitation amount, etc. as explanatory variables.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

[0006] However, conventional predictions of natural capital stock, as described above, have room for improvement in predicting increases and decreases in natural capital stock due to human and non-human activities. Specifically, human activities include consumption such as mineral extraction and crop harvesting, as well as conservation such as afforestation, while non-human activities include depletion due to climate change and loss due to wildfires. Each of these events has its own corresponding time scale for the increase or decrease in natural capital stock.

[0007] The above-mentioned Patent Document 1 presents models that focus on specific events, and does not offer a technology to predict the increase or decrease of natural capital stock on various time scales resulting from human activities and various non-human natural phenomena.

[0008] Therefore, the object of the present invention is to provide an information processing device and an information processing method for predicting the increase or decrease of natural capital stock due to human activities, non-human ecosystems, and non-ecosystem activities. [Means for solving the problem]

[0009] To solve the above problems, the present invention provides an input unit that takes in human influence parameters affected by human activities, natural environment parameters affected by non-human ecosystems and non-ecosystem activities, and which changes over time. vinegar A calculation processing unit that calculates a predicted value of natural capital stock from the human influence parameter and the natural environment parameter using a function that represents the sum of the changes in natural capital stock per unit time, with internal factors and external factors consisting of the human influence parameter and the natural environment parameter as elements; and an output unit that outputs the predicted value of natural capital stock calculated by the calculation processing unit. A function estimation unit having an evaluation function and a minimum point operator, which estimates the function from observed measured values, Equipped with The input unit receives previously observed measured values ​​of human influence parameters, measured values ​​of natural environment parameters, and measured values ​​of natural capital stock. The evaluation function calculates the error such that the error between the predicted value of natural capital stock, calculated by inputting the measured values ​​of human influence parameters and natural environment parameters into the calculation processing unit, and the measured value of natural capital stock is minimized. The minimum point operator minimizes the output of the evaluation function, and the internal factor is a self-feedback of the predicted value of natural capital stock to avoid numerical divergence in the calculation processing unit. to of It is characterized by.

[0010] Furthermore, the present invention provides a step of (a) inputting human impact parameters affected by human activities and natural environment parameters affected by non-human ecosystems and non-ecosystem activities. and (b) Changes over time vinegar The step of calculating a predicted value of natural capital stock from the human influence parameter and the natural environment parameter using a function that represents the cumulative change in the amount of change of natural capital stock per unit time, with internal factors and external factors consisting of the human influence parameter and the natural environment parameter as elements. and (c) A step of outputting the predicted value of natural capital stock calculated in step (b) above. (d) The step of inputting previously observed measured values ​​of human impact parameters, measured values ​​of natural environment parameters, and measured values ​​of natural capital stock; (e) The step of calculating the predicted value of natural capital stock from the measured values ​​of human impact parameters and measured values ​​of natural environment parameters, and calculating the error such that the error with the measured value of natural capital stock is minimized. to have Furthermore, the aforementioned internal factors are self-feedback of the predicted natural capital stock to avoid numerical divergence in step (b) above. to of It is characterized by. [Effects of the Invention]

[0011] According to the present invention, it is possible to realize an information processing device and an information processing method that predict the increase or decrease of natural capital stock due to human activities, non-human ecosystems, and non-ecosystem activities.

[0012] This makes it possible to predict increases and decreases in natural capital stock across diverse timescales, resulting from human activities and various non-human natural phenomena, thereby improving the accuracy of production forecasts.

[0013] Other issues, configurations, and effects not mentioned above will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0014] [Figure 1] This is a block diagram showing the schematic configuration of an information processing device according to Embodiment 1 of the present invention. [Figure 2] Figure 1 is a sequence diagram showing the operation (processing) of the information processing device. [Figure 3] This graph shows the annual temperature fluctuations in a mixed forest. [Figure 4] This graph shows the annual variation in precipitation in a mixed forest. [Figure 5]It is a graph showing the annual variation of the consumption of mixed forests by humans. [Figure 6] It is a graph comparing the predicted annual variation values of the normalized vegetation index of mixed forests with no human consumption and with human consumption predicted using the information processing device of FIG. 1. [Figure 7] It is a block diagram showing the schematic configuration of the information processing device according to Example 2 of the present invention. [Figure 8] It is a sequence diagram showing the operation (processing) of the information processing device of FIG. 7. [Figure 9] It is a graph showing the measured annual variation of the temperature of a deciduous broad-leaved forest. [Figure 10] It is a graph showing the measured annual variation of the precipitation of a deciduous broad-leaved forest. [Figure 11] It is a graph showing the measured annual variation of the normalized vegetation index of a deciduous broad-leaved forest. [Figure 12] It is a graph comparing the predicted annual variation value of the normalized vegetation index of a deciduous broad-leaved forest predicted using the information processing device of FIG. 7 with the measured annual variation value. [Figure 13] It is a graph comparing the predicted annual variation value of the normalized vegetation index of a deciduous broad-leaved forest predicted using a conventional information processing device with the measured annual variation value. [Figure 14] It is a block diagram showing the schematic configuration of the information processing device according to Example 3 of the present invention. [Figure 15] It is a sequence diagram showing the operation (processing) of the information processing device of FIG. 14. [Figure 16] It is a flowchart showing the information processing method according to Example 1 of the present invention.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In each drawing, the same or functionally identical components are denoted by the same reference numerals, and repeated descriptions of overlapping parts are partially omitted.

[0016] Furthermore, in this specification, "human activity" means conscious human activity, and "natural environment" means information relating to ecosystems excluding non-ecosystems and conscious human activity. [Examples]

[0017] An information processing apparatus and information processing method according to Embodiment 1 of the present invention will be described with reference to Figures 1 to 6 and Figure 16.

[0018] First, the schematic configuration of the information processing device of this embodiment will be explained using Figures 1 and 2. Figure 1 is a block diagram showing the schematic configuration of the information processing device 1 of this embodiment. Figure 2 is a sequence diagram showing the operation (processing) of the information processing device 1 of Figure 1.

[0019] As shown in Figure 1, the information processing device 1 of this embodiment mainly comprises an input unit 4, a calculation processing unit 9, and an output unit 10.

[0020] Input unit 4 receives human influence parameters 2, which are affected by human activities, and natural environment parameters 3, which are affected by non-human ecosystems and ecosystem activities.

[0021] The calculation processing unit 9 calculates a predicted value of natural capital stock 8 using a function 7 that represents the sum of the changes in natural capital stock per unit time, with external factors 5 consisting of human influence parameters 2 and natural environment parameters 3 input to the input unit 4, and internal factors 6 that can change over time as its elements.

[0022] The output unit 10 outputs the predicted value 8 of natural capital stock calculated by the calculation processing unit 9 to the outside of the information processing device 1.

[0023] The input unit 4 can be, for example, a keyboard, mouse, sensor, or connection terminal for an external device, and the output unit 10 can be, for example, a display or connection terminal for an external device. The input unit 4 and the output unit 10 can be implemented using these I / O (Input / Output) devices. The calculation processing unit 9 can be implemented using a CPU (Central Processing Unit), etc.

[0024] Here, in order to avoid numerical divergence in the calculation processing unit 9, function 7 has as its elements the value obtained by adding the external factor 5 at the addition point 13 to the value obtained by adding the internal factor 6, which is obtained by branching the predicted natural capital stock value 8 at the extraction point 11 and assigning a negative sign 12 to it.

[0025] Figure 2 is a diagram illustrating an example of the operation (processing) of the information processing device 1, and is a sequence diagram showing the inputs provided to the information processing device 1 from the user 14 and the ground station antenna 15 that receives data from the artificial satellite.

[0026] First, user 14 inputs human impact parameters 2 related to the conservation or utilization of the natural capital stock under consideration into the input unit 4 of the information processing device 1, and ground station antenna 15 inputs natural environment parameters 3 based on received satellite data related to the natural capital stock under consideration into the input unit 4 of the information processing device 1.

[0027] Next, the input unit 4 inputs the human influence parameter 2 and the natural environment parameter 3 to the calculation processing unit 9.

[0028] The calculation processing unit 9 assigns a negative sign 12 to the internal factors 6 obtained by branching the external factors 5, consisting of human influence parameters 2 and natural environment parameters 3, and the predicted natural capital stock value 8 at the extraction point 11, and then inputs the added value of the external factors 5 and the internal factors 6 at the addition point 13 into a function 7 that represents the cumulative change in the natural capital stock per unit time, thereby calculating the predicted natural capital stock value 8. The time-series predicted natural capital stock value 8 is output from the calculation processing unit 9 to the output unit 10.

[0029] The output unit 10 then outputs the predicted natural capital stock value 8 to an external source (user 14 in Figure 2) of the information processing device 1, and completes the processing.

[0030] Furthermore, the calculation using function 7 is performed in a loop 16 as long as human impact parameter 2 and natural environment parameter 3 are input.

[0031] The above operations (processes) will be explained step by step using the flowchart in Figure 16.

[0032] First, in step S1, the human impact parameter 2 and the natural environment parameter 3 are input to the input unit 4.

[0033] Next, in step S2, the human impact parameter 2 and the natural environment parameter 3 are input to the calculation processing unit 9.

[0034] Next, in step S3, the natural capital stock forecast value 8 is branched to obtain an internal factor 6, to which a negative sign is assigned 12. The value obtained by adding this to the external factor 5, which consists of the human influence parameter 2 and the natural environment parameter 3, is input into a function 7 that represents the cumulative change in the natural capital stock per unit time, and the natural capital stock forecast value 8 is calculated.

[0035] Next, in step S4, it is determined whether or not human impact parameter 2 and natural environment parameter 3 have been input. If there is no input for human impact parameter 2 and natural environment parameter 3, the process proceeds to step S5. On the other hand, if there is input for human impact parameter 2 and natural environment parameter 3, the process returns to step S3 and steps S3 and S4 are repeated.

[0036] Next, in step S5, the time-series natural capital stock forecast value 8 is output from the calculation processing unit 9 to the output unit 10.

[0037] Finally, in step S6, the output unit 10 outputs the predicted value of natural capital stock 8 to the outside of the information processing device 1, and the process ends.

[0038] As a specific example of the information processing device 1 in this embodiment, we will explain the case in which a mixed forest, which is a forest consisting of two or more tree species, is considered as the natural capital stock. Let y(t) be the change in the mixed forest stock with respect to time t, and consider temperature x1(t) and precipitation x2(t) as natural environment parameters 3, and logging h(t) of the mixed forest as human influence parameter 2.

[0039] Assuming that the external factor 5 is represented by the function Φ(x1(t),x2(t),h(t)) and the function representing the rate of change of natural capital stock per unit time is represented by f, the predicted value of natural capital stock 8 obtained by the calculation processing unit 9 is given by equation (1) as the product of function f.

[0040]

number

[0041] Here, as an example, we assume that the function Φ representing external factor 5 and the function f representing the rate of change of natural capital stock per unit time are both linear equations, and give them in equation (2).

[0042]

number

[0043] In equation (2), Φ1, Φ2, and Φ3 are weights representing the function Φ of the external factor 5, and τ is a time constant representing the rate of change per unit time of the predicted natural capital stock 8 due to the external factor 5 and the internal factor 6.

[0044] Furthermore, if the time constant τ is set to a constant K as in equation (3), the model increases and decreases while ignoring the density effect of the natural capital stock. If it is set to be inversely proportional to the natural capital stock y(t) as in equation (4), the model takes into account the competition for resources consisting of external factors 5 and internal factors 6 due to density effects.

[0045]

number

[0046]

number

[0047] As specific examples of the natural environment parameter 3, Figure 3 shows the annual variation in temperature in a mixed forest 17, and Figure 4 shows the annual variation in precipitation in a mixed forest 18. Furthermore, as a specific example of the human impact parameter 2, Figure 5 shows the annual variation in consumption in a mixed forest 19. Inputting these into equation (2) and assuming the constant in equation (3) as the time constant τ, Figure 6 shows the predicted value of the mixed forest stock. Note that the mixed forest stock is evaluated here using the Normalized Density Variance Index (NDVI).

[0048] These natural environment parameters 3 and human impact parameters 2 are expected to be calculated from hyperspectral data measured by hyperspectral cameras mounted on artificial satellites and image data captured by high-resolution image sensors, etc., through signal processing such as principal component analysis and pattern recognition. However, they may also be calculated using measurement data from aircraft or drones, or data measured on the ground, not limited to artificial satellites.

[0049] Figure 6 shows the annual variation 20 of the normalized vegetation index for mixed forests without human consumption, calculated with the human impact parameter 2 set to zero, and the annual variation 21 of the normalized vegetation index for mixed forests with human consumption, calculated using the human impact parameter 2 given in Figure 5.

[0050] As described above, the information processing device 1 of this embodiment takes human influence parameters 2, which are affected by human activities, and natural environment parameters 3, which are affected by the activities of non-human ecosystems and non-ecosystems, as inputs, and uses a function 7 that represents the accumulation of the amount of change in natural capital stock per unit time to calculate a predicted value of natural capital stock 8 from the human influence parameters 2 and the natural environment parameters 3. Thus, it is possible to predict and provide results for the increase or decrease in natural capital caused by human activities and various activities of non-human natural phenomena. [Examples]

[0051] Referring to Figures 7 to 13, an information processing apparatus and information processing method according to Embodiment 2 of the present invention will be described.

[0052] First, the schematic configuration of the information processing device of this embodiment will be explained using Figures 7 and 8. Figure 7 is a block diagram showing the schematic configuration of the information processing device 1 of this embodiment. Figure 8 is a sequence diagram showing the operation (processing) of the information processing device 1 in Figure 7.

[0053] As shown in Figure 7, the information processing device 1 of this embodiment comprises, as its main components, an input unit 4, a calculation processing unit 9, an output unit 10, and a function estimation unit 30. It differs from the information processing device 1 of Embodiment 1 (Figure 1) in that it further comprises a function estimation unit 30.

[0054] The input unit 4 receives the measured values ​​22 of human influence parameters observed by the sensing means, the measured values ​​23 of natural environment parameters observed by the sensing means, and the measured values ​​24 of natural capital stock observed by the sensing means.

[0055] The calculation processing unit 9 calculates a predicted value of natural capital stock 8 using a function 7 that represents the sum of the changes in natural capital stock per unit time, with the elements being an external factor 25 consisting of measured human influence parameter values ​​22 and measured natural environment parameter values ​​23 input to the input unit 4, and an internal factor 6 that can change over time.

[0056] The function estimation unit 30 consists of an evaluation function 27 that calculates an error 26 from the measured value 24 of natural capital stock and the predicted value 8 of natural capital stock, and a minimum point operator 29 that finds the function form 28 that minimizes the error 26, and estimates the function 7 of the calculation processing unit 9 from the measured value observed by the sensing means.

[0057] Figure 8 is a diagram illustrating an example of the operation (processing) of the information processing device 1, showing the sequence of events when an input is provided from the satellite's ground station antenna 15 to the information processing device 1, and when the user 14 receives an output from the information processing device 1.

[0058] First, the ground station antenna 15 inputs the measured values ​​of human impact parameters 22, natural environment parameters 23, and natural capital stock 24, based on received satellite data relating to the natural capital stock under consideration, to the input unit 4 of the information processing device 1.

[0059] Next, the input unit 4 inputs the measured values ​​22 for human influence parameters and the measured values ​​23 for natural environment parameters to the calculation processing unit 9.

[0060] The calculation processing unit 9 assigns a negative sign 12 to the internal factors 6 obtained by branching the external factors 25, which consist of the measured human influence parameters 22 and the measured natural environment parameters 23, and the predicted natural capital stock value 8 at the extraction point 11. Then, at the addition point 13, it inputs the value obtained by adding the external factors 25 and the internal factors 6 into a function 7 that represents the accumulation of the change in natural capital stock per unit time, and calculates the predicted natural capital stock value 8. Subsequently, the calculation processing unit 9 inputs the time-series predicted natural capital stock value 8, and the input unit 4 inputs the measured natural capital stock value 24, into the function estimation unit 30.

[0061] In the function estimation unit 30, first, the predicted value 8 of the natural capital stock and the measured value 24 of the natural capital stock are input to the evaluation function 27 to calculate the error 26. Next, the error 26 is input to the minimum point operator 29 to calculate a function form 28 that minimizes the error 26. Finally, the function estimation unit 30 outputs the function form 28 and substitutes it 31 into the function 7 which represents the cumulative change in the natural capital stock per unit time.

[0062] These series of function estimation processes are looped 16 until the error 26 is minimized. After that, the calculation processing unit 9 inputs the predicted natural capital stock value 8 to the output unit 10, and the output unit 10 outputs the predicted natural capital stock value 8 to an external party (user 14 in Figure 8) of the information processing device 1, thus ending the process.

[0063] As a specific example of the information processing device 1 of this embodiment, we will explain the case in which deciduous broadleaf forests are considered as the natural capital stock, similar to the specific example of the information processing device 1 of Embodiment 1. We assume that the measured value ym(t) of the change in the deciduous broadleaf forest stock with respect to time t is obtained by sensing such as artificial satellites, and the measured values ​​of natural environment parameters 23, namely measured temperature x1m(t) and measured precipitation x2m(t), are obtained. Assuming that the extra-measurement factor 25 is represented by the function Φm(x1m(t), x2m(t)) and the function representing the amount of change in the natural capital stock per unit time is represented by f, the predicted value of the natural capital stock 8, expressed as y(t), obtained by the calculation processing unit 9 is given by equation (5).

[0064]

number

[0065] Here, the function estimation unit 30 first calculates the error E using equation (6) from the predicted value 8 of natural capital stock obtained by equation (5) and the measured value ym(t) of deciduous broadleaf forest stock in the evaluation function 27.

[0066]

number

[0067] Next, the function estimation unit 30 uses the minimum point operator 29 to determine the function f representing the rate of change of natural capital stock per unit time and the function Φm of extra-measurable factors using equation (7), so as to find the function form that minimizes the error E in equation (6).

[0068]

number

[0069] Thus, the information processing device 1 of this embodiment makes it possible to estimate the functional form related to the increase or decrease of natural capital stock, which is difficult to provide theoretically, based on observed values.

[0070] As specific examples of measured values ​​of natural environment parameters 23, Figure 9 shows the measured annual fluctuations of temperature in deciduous broadleaf forests 32, and Figure 10 shows the measured annual fluctuations of precipitation in deciduous broadleaf forests 33. In addition, as a specific example of measured values ​​of natural capital stock 24, Figure 11 shows the measured annual fluctuations of the normalized vegetation index in deciduous broadleaf forests 34.

[0071] Based on the information processing device 1 of this embodiment, a function 7 is estimated that represents the sum of the changes per unit time of natural capital stock, which gives a predicted natural capital stock value 8 when the measured annual temperature fluctuations 32 and the measured annual precipitation fluctuations 33 are considered non-measured factors 25.

[0072] For simplicity, we assume that the function Φm representing the extra-measurable factor 25 and the function f representing the rate of change of natural capital stock per unit time are both linear equations, and these are given in equation (8).

[0073]

number

[0074] In equation (8), Φ1m and Φ2m are weights representing the function Φm of the extra-measurable factors 25, and τm is a time constant representing the rate of change per unit time of the predicted natural capital stock 8 due to the extra-measurable factors 25 and the intrinsic factors 6.

[0075] Figure 12 shows a comparison between the measured annual fluctuation value 34 of the normalized vegetation index for deciduous broad-leaved forests and the predicted annual fluctuation value 35 of the normalized vegetation index for deciduous broad-leaved forests calculated using the information processing device 1 of this embodiment.

[0076] To illustrate the effects of the present invention, Figure 13 shows the results of prediction using only a linear model, without using function 7 which represents the cumulative change in natural capital stock per unit time, as disclosed in Patent Document 1. This is a comparison of the measured annual fluctuation value 34 of the normalized vegetation index of deciduous broadleaf forests and the predicted annual fluctuation value 36 of the normalized vegetation index of deciduous broadleaf forests calculated using a conventional information processing device. It can be seen that the prediction accuracy is lower compared to the results in Figure 12 because the time lag caused by function 7 which represents the cumulative change in natural capital stock per unit time is not properly reflected.

[0077] Thus, the information processing device 1 of this embodiment makes it possible to estimate the parameters that represent the optimal function form that minimizes the error between the predicted value and the measured value, based on the assumed function form (equation (8) in this example).

[0078] In the example shown in equation (8), it was assumed that the rate of change of natural capital stock per unit time is represented by a single time constant τm. However, as shown in equation (9), the function 7 representing the cumulative rate of change of natural capital stock per unit time may be expressed using two or more time constants τmi (i=1,2…).

[0079]

number

[0080] In equation (9), Φ1mi and Φ2mi (i=1,2…) are weights representing the functions Φm of the extra-measurable factors 25, and represent the contribution rates to the time change yi of natural capital stocks with different time scales expressed by the time constant.

[0081] This makes it possible to provide predictions of increases and decreases in natural capital stock across diverse timescales, resulting from human activities and various non-human natural phenomena. [Examples]

[0082] Referring to Figures 14 and 15, an information processing apparatus and information processing method according to Embodiment 3 of the present invention will be described.

[0083] Figure 14 is a block diagram showing the schematic configuration of the information processing device 1 in this embodiment. Figure 15 is a sequence diagram showing the operation (processing) of the information processing device 1 in Figure 14.

[0084] As shown in Figure 14, the information processing device 1 of this embodiment comprises, as its main components, an input unit 4, a calculation processing unit 9, an output unit 10, and a production function 41. It differs from the information processing device 1 of Embodiment 1 (Figure 1) in that it further comprises a production function 41.

[0085] Input unit 4 receives the following parameters: human influence parameter 2, which is affected by human activities; natural environment parameter 3, which is affected by non-human ecosystems and ecosystem activities; human capital parameter 37, which is related to the amount of labor; artificial capital parameter 38, which is related to production equipment; and productivity parameter 39, which is related to technological and institutional innovation.

[0086] The production function 41 calculates a predicted output value 40 of the product obtained when the predicted natural capital stock value 8 calculated by the calculation processing unit 9, the human capital parameter 37, the artificial capital parameter 38, and the productivity parameter 39 are used as production factors.

[0087] The output unit 10 outputs the predicted value 8 of natural capital stock calculated by the calculation processing unit 9 and the predicted value 40 of the output of products calculated by the production function 41 to the outside of the information processing device 1.

[0088] Figure 15 is a diagram showing an example of the operation (processing) of the information processing device 1, and is a sequence diagram showing the process when input is provided from the artificial intelligence 42 to the information processing device 1 following a problem presentation 43 from the user 14 to the artificial intelligence 42.

[0089] First, the artificial intelligence 42 inputs the following parameters into the input unit 4 of the information processing device 1: a human impact parameter 2 related to the conservation or utilization of the natural capital stock under consideration, a natural environment parameter 3, a human capital parameter 37 related to the amount of labor required to produce products using the natural capital stock, an artificial capital parameter 38 related to production equipment, and a productivity parameter 39 related to technological and institutional innovation.

[0090] Next, the input unit 4 inputs the human influence parameter 2 and the natural environment parameter 3 to the calculation processing unit 9.

[0091] The calculation processing unit 9 assigns a negative sign 12 to the internal factors 6 obtained by branching the external factors 5, which consist of human influence parameters 2 and natural environment parameters 3, and the predicted natural capital stock value 8 at the extraction point 11. Then, at the addition point 13, it inputs the value obtained by adding the external factors 5 to the function 7, which represents the cumulative change in the natural capital stock per unit time, and calculates the predicted natural capital stock value 8. Subsequently, the calculation processing unit 9 inputs the predicted natural capital stock value 8 to the production function 41 and the output unit 10.

[0092] Here, in addition to the predicted value of natural capital stock 8, the human capital parameter 37, the artificial capital parameter 38, and the productivity parameter 39 are input to the production function 41 from the input unit 4.

[0093] As a result, the production function 41 calculates a predicted output value 40 of the product and inputs it to the output unit 10.

[0094] The output unit 10 outputs the natural capital stock forecast value 8 and the output forecast value 40 to the outside of the information processing device 1 (artificial intelligence 42 in Figure 15).

[0095] Based on the given problem presentation 43, the artificial intelligence 42 adjusts the human influence parameter 2, the natural environment parameter 3, the human capital parameter 37, the artificial capital parameter 38, and the productivity parameter 39 until the presented problem is solved, inputs them to the information processing device 1, and performs loop 16 calculations.

[0096] Finally, the artificial intelligence 42 presents the human influence parameter 2, natural environment parameter 3, human capital parameter 37, artificial capital parameter 38, productivity parameter 39, natural capital stock prediction value 8, and product output prediction value 40 output from the information processing device 1 to the user 14, and then completes the process.

[0097] Here, the production function 41 is the improved Cobb-Douglas production function described above, and is given by equation (10) when the human capital parameter is L, the artificial capital parameter is K, the productivity parameter is A, the predicted value of natural capital stock is S, and the predicted value of output is Q.

[0098]

number

[0099] In equation (10), α1 to α3 are values ​​between 0 and 1, and represent the distribution rates of production factors to the output obtained using the natural capital stock under consideration.

[0100] As described above, the information processing device 1 of this embodiment takes human influence parameters affected by human activities, natural environment parameters affected by non-human ecosystem and non-ecosystem activities, human capital parameters related to the amount of labor required to produce products using natural capital stock, artificial capital parameters related to production equipment, and productivity parameters related to technological and institutional innovation as input to calculate predicted values ​​for natural capital stock and predicted values ​​for production volume. Thus, it can predict and provide results for the increase or decrease in natural capital resulting from various activities of human activities and non-human natural phenomena, while taking economic impacts into consideration.

[0101] It should be noted that the present invention is not limited to the embodiments described above, and various modifications are included. For example, the embodiments described above are described in detail to make the present invention easier to understand, and are not necessarily limited to those having all the configurations described. Furthermore, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add configurations from other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace parts of the configuration of each embodiment with other configurations.

[0102] Furthermore, each of the above configurations, functions, processing units, and processing means may be implemented in hardware, either partially or entirely, by designing them as integrated circuits, for example. Alternatively, each of the above configurations and functions may be implemented in software by having the processor interpret and execute programs that implement each function. Information such as programs, tables, and files that implement each function can be stored in memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD. [Explanation of Symbols]

[0103] 1...Information processing device, 2...Human influence parameters, 3...Natural environment parameters, 4...Input unit, 5...External factors, 6...Internal factors, 7...Function representing the accumulation of the change in natural capital stock per unit time, 8...Predicted value of natural capital stock, 9...Calculation processing unit, 10...Output unit, 11...Lead point, 12...Negative sign addition, 13...Addition point, 14...User, 15...Ground station antenna, 16...Loop, 17...Annual variation of temperature in mixed forest, 18...Annual variation of precipitation in mixed forest, 19...Annual variation of consumption in mixed forest, 20...Annual variation of normalized vegetation index in mixed forest without human consumption, 21...Annual variation of normalized vegetation index in mixed forest with human consumption, 22...Measured value of human influence parameters, 23 …Measured values ​​of natural environment parameters, 24…Measured values ​​of natural capital stock, 25…External factors, 26…Error, 27…Evaluation function, 28…Function form, 29…Minimum point operator, 30…Function estimation unit, 31…Substitution, 32…Measured annual fluctuations of temperature in deciduous broadleaf forests, 33…Measured annual fluctuations of precipitation in deciduous broadleaf forests, 34…Measured annual fluctuations of normalized vegetation index in deciduous broadleaf forests, 35…Predicted annual fluctuations of normalized vegetation index in deciduous broadleaf forests, 36…Predicted annual fluctuations of normalized vegetation index in deciduous broadleaf forests by conventional information processing equipment, 37…Human capital parameters, 38…Artificial capital parameters, 39…Productivity parameters, 40…Predicted output values, 41…Production function, 42…Artificial intelligence, 43…Problem presentation.

Claims

1. An input section for inputting human impact parameters affected by human activities, and natural environment parameters affected by non-human ecosystems and non-ecosystem activities, A calculation processing unit that calculates a predicted value of natural capital stock from the human influence parameter and the natural environment parameter, using a function that represents the accumulation of the amount of change per unit time of natural capital stock, with elements being internal factors that change over time and external factors consisting of the human influence parameter and the natural environment parameter. An output unit that outputs the natural capital stock forecast value calculated by the calculation processing unit, A function estimation unit having an evaluation function and a minimum point operator, which estimates the function from observed measured values, Equipped with, The input unit receives the previously observed measured values ​​of human influence parameters, measured values ​​of natural environment parameters, and measured values ​​of natural capital stock. The evaluation function calculates the error such that the error between the predicted value of natural capital stock, which is calculated by inputting the measured values ​​of the human impact parameter and the measured values ​​of the natural environment parameter into the calculation processing unit, and the measured value of natural capital stock is minimized. The minimum point operator minimizes the output of the evaluation function, The information processing apparatus is characterized in that the aforementioned internal factor is a self-feedback of the natural capital stock forecast value to avoid numerical divergence in the calculation processing unit.

2. An input unit for inputting human impact parameters affected by human activities, and natural environment parameters affected by non-human ecosystems and non-ecosystem activities, A calculation processing unit that calculates a predicted value of natural capital stock from the human influence parameter and the natural environment parameter, using a function that represents the accumulation of the amount of change per unit time of natural capital stock, with elements being internal factors that change over time and external factors consisting of the human influence parameter and the natural environment parameter. An output unit that outputs the natural capital stock forecast value calculated by the calculation processing unit, A production function that calculates the predicted output of a product obtained when the aforementioned predicted natural capital stock, a human capital parameter related to the amount of labor, an artificial capital parameter related to production equipment, and a productivity parameter related to technological or institutional innovation are used as factors of production, Equipped with, The information processing apparatus is characterized in that the aforementioned internal factor is a self-feedback of the natural capital stock forecast value to avoid numerical divergence in the calculation processing unit.

3. (a) A step of inputting human impact parameters that are affected by human activities, and natural environment parameters that are affected by non-human ecosystems and non-ecosystem activities, (b) A step of calculating a predicted value of natural capital stock from the human influence parameter and the natural environment parameter using a function that represents the sum of the changes in the amount of natural capital stock per unit time, with the elements being internal factors that change over time and external factors consisting of the human influence parameter and the natural environment parameter, (c) A step of outputting the predicted value of the natural capital stock calculated in step (b), (d) A step of inputting previously observed measured values ​​of human impact parameters, measured values ​​of natural environment parameters, and measured values ​​of natural capital stock, (e) A step of calculating the predicted value of natural capital stock from the measured values ​​of the human impact parameter and the measured values ​​of the natural environment parameter, and calculating the error such that the error with the measured value of natural capital stock is minimized, It has, The information processing method is characterized in that the aforementioned internal factors are self-feedback of the natural capital stock forecast values ​​to avoid numerical divergence in step (b).

4. (a) A step of inputting human impact parameters that are affected by human activities, and natural environment parameters that are affected by non-human ecosystems and non-ecosystem activities, (b) A step of calculating a predicted value of natural capital stock from the human influence parameter and the natural environment parameter using a function that represents the sum of the changes in the amount of natural capital stock per unit time, with the elements being internal factors that change over time and external factors consisting of the human influence parameter and the natural environment parameter, (c) A step of outputting the predicted value of the natural capital stock calculated in step (b), (d) A step of calculating a predicted output of a product obtained when the predicted natural capital stock, a human capital parameter related to the amount of labor, an artificial capital parameter related to production equipment, and a productivity parameter related to technological or institutional innovation are used as factors of production, It has, The information processing method is characterized in that the aforementioned internal factors are self-feedback of the natural capital stock forecast values ​​to avoid numerical divergence in step (b).

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