JP7416394B2 - Cropping schedule calculation device, cropping schedule calculation program, and cropping schedule calculation method - Google Patents

Description

The present disclosure relates to a technique for calculating a crop planting schedule.

Techniques for predicting crop harvest conditions using statistical methods, machine learning, etc. are known. In the technology disclosed in Patent Document 1, the heading date of rice is predicted by machine learning using weather information. The yield of rice is then predicted by machine learning using weather information on days determined based on the heading date. Furthermore, the quality of rice can be predicted by multiple regression analysis using the weather information. According to this technology, the harvest status of crops such as rice can be predicted with high accuracy.

JP2017-163956A

However, there may be cases where the demand for crops and the yield do not match. In such a case, there is a risk that there will be an oversupply of crops, leading to crop destruction and a fall in prices, or conversely, a shortage of crop supply.

One aspect of the present disclosure preferably balances crop demand and yield.

A planting schedule calculation device according to one aspect of the present disclosure calculates at least one planting date for a crop and a planting amount that is the amount of the crop to be planted on the planting date. Here, x _i (i is an integer from 1 to n) is a variable indicating each of the planting dates for n days (n is a predetermined integer greater than or equal to 1), and w is a variable indicating the amount of cropping at x _i . _i , y is a variable indicating the harvest date, which is the day on which crops are harvested, u is a variable indicating a variable factor in the demand for crops, z is a variable indicating the growing environment of crops, and H0 is a predetermined threshold value. The cropping schedule calculation device includes an acquisition section and a calculation section. The acquisition unit acquires the values of y, u, and z. Further, the calculation unit calculates x _i and w _i that satisfy equation (1) when y, u, and z are values acquired by the acquisition unit.

なお、ｇ（ｙ、ｕ）は、ｙ、ｕを説明変数とする数理モデルを表す関数であり、収穫日ｙに収穫された作物の需要量の予測値を算出する。また、ｆ（ｘ_ｉ、ｙ、ｚ）は、ｘ_ｉ、ｙ、ｚを説明変数とする数理モデルを表す関数であり、作物の単位作付量の作付から得られる、ｙにおける収穫量の予測値を算出する。

Note that g(y, u) is a function representing a mathematical model using y and u as explanatory variables, and calculates a predicted value of the demand amount of crops harvested on harvest day y. In addition, f(x _i , y, z) is a function representing a mathematical model using x _i , y, z as explanatory variables, and is a predicted value of the yield at y obtained from planting a unit crop amount of the crop. Calculate.

According to the above configuration, the solution of x _i and w _i in equation (1) corresponds to the planting date and planting amount at which the difference between the demand amount and the harvest amount of the crop is equal to or less than H0. Therefore, by determining at least one planting date and planting amount based on the solutions of x _i and w _i , it is possible to bring the crop yield closer to the demand amount. Therefore, it is possible to balance the demand for crops with the amount of harvest.

Alternatively, a value indicating each harvest date for m days (m is an integer of 1 or more) may be set to y _j (j is an integer of 1 or more and m or less). Further, the acquisition unit may acquire m y _j (in other words, y ₁ to y _m ) as the value of y. Further, the calculation unit is configured to calculate x i that satisfies m equations (2) in which the values of u and z acquired by the acquisition unit are set, and y ₁ to y _m are respectively set as the value of _y. x _i and w _i that satisfy equation (1) may be calculated by calculating and w _i .

つまり、式（２）は、式（１）におけるｙの値に、離散的な１又は複数の収穫日であるｙ_ｊを設定することで得られ、式（２）におけるｘ_ｉ、ｗ_ｉの解は、離散的な１又は複数の収穫日において式（１）を充足する作付日及び作付量となる。このため、ｘ_ｉ、ｗ_ｉの解に基づき少なくとも１つの作付日及び作付量を決定することで、離散的な１又は複数の収穫日の各々において、作物の収穫量を需要量に近づけることができる。したがって、作物の需要量と収穫量との調和を取ることができる。

In other words, equation (2) is obtained by setting y _j , which is one or more discrete harvest dates, to the value of y in equation (1), and x _i and w _i in equation (2) are The solution is a planting date and a planting amount that satisfy Equation (1) at one or more discrete harvest dates. Therefore, by determining at least one planting date and planting amount based on the solutions of x _i and w _i , it is possible to bring the crop yield closer to the demand amount on each of one or more discrete harvest dates. can. Therefore, it is possible to balance the demand for crops with the amount of harvest.

In addition, according to the above configuration, the harvest amount of crops on a specific day can be brought close to the demand amount, so that the demand amount and harvest amount of crops, whose demand fluctuates rapidly on a specific day or time of the year, can be harmonized. It is suitable for taking.

Further, the harvest date is a harvest period of m consecutive days (m is an integer of 1 or more), and the first day of the harvest period may be y _s and the last day may be _ye . Further, the acquisition unit may acquire the harvest period as the value of y by acquiring y _s and ye _e . Furthermore, the calculation unit calculates x i _{and w i} that satisfy _equation (1) by calculating x i and _{w i} that satisfy equation (3) for n cases where i is 1 to n. You can also calculate it.

なお、式（３）におけるＨは、以下の式（４）により算出されても良い。

Note that H in equation (3) may be calculated using equation (4) below.

式（４）におけるｕ及びｚには、取得部により取得された値が設定されても良い。また、ｈは１以上の整数であっても良い。

Values acquired by the acquisition unit may be set to u and z in Equation (4). Further, h may be an integer of 1 or more.

In other words, Equation (4) integrates the h-th power of the left side of Equation (1) over the harvest period from y _s to y _e , which are consecutive harvest days. By calculating x _i and w _i that minimize H, it is possible to calculate x _i and w _i that satisfy formula (1) on average during the harvest period. Therefore, in the above configuration, x i and _{w i} that minimize H are calculated by solving equation (3) for each case where i is 1 to n.

Therefore, by determining at least one planting date and planting amount based on the solutions of x _i and w _i obtained from equation (3), the average crop yield can be adjusted to the average crop yield during the harvest period. It is possible to get close to the demand quantity. Therefore, it is possible to balance the demand for crops with the amount of harvest.

Further, according to the above configuration, it is possible to bring the harvest amount of crops closer to the demand amount on average during the harvest period. For this reason, it is suitable for achieving a balance between the demand amount and the harvest amount of crops whose demand amount fluctuates relatively small, such as crops sold at large-scale stores such as major supermarkets.

Note that one aspect of the present disclosure may be a cropping schedule calculation program that uses a computer to implement the functions realized by the cropping schedule calculation device. Further, one aspect of the present disclosure may be a cropping schedule calculation method realized by the cropping schedule calculation device.

It is a block diagram of a cropping schedule calculation device. It is a graph showing an example of a mathematical model showing the yield of crops. It is a graph which shows an example of the mathematical model which shows the demand amount of crops. 2 is a flowchart of cropping schedule calculation processing 1 performed by solution method 1. 12 is a flowchart of cropping schedule calculation processing 1 performed by solution method 2.

Embodiments of the present disclosure will be described below with reference to the drawings. Note that the embodiments of the present disclosure are not limited to the embodiments described below, and may take various forms as long as they fall within the technical scope of the present disclosure.

[1. Overall configuration]
A cropping schedule calculation device 10 shown in FIG. 1 calculates a cropping schedule for a specific crop in order to harmonize the supply amount and demand amount of the crop. Note that the planting schedule means at least one planting date for a crop and a planting amount, which is the amount of the crop to be planted on the planting date.

The crops may be, for example, grains, vegetables, fruits, or ornamental flowers. Moreover, cropping means, for example, planting or sowing of crops. In other words, planting means to start cultivating crops on farmland, plant factories, etc. Furthermore, various forms of crop cultivation are assumed, such as alley cultivation, greenhouse horticulture, and cultivation in a plant factory. Furthermore, crops may be cultivated at one location or at multiple locations.

The cropping schedule calculation device 10 shown in FIG. 1 is configured by a PC as an example, and includes a storage section 11, a control section 12, a communication section 13, a display section 14, and an operation section 15.
The storage unit 11 includes a rewritable nonvolatile storage device such as a flash memory or an HDD. The storage unit 11 corresponds to a non-transitional physical recording medium. The storage unit 11 stores a cropping schedule calculation program, which is an application installed in the cropping schedule calculation device 10.

The control unit 12 includes a well-known computer having a CPU and semiconductor memory such as ROM, RAM, and flash memory. The CPU operates according to a program stored in the semiconductor memory.

The communication unit 13 is a part for accessing a network such as the Internet. In the cropping schedule calculation device 10, the communication unit 13 transmits and receives information via the network.

The display unit 14 has a liquid crystal display or the like, and displays images in accordance with instructions from the control unit 12.
The operation unit 15 includes a keyboard, a mouse, etc., and accepts various operations.

In the cropping schedule calculation device 10 , the cropping schedule calculation program stored in the storage unit 11 is loaded into the RAM of the control unit 12 . The CPU of the control unit 12 operates according to the cropping schedule calculation program, thereby realizing the function of the cropping schedule calculation device 10.

[2. About mathematical models]
The cropping schedule calculation device 10 uses a mathematical model that calculates a predicted value of crop yield (hereinafter referred to as a yield amount model) and a mathematical model that calculates a predicted value of crop demand (hereinafter referred to as a demand amount model). Then, calculate the planting schedule. Hereinafter, a variable indicating the planting date will be referred to as x, and a variable indicating the harvesting date, which is the day on which the crop will be harvested, will be referred to as y.

FIG. 2 shows an example of a yield model that predicts the daily yield of crops planted on planting date x. The vertical axis of the yield model represents the harvest amount q, and the horizontal axis represents the harvest date y. The yield model is expressed by the function of equation (5) below.

収穫量モデルは、例えば機械学習や時系列分析や回帰分析等といった統計的手法を用いて、複数年にわたる作物の生育環境及び収穫量等の変化を示すデータを解析することで得られた数理モデルである。収穫量モデルは、所定の作付日ｘにおける単位作付量の作物の作付けにより得られる、収穫日ｙにおける収穫量を予測する。式（５）の収穫量モデルは、ｘ及びｙと、作物の生育環境を示すｚとを説明変数としている。つまり、収穫量モデルは、作物の生育環境を考慮して収穫量を予測する。

A yield model is a mathematical model obtained by analyzing data showing changes in the growing environment and yield of crops over multiple years using statistical methods such as machine learning, time series analysis, and regression analysis. It is. The yield model predicts the yield on a harvest date y obtained by planting a unit crop amount of a crop on a predetermined planting date x. The yield model of Equation (5) uses x, y, and z, which indicates the growing environment of the crop, as explanatory variables. In other words, the yield model predicts the yield by considering the growing environment of the crop.

The growing environment indicated by z includes, for example, weather information (e.g., temperature, humidity, amount of sunlight, etc.) during the crop cultivation period (in other words, the period from the planting date to the harvest date), and the weather information given to the crop. It may also be the amount of water or carbon dioxide, the status of fertilization or top-dressing, etc. Furthermore, the growing environment may refer to, for example, the soil in which crops are cultivated, the planting method, and the like. Moreover, z may indicate the growing environment on each day during the cultivation period, or may indicate the growing environment during a period spanning a plurality of days during the cultivation period. Further, equation (5) may predict the harvest amount q using a plurality of explanatory variables z indicating the growing environment of the crop.

On the other hand, FIG. 3 shows an example of a demand quantity model that predicts the demand quantity of crops harvested on harvest day y. The vertical axis of the demand quantity model indicates the demand quantity r, and the horizontal axis indicates the harvest date y. Note that the harvest date of a crop and the day on which the crop is distributed (hereinafter referred to as distribution date) may be the same or different. If the harvest date and distribution date of a crop are the same, the demand amount model may predict the daily demand amount of the crop. On the other hand, if the harvest date and distribution date of a crop are different, the demand model predicts the distribution date demand for the crop harvested on harvest day y as the demand for the crop harvested on harvest day y. It may be something that you do.

The demand model is expressed by the function of equation (6) below.

需要量モデルは、例えば機械学習や時系列分析や回帰分析等といった統計的手法を用いて、複数年にわたる作物の需要量及び需要量の変動要因等の変化を示すデータを解析することで得られた数理モデルである。需要量モデルは、収穫日ｙと、需要量の変動要因を示すｕとを説明変数としている。

A demand model is obtained by analyzing data showing changes in crop demand and demand variation factors over multiple years, using statistical methods such as machine learning, time series analysis, and regression analysis. This is a mathematical model. The demand quantity model uses the harvest date y and u, which indicates the fluctuation factor of the demand quantity, as explanatory variables.

Note that the variable factor indicated by u may indicate, for example, the climate of the year in which the demand for the crop is predicted, the region where the crop is consumed, or the like. Further, equation (6) may be used to predict the demand amount r using a plurality of explanatory variables u indicating factors of variation in the demand amount.

[3. How to calculate the planting schedule]
The cropping schedule calculation device 10 calculates the cropping schedule by calculating the values of x _i and w _i that make the difference between the harvest amount q and the demand amount r smaller based on equations (5) and (6). . Here, x _i (i is an integer greater than or equal to 1 and less than or equal to n) is a variable indicating each of n days' worth of planting days (n is a predetermined integer greater than or equal to 1). Note that n may be an integer of 2 or more. Moreover, w _i is a variable indicating the cropping amount at x _i .

The cropping schedule calculation device 10 acquires the values of y, u, and z, and calculates x _{i and} w _i that satisfy equation (7) when y, u, and z are the acquired values. , calculate the planting schedule.

なお、Ｈ０は、予め定められた閾値である。Ｈ０は、一例として０であっても良い。すなわち、ｙ、ｕ、及びｚが上記値である場合の式（８）によりｘ_ｉ、ｗ_ｉを算出することで、作付スケジュールが算出されても良い。

Note that H0 is a predetermined threshold value. H0 may be 0, for example. That is, the cropping schedule may be calculated by calculating x _i and w _i using equation (8) when y, u, and z are the above values.

式（７）又は式（８）によりｘ_ｉ、ｗ_ｉを算出する方法として、後述する解法１と解法２とが考えられる。作付スケジュール算出装置１０は、解法１及び解放２の双方又は一方により、作付スケジュールを算出する。なお、作付スケジュール算出装置１０は、解法１及び解法２以外の方法で式（７）又は式（８）に基づきｘ_ｉ、ｗ_ｉを算出することで、作付スケジュールを算出しても良い。

Solution method 1 and solution method 2, which will be described later, are possible methods for calculating x _i and w _i using equation (7) or equation (8). The cropping schedule calculation device 10 calculates the cropping schedule using both or one of Solution 1 and Release 2. Note that the cropping schedule calculation device 10 may calculate the cropping schedule by calculating x _i and w _i based on equation (7) or equation (8) using a method other than solution method 1 and solution method 2.

[4. Regarding solution 1]
In solution method 1, the harvest date yj (j is an integer of 1 or more and m or less) for m discrete days (m is a predetermined integer of 1 or more) is used as the value of y. Note that m may be an integer of 2 or more. Below, cropping schedule calculation process 1 for calculating a cropping schedule using solution method 1 will be explained using the flowchart of FIG. 4. This process is executed by the control unit 12 of the cropping schedule calculation device 10 operating according to the cropping schedule calculation program. Furthermore, the cropping schedule calculation process 1 realizes the cropping schedule calculation method using the solution method 1.

In S100, the control unit 12 obtains y1 to ym, which are m days of discrete harvest dates, as the value of y, and also obtains the values of u and z. Specifically, for example, the control unit 12 may obtain the values of y, u, and z by receiving input from the user via the operation unit 15. Further, for example, the control unit 12 may obtain the values of y, u, and z from an external server, PC, etc. via the communication unit 13. Further, for example, the control unit 12 may acquire these values by reading out the values of y, u, and z that have been stored in advance from the storage unit 11. In this case, the values of y, u, and z stored in the storage unit 11 may be provided from an external server, PC, etc. via the communication unit 13, or may be provided from an external server or PC via the communication unit 13, or The information may be input by the user via 15.

In subsequent S105, the control unit 12 solves m equations (9) in which the values of u and z and y1 to ym are respectively set as simultaneous inequalities, or solves m equations (9) in which the values of u and z and y1 to ym are respectively set, or x _i and w _i are calculated by solving equation (10) as simultaneous equations. Thereby, x _i and w _i that satisfy equation (7) or equation (8) are calculated.

続くＳ１１０では、制御部１２は、Ｓ１０５にて算出されたｘ_ｉ及びｗ_ｉに基づき、作付スケジュールを決定する。具体的には、算出されたｘ_１～ｘ_ｎの値を作付日としても良いし、ｗ_１～ｗ_ｎの値を各作付日における作付量としても良い。また、収穫量に余裕を持たせるため、ｗ_ｉの値に所定値を加えた値を作付量としても良い。

In subsequent S110, the control unit 12 determines a planting schedule based on x _i and w _i calculated in S105. Specifically, the calculated values of x ₁ to x _n may be used as the planting date, or the values of w ₁ to w _n may be used as the planting amount on each planting date. Furthermore, in order to provide a margin for the harvest amount, the cropping amount may be set to a value obtained by adding a predetermined value to the value of w _i .

[5. Regarding solution 2]
In Solution 2, a period of m consecutive days (m is a predetermined integer of 1 or more) (hereinafter referred to as a harvest period) is used as the value of y. Hereinafter, the first day of the harvest period will be _ys , and the last day will be _ye . Note that m may be an integer of 2 or more. Below, cropping schedule calculation process 2 for calculating a cropping schedule using solution method 2 will be explained using the flowchart of FIG. 5. This process is executed by the control unit 12 of the cropping schedule calculation device 10 operating according to the cropping schedule calculation program. Furthermore, the cropping schedule calculation process 2 implements the cropping schedule calculation method using the solution method 2.

In S200, the control unit 12 obtains the harvesting period from ys to _ye as the value of y by obtaining _{ys and ye ,} and also obtains the values of u and z. Note that the control unit 12 acquires these values in the same manner as in S100.

In subsequent S205, the control unit 12 calculates x i and _{w i} that satisfy equation (11) for n cases where i is 1 to n. Thereby, x _i and w _i that satisfy equation (7) or equation (8) are calculated.

なお、式（１１）におけるＨは、以下の式（１２）により算出される。

Note that H in equation (11) is calculated using equation (12) below.

また、ｈは一例として２である。しかし、ｈは、１又は３以上の整数であっても良い。

Further, h is 2 as an example. However, h may be an integer of 1 or 3 or more.

In solution method 2, x i and w _i that satisfy equation (7) or equation (8) on average are calculated during the harvest period from y _s to _{y e .} For this reason, Equation (12) is defined that integrates the h-th power of the difference between Equation (6) and Equation (5) over the period from _{ys to ye .} Then, by calculating x _i and w _i that minimize H, x i and _{w i} that satisfy equation (7) or equation (8) are calculated. That is, for each case where i is 1 to n, the value of x _i where the partial derivative obtained by partially differentiating H with x i is 0, and the value of x _i obtained by partially differentiating H with w _i x _i and w _i are calculated by calculating the value of w _i whose partial derivative becomes 0.

In subsequent S210, the control unit 12 determines a planting schedule based on x _i and w _i calculated in S205, similarly to S110.
[5. effect]
(1) According to the above embodiment, the solution of x _i and w _i in equation (7) or (8) corresponds to the planting date and planting amount at which the difference between the demand amount and the harvest amount of the crop is less than or equal to H0. do. Therefore, by determining at least one planting date and planting amount based on the solutions of x _i and w _i , it is possible to bring the crop yield closer to the demand amount. Therefore, it is possible to balance the demand for crops with the amount of harvest.

(2) Regarding Solution 1, the solution for x _i and w _i in equation (9) or (10) is based on the planting date and The amount of planting. Therefore, by determining at least one planting date and planting amount based on the solutions of x _i and w _i , it is possible to bring the crop yield closer to the demand amount on each of at least one discrete harvest date. . Therefore, it is possible to balance the demand for crops with the amount of harvest.

In addition, according to Solution 1, it is possible to bring the crop harvest amount on a specific day closer to the demand amount, so the demand amount and harvest amount can be harmonized for crops whose demand fluctuates rapidly on specific days and times of the year. It is suitable for taking.

(3) Regarding Solution 2, Equation (12) integrates the h-th power of the left side of Equation (7) or (8) over the harvest period from y _s to y _e , which are consecutive harvest days. It is. By calculating x _i and w _i that minimize H, it is possible to calculate x _i and w _i that satisfy equation (7) or (8) on average during the harvest period. Therefore, in solution method 2, x i and _{w i that} minimize H are calculated by solving equation (11) for each case where i is 1 to n.

Therefore, by determining at least one planting date and planting amount based on the solutions of x _i and w _i obtained from equation (11), the average crop yield can be adjusted to the average crop yield during the harvest period. It is possible to get close to the demand quantity. Therefore, it is possible to balance the demand for crops with the amount of harvest.

Furthermore, according to Solution 2, it is possible to bring the harvest amount of crops closer to the demand amount on average during the harvest period. For this reason, it is suitable for achieving a balance between the demand amount and the harvest amount of crops whose demand amount fluctuates relatively small, such as crops sold at large-scale stores such as major supermarkets.

[4. Other embodiments]
Although the embodiments for carrying out the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments, and can be implemented with various modifications.

(1) The cropping schedule calculation device 10 may be configured not as a PC but as a dedicated electronic device for calculating the cropping schedule. Further, instead of realizing the function of the cropping schedule calculation device 10 by a computer, all or part of the function may be realized by a logic circuit or the like (in other words, hardware). Moreover, the cropping schedule calculation device 10 may be configured as a plurality of PCs.

(2) Furthermore, the functions realized by the cropping schedule calculation device 10 may be provided on the cloud. That is, the cropping schedule calculation device 10 may be configured as one or more servers. In addition, the cropping schedule calculation device 10 acquires the values of y, u, and z in response to instructions from a terminal acquired via a network such as the Internet, and calculates a cropping schedule in the same manner as in the above embodiment. It's okay. The cropping schedule calculation device 10 may then provide the calculated cropping schedule to the terminal.

(3) A plurality of functions of one component in the above embodiment may be realized by a plurality of components, and a function of one component may be realized by a plurality of components. . Further, a plurality of functions possessed by a plurality of constituent elements may be realized by one constituent element, or one function realized by a plurality of constituent elements may be realized by one constituent element. Further, a part of the configuration of the above embodiment may be omitted. Further, at least a part of the configuration of the above embodiment may be added to or replaced with the configuration of other embodiments.

[Correspondence with the scope of claims]
S100 and S200 in cropping schedule calculation processes 1 and 2 correspond to an example of an acquisition unit, and S105 and S205 correspond to an example of a calculation unit.

DESCRIPTION OF SYMBOLS 10... Cropping schedule calculation device, 11... Storage part, 12... Control part, 13... Communication part, 14... Display part, 15... Operation part.

Claims (6)

A planting schedule calculation device that calculates at least one planting date for a crop and a planting amount that is the amount of the crop to be planted on the planting date,
A variable indicating each of the planting dates for n days (n is a predetermined integer greater than or equal to 1) is x _i (i is an integer greater than or equal to 1 and less than or equal to n), and a variable indicating the cropping amount at x _i is w _i , y is a variable indicating the harvest date, which is the day on which the crop is harvested, u is a variable indicating the fluctuation factor of the demand for the crop, z is a variable indicating the growing environment of the crop, and H0 is a predetermined threshold value. ,
Acquisition of y _j (j is an integer of 1 or more and m or less) indicating each harvest date for m days (m is an integer of 1 or more) as the value of y, and the values of u and z Department and
A calculation unit that calculates x _i and w _i based on equation (1),
The calculation unit calculates m equations (1) in which the values of u and z acquired by the acquisition unit are set, and y ₁ to y _m are respectively set as the value of y, and calculates these m equations (1). A cropping schedule calculation device that calculates x _i and w _i by solving equation (1) as a simultaneous inequality.
Note that g(y _j , u) is a preset mathematical model with y _j and u as explanatory variables, and is a predicted value according to the fluctuation factor indicated by the value of u, and is a predicted value on the harvest date y _j Indicates the predicted value of the demand for the harvested crop, f(x _i , y _j , z) is a preset mathematical model with x _i , y _j , z as explanatory variables, and the value of z is a function with x _i as a variable, which is a predicted value according to the growth environment indicated by and indicates a predicted value of the yield at y _j obtained from the planting of the unit planting amount of the crop at the planting date x _i . be. A planting schedule calculation device that calculates at least one planting date for a crop and a planting amount that is the amount of the crop to be planted on the planting date,
A variable indicating each of the planting dates for n days (n is a predetermined integer greater than or equal to 1) is x _i (i is an integer greater than or equal to 1 and less than or equal to n), and a variable indicating the cropping amount at x _i is w _i , y is a variable indicating the harvest date, which is the day on which the crop is harvested, u is a variable indicating the fluctuation factor of the demand for the crop, z is a variable indicating the growing environment of the crop, and H0 is a predetermined threshold value. ,
The harvest date is a harvest period of m consecutive days (m is an integer of 1 or more), the value indicating the first day of the harvest period is _ys , the value indicating the last day _{is ye} ,
an acquisition unit that acquires the harvest period as a value of _y and also acquires values _of u and z by acquiring ys and ye;
A calculation unit that calculates x _i and w _i based on equation (2),
The calculation unit calculates x i and _{w i} that satisfy equation (2) for each of n cases where i is 1 to n.
Note that H in equation (2) is calculated using equation (3) below.
Values acquired by the acquisition unit are set for u and z in equation (3). Further, h is an integer of 1 or more.
Note that g(y, u) is a preset mathematical model with y and u as explanatory variables, and is a predicted value according to the fluctuation factors indicated by the value of u, and is a predicted value for the harvested crop on harvest date y. It is a function with y as a variable indicating the predicted value of the demand amount of the crop, and f(x _i , y, z) is a preset mathematical model with x _i , y, z as explanatory variables. , z is a predicted value according to the growing environment indicated by the value of _y , and indicates the predicted value of the yield at y obtained from the planting of the unit planting amount of the crop at the planting date x _i . This is a function that is a variable. A cropping schedule calculation method that calculates at least one planting date for a crop and a planting amount that is the amount of the crop to be planted on the planting date, the method comprising:
The computer is
A variable indicating each of the planting dates for n days (n is a predetermined integer greater than or equal to 1) is x _i (i is an integer greater than or equal to 1 and less than or equal to n), and a variable indicating the cropping amount at x _i is w _i , y is a variable indicating the harvest date, which is the day on which the crop is harvested, u is a variable indicating the fluctuation factor of the demand for the crop, z is a variable indicating the growing environment of the crop, and H0 is a predetermined threshold value. ,
As the value of y, obtain y _j (j is an integer of 1 or more and m or less) indicating the harvest date for each of m days (m is an integer of 1 or more), and obtain the values of u and z,
Calculate x _i and w _i based on equation (4),
In the above calculation, m equations (4) are obtained in which the acquired values of u and z are set, and y ₁ to y _m are respectively set as the value of y, and these equations (4 ) as simultaneous inequalities to calculate x _i and w _i .
Note that g(y _j , u) is a preset mathematical model with y _j and u as explanatory variables, and is a predicted value according to the fluctuation factor indicated by the value of u, and is a predicted value on the harvest date y _j Indicates the predicted value of the demand for the harvested crop, f(x _i , y _j , z) is a preset mathematical model with x _i , y _j , z as explanatory variables, and the value of z is a function with x _i as a variable, which is a predicted value according to the growth environment indicated by and indicates a predicted value of the yield at y _j obtained from the planting of the unit planting amount of the crop at the planting date x _i . be. A cropping schedule calculation method that calculates at least one planting date for a crop and a planting amount that is the amount of the crop to be planted on the planting date, the method comprising:
The computer is
A variable indicating each of the planting dates for n days (n is a predetermined integer greater than or equal to 1) is x _i (i is an integer greater than or equal to 1 and less than or equal to n), and a variable indicating the cropping amount at x _i is w _i , y is a variable indicating the harvest date, which is the day on which the crop is harvested, u is a variable indicating the fluctuation factor of the demand for the crop, z is a variable indicating the growing environment of the crop, and H0 is a predetermined threshold value. ,
The harvest date is a harvest period of m consecutive days (m is an integer of 1 or more), the value indicating the first day of the harvest period is _ys , the value indicating the last day _{is ye} ,
By obtaining _ys and _ye , the harvest period is obtained as the value of y, and the values of u and z are obtained,
Calculate x _i and w _i based on equation (5),
In the calculation, x _i and _w i that satisfy equation (5) are calculated for each of n cases where i is 1 to n.
Note that H in equation (5) is calculated using equation (6) below.
The acquired values are set for u and z in equation (6). Further, h is an integer of 1 or more.
Note that g(y, u) is a preset mathematical model with y and u as explanatory variables, and is a predicted value according to the fluctuation factors indicated by the value of u, and is a predicted value for the harvested crop on harvest date y. It is a function with y as a variable indicating the predicted value of the demand amount of the crop, and f(x _i , y, z) is a preset mathematical model with x _i , y, z as explanatory variables. , z is a predicted value according to the growing environment indicated by the value of _y , and indicates the predicted value of the yield at y obtained from the planting of the unit planting amount of the crop at the planting date x _i . This is a function that is a variable. A planting schedule calculation program that calculates at least one planting date for a crop and a planting amount that is the amount of the crop to be planted on the planting date,
A variable indicating each of the planting dates for n days (n is a predetermined integer greater than or equal to 1) is x _i (i is an integer greater than or equal to 1 and less than or equal to n), and a variable indicating the cropping amount at x _i is w _i , y is a variable indicating the harvest date, which is the day on which the crop is harvested, u is a variable indicating the fluctuation factor of the demand for the crop, z is a variable indicating the growing environment of the crop, and H0 is a predetermined threshold value. ,
Acquisition of y _j (j is an integer of 1 or more and m or less) indicating each harvest date for m days (m is an integer of 1 or more) as the value of y, and the values of u and z Department and
As a calculation unit that calculates x _i and w _i based on equation (7),
run the computer,
The calculation unit calculates m equations (7) in which the values of u and z acquired by the acquisition unit are set, and y ₁ to y _m are respectively set as the value of y, and calculates these m equations (7). A cropping schedule calculation program that calculates x _i and w _i by solving equation (7) as a simultaneous inequality.
Note that g(y _j , u) is a preset mathematical model with y _j and u as explanatory variables, and is a predicted value according to the fluctuation factor indicated by the value of u, and is a predicted value on the harvest date y _j Indicates the predicted value of the demand for the harvested crop, f(x _i , y _j , z) is a preset mathematical model with x _i , y _j , z as explanatory variables, and the value of z is a function with x _i as a variable, which is a predicted value according to the growth environment indicated by and indicates a predicted value of the yield at y _j obtained from the planting of the unit planting amount of the crop at the planting date x _i . be. A planting schedule calculation program that calculates at least one planting date for a crop and a planting amount that is the amount of the crop to be planted on the planting date,
A variable indicating each of the planting dates for n days (n is a predetermined integer greater than or equal to 1) is x _i (i is an integer greater than or equal to 1 and less than or equal to n), and a variable indicating the cropping amount at x _i is w _i , y is a variable indicating the harvest date, which is the day on which the crop is harvested, u is a variable indicating the fluctuation factor of the demand for the crop, z is a variable indicating the growing environment of the crop, and H0 is a predetermined threshold value. ,
The harvest date is a harvest period of m consecutive days (m is an integer of 1 or more), the value indicating the first day of the harvest period is _ys , the value indicating the last day _{is ye} ,
an acquisition unit that acquires the harvest period as a value of _y and also acquires values _of u and z by acquiring ys and ye;
As a calculation unit that calculates x _i and w _i based on equation (8),
run the computer,
The calculation unit calculates x _i and w _i that satisfy equation (8) for each of n cases where i is 1 to n.
Note that H in equation (8) is calculated using equation (9) below.
Values acquired by the acquisition unit are set to u and z in equation (9). Further, h is an integer of 1 or more.
Note that g(y, u) is a preset mathematical model with y and u as explanatory variables, and is a predicted value according to the fluctuation factors indicated by the value of u, and is a predicted value for the harvested crop on harvest date y. It is a function with y as a variable indicating the predicted value of the demand amount of the crop, and f(x _i , y, z) is a preset mathematical model with x _i , y, z as explanatory variables. , z is a predicted value according to the growing environment indicated by the value of _y , and indicates the predicted value of the yield at y obtained from the planting of the unit planting amount of the crop at the planting date x _i . This is a function that is a variable.

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