KR102254772B1 - Method and system for presenting the selling price of agricultural products - Google Patents

Abstract

The present disclosure relates to a method for presenting a sale price of agricultural products performed by an information processing system. The method for presenting a sale price of agricultural products comprises the steps of: receiving, by a communication unit, a market price data set; extracting, by a processor, a principal component reflecting a market supply and demand situation by using principal component analysis on the market price data set; and calculating, by the processor, a standard price by applying a ratio of predetermined prices receivable by producers in accordance with the extracted main component.

Description

Method and system for presenting the sale price of agricultural products {METHOD AND SYSTEM FOR PRESENTING THE SELLING PRICE OF AGRICULTURAL PRODUCTS}

The present disclosure relates to a method and system for presenting agricultural product sales price, and more particularly, to provide a method and system capable of presenting the extracted agricultural product sales price based on principal component analysis of market price data of agricultural products.

In the distribution process of agricultural products, a large number of distribution entities, such as farmhouses, producers' groups, producers' organizations, distributors, wholesale market corporations, wholesalers and retailers are involved, resulting in an inefficient distribution structure and high agricultural product prices. In such a complex distribution structure of agricultural products, excessively high margins are set in the intermediate distribution stage, and prices of agricultural products delivered to end consumers are rising, but profits returned to farmers are decreasing. In addition, price volatility of agricultural products is increasing due to various causes, such as changes in the atmospheric environment and imports of foreign agricultural products.

In addition, the price of agricultural products can be determined according to the classification system. For example, according to the agricultural product grading system, products or heavy goods having a certain shape and size are sold to consumers at an appropriate price, while they are ugly or irregular in size, but they are not used for food. Some of the non-problem grade agricultural products are allowed to be sold by tying. On the other hand, the non-grade agricultural products that remain after being sold in such a way are sold or discarded to distribution processors at a bargain price.

On the other hand, there is a need for general consumers or small restaurant businesses to purchase agricultural products at a more reasonable price through direct transactions with farmers. However, in this case, there is a problem that direct trading of non-grade agricultural products is difficult to be activated in the state that the farmhouse as a supplier unilaterally presents a price slightly lower than the market price or an appropriate price standard is not presented.

The present disclosure provides a method of presenting agricultural product trading prices to solve the above problems.

The method according to some embodiments of the present disclosure extracts a principal component that reflects the market supply and demand situation, based on agricultural product market price data for which prices are determined according to grade classification, and applies a ratio of a predetermined producer receipt price to the extracted principal component. Standard prices for non-grade products can be calculated.

The method according to some embodiments of the present disclosure may calculate a suggested price of a product other than the grade by applying a predetermined scaling adjustment value to the calculated standard price.

The method according to some embodiments of the present disclosure may calculate a smoothing value for predicting a future price of agricultural products by applying an autoregressive model to the calculated standard price or suggested price.

The present disclosure may be implemented in a variety of ways, including a method, system, or computer readable storage medium storing instructions.

The method of presenting the sale price of agricultural products according to an embodiment of the present disclosure includes the steps of receiving a market price data set by a communication unit, and reflecting the market supply and demand situation by using a principal component analysis on the market price data set by a processor. And extracting the principal component, and calculating a standard price by applying, by the processor, a ratio of a predetermined producer receipt price to the extracted principal component.

According to an embodiment, the method of presenting the selling price of agricultural products further includes calculating, by the processor, the proposed price by applying a predetermined scaling adjustment value to the calculated standard price.

According to an embodiment, the method of presenting the selling price of agricultural products further includes calculating, by the processor, a smoothing value by applying an autoregression to the calculated standard price or the suggested price.

을 이용하여 평활화 값을 산출하는 단계를 더 포함한다. 상기 수학식에서,

는 t 시점의 평활화값,

은 t 시점으로부터 1 시점 전에 획득한 평활화값,

는 평균이 0이고, 분산이 1인 정규분포에서 나온 임의의 값, 즉 백색잡음(white noise),

및

은 데이터를 이용한 모형의 추정결과로 산출되는 값을 각각 나타낸다.According to an embodiment, the step of calculating the smoothing value is Equation

It further includes calculating a smoothing value by using. In the above equation,

Is the smoothing value at point t,

Is the smoothing value obtained 1 time before the time point t,

Is any value from the normal distribution with mean 0 and variance 1, i.e. white noise,

And

Represents the values calculated from the model's estimation results using the data.

According to an embodiment, the market price data includes at least one of a shipping price, an auction price, a wholesale price, and a retail price of each agricultural product provided from the public DB.

According to an embodiment, the predetermined ratio of producer receipt prices is calculated from the distribution cost rate of each agricultural product provided from the public DB.

According to another embodiment, there is provided a computer-readable medium in which a computer program for executing a method of presenting a selling price of agricultural products on a computer by an information processing system is recorded.

An information processing system according to another embodiment includes a communication unit configured to receive a price data set, a storage unit configured to store the price data set and one or more program instructions, and a principal component analysis in the price data set by executing the stored one or more program instructions. And a processor consisting of a principal component analysis unit for extracting the principal component by using and a price adjustment unit configured to calculate a standard price by applying a ratio of a predetermined producer receipt price to the extracted principal component.

According to an embodiment, the price adjustment unit is further configured to calculate the suggested price by applying a predetermined scaling adjustment value to the calculated standard price.

According to an embodiment, the processor is configured to further include an autoregressive model calculator configured to calculate a smoothing value by applying the autoregressive model to the calculated standard price or suggested price.

According to some embodiments of the present disclosure, it is possible to extract information on the price of reasonable farm products (or yawns) using a statistical (quantitative economics) model from market price data of commodities or heavy agricultural products.

According to some embodiments of the present disclosure, both sellers (eg, farmers) and buyers (eg, retail consumers, restaurants, etc.) can be satisfied through direct transactions without intermediate distribution, and reasonable sales through financial engineering verification You can offer a price.

According to some embodiments of the present disclosure, a stable transaction price may be calculated by predicting and reflecting a market supply and demand situation and a future transaction price from market price data of agricultural products.

The effects of the present disclosure are not limited to the above-mentioned effects, and other effects not mentioned are those of ordinary skill in the technical field belonging to the present disclosure from the description of the claims (hereinafter referred to as'common technician') Will be clearly understood.

Embodiments of the present disclosure will be described with reference to the accompanying drawings described below, in which like reference numerals denote like elements, but are not limited thereto.
1 is an exemplary configuration diagram illustrating a system for presenting an agricultural product sale price according to an embodiment of the present disclosure.
2 is an exemplary configuration diagram of an information processing system according to an embodiment of the present disclosure.
3 is a flowchart illustrating a method of presenting a sale price of agricultural products according to an embodiment of the present disclosure.
4 is a flowchart illustrating a method of presenting a sale price of agricultural products according to an embodiment of the present disclosure.
5 is a flowchart illustrating a method of presenting a selling price of agricultural products according to another exemplary embodiment of the present disclosure.
6 is a flowchart illustrating a method of buying and selling agricultural products according to the presentation of the selling price of agricultural products between an information processing system, a seller terminal, and a buyer terminal according to an embodiment of the present disclosure.
7 is an exemplary diagram of a graph representing a price data set according to an embodiment of the present disclosure.
8 is an exemplary diagram of a graph showing a main component, a standard price, and a suggested price according to an embodiment of the present disclosure.
9 is an exemplary view illustrating a method of buying and selling agricultural products according to the presentation of the selling price of agricultural products according to an embodiment of the present disclosure.

Hereinafter, with reference to the accompanying drawings, specific details for carrying out the present disclosure will be described in detail. However, in the following description, when there is a possibility that the subject matter of the present disclosure may be unnecessarily obscure, detailed descriptions of widely known functions or configurations will be omitted.

In the accompanying drawings, the same or corresponding elements are denoted with the same reference numerals. In addition, in the description of the following embodiments, overlapping descriptions of the same or corresponding components may be omitted. However, even if description of a component is omitted, it is not intended that such component is not included in any embodiment.

Advantages and features of the disclosed embodiments, and a method of achieving them will become apparent with reference to the embodiments described below together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below, but may be implemented in a variety of different forms, only the present embodiments make the present disclosure complete, and the present disclosure completely covers the scope of the invention to those skilled in the art. It is only provided to inform you.

The terms used in the present specification will be briefly described, and the disclosed embodiments will be described in detail. Terms used in the present specification have selected general terms that are currently widely used as possible while considering functions in the present disclosure, but this may vary according to the intention or precedent of a technician engaged in a related field, the emergence of new technologies, and the like. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning of the terms will be described in detail in the description of the corresponding invention. Therefore, the terms used in the present disclosure should be defined based on the meaning of the term and the contents of the present disclosure, not the name of a simple term.

In the present specification, expressions in the singular include plural expressions unless the context clearly specifies that they are in the singular. In addition, plural expressions include expressions in the singular, unless the context clearly specifies that they are plural. When a part of the specification is said to "include" a certain component, it means that other components may be further included rather than excluding other components unless specifically stated to the contrary.

In addition, the terms "module" or "unit" used in the specification mean software or hardware components, and "module" or "unit" performs certain roles. However,'module' or'unit' is not meant to be limited to software or hardware. The'module' or'unit' may be configured to be in an addressable storage medium, or may be configured to reproduce one or more processors. Thus, as an example, the'module' or'unit' refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, It may include at least one of procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, or variables. Components and functions provided within the'module' or'unit' may be combined into a smaller number of components and'module' or'unit', or additional components and'module' or'unit'. Can be further separated.

According to an embodiment of the present disclosure, a'module' or'unit' may be implemented with a processor and a memory. 'Processor' should be interpreted broadly to include general purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), controllers, microcontrollers, state machines, etc. In some circumstances, a'processor' may refer to an application specific semiconductor (ASIC), programmable logic device (PLD), field programmable gate array (FPGA), and the like. 'Processor' refers to a combination of processing devices such as, for example, a combination of a DSP and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors in combination with a DSP core, or any other such combination of configurations. You may. In addition, the'memory' should be broadly interpreted to include any electronic component capable of storing electronic information. 'Memory' refers to random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erase-programmable read-only memory (EPROM), It may refer to various types of processor-readable media such as electrically erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, and the like. The memory is said to be in electronic communication with the processor if the processor can read information from and/or write information to the memory. The memory integrated in the processor is in electronic communication with the processor.

In the present disclosure, the'system' may include at least one of a server device and a cloud device, but is not limited thereto. For example, the system may consist of one or more server devices. As another example, the system may consist of one or more cloud devices. As another example, the system may be operated by configuring a server device and a cloud device together.

In the present disclosure, the'seller terminal' or the'buyer's terminal' is provided with a communication module to enable network connection, and any electronic device capable of inputting and outputting arbitrary data and/or information by accessing a website, an application, etc. For example, it may include a smartphone, a PC, a tablet PC, a laptop PC, etc.). The seller or the buyer is input through the seller terminal or the buyer terminal through the interface of the seller terminal or the buyer terminal (for example, a touch display, a keyboard, a mouse, a touch pen or a stylus, a microphone, a motion recognition sensor, etc.) through the network. Any accessible information/data can be provided.

In the present disclosure, "similar" may include all meanings of the same or similar. For example, the fact that two pieces of information are similar may indicate that the two pieces of information are the same or similar to each other.

In the present disclosure, a'program instruction' refers to a set of instructions grouped on the basis of a function, which is a component of a computer program and executed by a processor.

1 is an exemplary configuration diagram illustrating a system 100 for presenting an agricultural product sale price according to an embodiment of the present disclosure. As shown, the agricultural product sale price presentation system 100 may include an information processing system 110, a network 120, a public DB 130, a seller terminal 140, and a buyer terminal 150. Here, the information processing system 110 may be configured to be connected to each of the public DB 130, the seller terminal 140, and the purchaser terminal 150 through a network 120 to enable communication. In FIG. 1, the information processing system 110 is illustrated as one computing device, but is not limited thereto, and the information processing system 110 may be configured to distribute information and/or data through a plurality of computing devices. . In addition, each of the components of the agricultural product sale price presentation system 100 in FIG. 1 represents functional elements that are functionally divided, and a plurality of components may be implemented in a form in which they are integrated with each other in an actual physical environment.

The information processing system 110 is any computing device used to receive a set of quote data and generate principal component values, standard prices, suggested prices, and smoothing values corresponding to the received quote data set. Here, the computing device may refer to any type of device equipped with a computing function, and may be, for example, a notebook computer, a desktop computer, a server, a cloud system, and the like, but is not limited thereto. Further, a more detailed configuration of the information processing system 110 will be described later in FIG. 2.

The public DB 130 may contain a set of quote data, including the actual transaction price of the market. The market price data set may include at least one of a shipping price, an auction price, a wholesale price, and a retail price of each agricultural product. In addition, the public DB 130 may include a distribution cost rate of each agricultural product.

In one embodiment, the public DB 130 may transmit information stored in the public DB 130 to the information processing system 110 through the network 120. For example, the public DB 130 may provide information to the information processing system 110 through an open API (application programming interface) provided by a public institution, local government, or government agency. The public DB 130 stores information on the quantity of production by production area, the price of the last five years by item, the price by production site of auction items, the price by grade by item, the price of major items, and quantity by production area, and the stored information is stored in the information processing system 110. Can provide.

The seller terminal 140 may include a terminal used by a seller who wants to sell agricultural products (eg, a farmer in a mountainous area) using the agricultural product sale price presentation system according to the present disclosure. The seller terminal 140 may be connected to the information processing system 110 through the network 120 and may enter into a sales contract for agricultural products with the purchaser terminal 150.

The purchaser terminal 150 may include a terminal used by a purchaser (eg, a general consumer or a small restaurant business) who wants to purchase agricultural products by using the agricultural product sale price presentation system according to the present disclosure. The purchaser terminal 150 may be connected to the information processing system 110 through the network 120 and may enter into a sales contract for agricultural products with the seller terminal 140.

The network 120 may be configured to enable communication between the information processing system 110, the public DB 130, the seller terminal 140, and the buyer terminal 150. Depending on the installation environment, the network 120 is, for example, a wired network such as Ethernet, a wired home network (Power Line Communication), a telephone line communication device and RS-serial communication, a mobile communication network, a WLAN (Wireless LAN), It can be composed of wireless networks such as Wi-Fi, Bluetooth and ZigBee, or a combination thereof. In other words, the communication method is not limited, and not only a communication method using a communication network (for example, a mobile communication network, wired Internet, wireless Internet, broadcasting network, satellite network, etc.) that the network 120 can include, but also a short distance between user terminals. Wireless communication may also be included. For example, the network 120 includes a personal area network (PAN), a local area network (LAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), and a broadband network (BBN). And any one or more of networks such as the Internet. In addition, the network 120 may include any one or more of a network topology including a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree or a hierarchical network, etc. Not limited.

2 is an exemplary configuration diagram of an information processing system according to an embodiment of the present disclosure. As shown, the information processing system 110 may include at least one processor 210, a communication unit 220, and a storage unit 230. FIG. 2 shows an exemplary configuration, and those of ordinary skill in the art to which the present disclosure pertains can recognize that other general-purpose components may be further included in addition to the components illustrated in FIG. 2.

The processor 210 controls the overall operation of each component of the information processing system 110. The processor 210 includes a CPU (Central Processing Unit), MPU (Micro Processor Unit), MCU (Micro Controller Unit), GPU (Graphic Processing Unit), or any type of processor well known in the technical field of the present disclosure. Can be. Also, the processor 210 may perform an operation on at least one application or program for executing the method according to the embodiments of the present disclosure. The information processing system 110 may include one or more processors.

The processor 210 may include a principal component analysis unit 212, a price adjustment unit 214, and an autoregression model calculation unit 216.

The principal component analysis unit 212 may convert variances of several variables into new variables generated by a linear combination of several variables having high correlations with each other through principal component analysis. For example, the principal component analysis unit 212 best reflects the characteristics of the market price data set by performing a principal component analysis on the market price data set (eg, shipping price, auction price, wholesale price, and retail price of agricultural products) for each time point. The main component can be extracted. When all of the input data, the market price data set, are transaction prices per unit of agricultural products, the main component extracted according to the above-described method may mean a kind of index reflecting the supply and demand situation of agricultural products in the market.

The price adjustment unit 214 may calculate a standard price by applying a ratio of a predetermined producer receipt price to the principal component calculated by the principal component analysis unit 212. Here, the ratio of the producer receipt price may be calculated from the distribution cost rate of each item received from the public DB (eg, 130 in FIG. 1). For example, although the main component reflects the supply and demand situation in the market, it may be a value that cannot be directly proposed as the price per unit of agricultural products. Therefore, by applying the ratio of the producer's receipt price to the main component calculated by the principal component analysis unit 212, it is possible to calculate a standard price that can be interpreted as a standardized price per unit of each agricultural product.

In another embodiment, the ratio of the predetermined producer receipt price is a representative of each subject of a system user according to the present disclosure (for example, a representative of a distribution institution, a representative of a small business promotion corporation, a representative of the national producer association, a representative of a restaurant business, etc.) and / Or it may include an adjustment factor selected by a separate adjustment factor selection committee composed of financial engineering experts.

In one embodiment, the price adjustment unit 214 may calculate the suggested price by applying a predetermined scaling adjustment value to a standard price or a smoothing value (a value calculated by the autoregressive model calculation unit 216 to be described in detail below). I can. For example, since the standard price or smoothing value is calculated based on the price of heavy goods or goods traded in the market, a penalty is imposed on the standard price or smoothing value in order to calculate the suggested price considering the characteristics of the item (or yawn). A scaling adjustment value, such as that, can be applied.

In an embodiment, the predetermined scaling adjustment value may include a value reflecting a difference in a yield of a product versus a product. For example, when processing to use agricultural products purchased by a consumer (for example, a buyer), if the yield of the product is generally about 95%, the yield of the scrap (or yawn) is about 20-30. Since %p is low, the suggested price can be calculated by lowering the price by a relative yield (eg, 20-30%p) from the smoothing value or the standard price.

In one embodiment, the predetermined scaling adjustment value may include a conversion to a transaction unit in which a sale is made in the agricultural product sale price presentation system according to the disclosure of the present invention, rounding off, etc., or a distribution margin reflection coefficient.

The autoregressive model calculation unit 216 may calculate a smoothing value by applying the autoregressive model to the standard price or the suggested price calculated by the price adjustment unit 214. For example, the smoothing value is a value estimated through a quantitative or statistical model, and through this, future agricultural product prices can be predicted. In addition, the smoothing value may include prices of agricultural products up to k points in the future to be used in the sales contract, which will be described later in more detail with reference to FIG. 4.

The communication unit 220 may support wired/wireless Internet communication of the information processing system 110. In addition, the communication unit 220 may support various communication methods other than Internet communication. To this end, the communication unit 220 may be configured to include a communication module well known in the technical field of the present disclosure.

The storage unit 230 may non-temporarily store one or more computer programs processed by the processor 210. The storage unit 230 is a nonvolatile memory such as a ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), flash memory, etc., a hard disk, a removable disk, or in the technical field to which the present disclosure belongs. It may be configured to include any well-known computer-readable recording medium.

3 is a flowchart illustrating a method 300 for presenting an agricultural product trading price according to an embodiment of the present disclosure. According to an embodiment, the method 300 for presenting the sale price of agricultural products may be performed by at least one processor of an information processing system (eg, 110 in FIG. 1 ).

As shown, the method 300 for presenting the selling price of agricultural products may be initiated by a communication unit in step S310 of receiving a market price data set. Here, the market price data set may include at least one of a shipping price, an auction price, a wholesale price, and a retail price of each agricultural product provided from the public DB.

Then, in step S320, the processor(s) may extract a principal component reflecting the market supply and demand situation by using a principal component analysis in the price data set. For example, the processor(s). By receiving at least one of the shipping price, meridian price, retail price, and wholesale price for each point included in the market price data set, the factors that best reflect the characteristics of the data (for example, the market supply and demand situation) can be extracted through principal component analysis. have.

Finally, in step S330, the processor(s) may calculate a standard price by applying a ratio of a predetermined producer receipt price to the extracted main component. Here, the ratio of the producer's receipt price may be calculated from the distribution cost rate of each agricultural product provided from the public DB. For example, the processor(s) is interpreted as a standardized price per unit of each agricultural product by applying the ratio of the producer price to the extracted main component, which is a value that reflects the supply and demand situation of the market but cannot be interpreted as a price per unit of agricultural products. You can calculate the standard price you can do.

In one embodiment, the calculated standard price is calculated as a value between a maximum value (eg, retail price for special products, etc.) and a minimum value (eg, auction price for heavy goods or yawns, etc.) for each agricultural product time point. The standard price calculated in this way may be transmitted to a seller terminal (eg, 140 in FIG. 1) or a buyer terminal (eg, 150 in FIG. 1), and may be used as a price of agricultural products for signing an agricultural product sale contract.

4 is a flowchart illustrating a method 400 for presenting a sale price of agricultural products according to an embodiment of the present disclosure. According to an embodiment, the method 400 for presenting the selling price of agricultural products may be performed by at least one processor of an information processing system (eg, 110 in FIG. 1 ).

As shown, the method 400 for presenting the selling price of agricultural products may be initiated by a communication unit in step S410 of receiving a market price data set. Then, in step S420, the processor(s) may extract the principal component reflecting the market supply/demand situation by using the principal component analysis in the price data set. Next, in step S430, the processor(s) may calculate a standard price by applying a ratio of a predetermined producer receipt price to the extracted main component.

Then, in step S440, the processor(s) may calculate a smoothing value by applying the autoregressive model to the calculated standard price.

For example, the smoothing value is a value estimated through a quantitative or statistical model (for example, an autoregressive model), and through this, future agricultural product prices can be predicted. Since the price of agricultural products fluctuates every day depending on the supply and demand situation of the market, there are cases in which the time of sale between the seller and the buyer (for example, the time of order) and the time of delivery of the agricultural product to the buyer are different. Therefore, the price fluctuation may be large depending on the difference between the time of sale and the time of delivery of agricultural products, so it is necessary to present a reasonable price according to the difference between the two time points. For example, if the sale contract was concluded today, but the seller trades a week's worth of quantities at a time before delivery of the contract, the sale price of agricultural products is based on the predicted value of the daily price change (for example, a smoothing value). Can be presented.

In one embodiment, the smoothing value may be calculated by the following [Equation 1].

[Equation 1]

는 t 시점의 평활화값,

은 t 시점으로부터 1 시점 전에 획득한 평활화값,

는 평균이 0이고, 분산이 1인 정규분포에서 나온 임의의 값, 즉 백색잡음(white noise),

및

은 데이터를 이용한 모형의 추정결과로 산출되는 값을 각각 나타낸다. 예를 들어, 본 개시에서 내일의 감자 가격

는, 오늘의 감자 가격

,

및

을 기초로 산출될 수 있다.here,

Is the smoothing value at point t,

Is the smoothing value obtained 1 time before the time point t,

Is any value from the normal distribution with mean 0 and variance 1, i.e. white noise,

And

Represents the values calculated from the model's estimation results using the data. For example, tomorrow's potato price in this disclosure

The, today's potato prices

,

And

It can be calculated based on.

,

, ...,

)을 포함한다.In one embodiment, the smoothing value is the prices of agricultural products up to the future point k to be used in the sales contract (

,

, ...,

).

In another embodiment, in order to calculate the smoothing value, various types of autoregression models well known to those skilled in the art may be used. For example, various types of time series analysis models that can explain the time-varying variation of standardized prices, such as an Auto-Regressive Integrated Moving Average (ARIMA) model and an ARMA(p,q) model, can be used.

Finally, in step S450, the processor(s) may calculate the suggested price by applying a predetermined scaling adjustment value to the calculated smoothing value. For example, since the values (e.g., standard prices, smoothing values) calculated in steps S430 and S440 are calculated based on the prices of heavy goods or commodities traded in the market, they are sold at the sale price ( Or, a scaling adjustment value such as giving a penalty considering the characteristics of yawning) can be applied.

The suggested price calculated in this way is transmitted to a seller terminal (for example, 140 in FIG. 1) or a buyer terminal (for example, 150 in FIG. 1), and may be used as a price of an agricultural product for signing an agricultural product sale contract.

5 is a flow chart illustrating a method 500 for presenting a sale price of agricultural products according to another embodiment of the present disclosure. According to an embodiment, the method 500 of presenting the sale price of agricultural products may be performed by at least one processor of an information processing system (eg, 110 of FIG. 1 ).

As shown, the method 500 for presenting the selling price of agricultural products may be initiated by a communication unit in step S510 of receiving a market price data set. Then, in step S520, the processor(s) may extract the principal component reflecting the market supply/demand situation by using the principal component analysis in the price data set. Next, in step S530, the processor(s) may calculate a standard price by applying a ratio of a predetermined producer receipt price to the extracted main component.

Then, in step S540, the processor(s) may calculate the first suggested price by applying a predetermined scaling adjustment value to the calculated standard price.

Next, in step S550, the processor(s) may calculate a smoothing value by applying an autoregressive model to the calculated first suggested price.

Finally, in step S560, the processor(s) may calculate the second suggested price by applying a predetermined scaling adjustment value to the calculated smoothing value. For example, the predetermined scaling adjustment value applied in step S560 may include a value different from the predetermined scaling adjustment value applied in step S540.

The second suggested price calculated in this way is transmitted to a seller terminal (for example, 140 in FIG. 1) or a buyer terminal (for example, 150 in FIG. 1), and can be used as the price of agricultural products for signing an agricultural product sale contract. have.

In another embodiment, after step (S550) is performed, step (S560) is not performed, and the smoothing value calculated in step (S550) is transmitted to the seller terminal or the buyer terminal, It can also be used as a price.

6 is a flow chart illustrating a method 600 of trading agricultural products according to the presentation of agricultural products trading prices between an information processing system, a seller terminal, and a buyer terminal according to an embodiment of the present disclosure. As shown, the information processing system 110 may calculate a suggested price for each item (S610). Here, the suggested price for each item may include at least one of a standard price, a suggested price, or a smoothing value extracted by the information processing system 110 according to a method illustrated in any one of FIGS. 3 to 5. In one embodiment, the information processing system 110 may transmit the generated suggested price to the seller terminal 140 (S612). In addition, the information processing system 110 may transmit the generated suggested price to the purchaser terminal 150 (S614).

After displaying the received suggested price on the interface screen of the seller terminal 140, the seller terminal 140 may receive information on the sale item and quantity from the seller who has confirmed the suggested price (S620). The information on the seller's sales item and quantity received in this way may be transmitted to the information processing system 110 (S622).

The purchaser terminal 150 may display the received suggested price on the interface screen of the purchaser terminal 150 and then receive information on the purchase item and quantity from the purchaser who checks the proposed price (S630). The information on the purchase item and quantity of the purchaser received in this way may be transmitted to the information processing system 110 (S632).

The information processing system 110 may compare the information on the sale item and quantity received from the seller terminal 140 and the information on the purchase item and quantity received from the purchaser terminal 150 (S640). In an embodiment, the information processing system 110 may complete a sales contract based on a result of comparing sales/purchase items and quantities (S650).

7 is an exemplary diagram of a graph 700 representing a price data set according to an embodiment of the present disclosure. As illustrated, a graph 700 representing a market price data set includes a merchandise meridian price, a product wholesale price, a product retail price, and a heavy product stored in a public DB (for example, 130 in FIG. 1). It may include the wholesale price and the retail price of heavy goods. Although not shown, the price data set may include various types of products and related price information that can be received from a public DB or an external server.

For example, a product may mean a superior product with a high grade in each item of agricultural products. In addition, heavy goods may mean intermediate goods with a middle grade in each item of agricultural products.

For example, the meridian price may include a price at which the seller decides to sell a product among various prices offered by buyers in a market where an auction is held.

For example, the wholesale price may include a price established in a mass transaction between a seller (eg, a farmer) and a buyer (eg, a corporation or wholesale corporation). In addition, the wholesale price can generally form a higher price than the meridian price.

For example, the retail price may include a price that is established in a small transaction between a wholesale buyer of a product and a general consumer. In addition, retail prices can generally form a higher price point than wholesale prices.

As shown in FIG. 7, the ranking of prices for each price constituting the market price data set fluctuates according to market conditions, but in general, prices in the order of product retail price, heavy product retail price, product wholesale price, heavy product wholesale price, and product meridian price are in order. Lowers.

8 is an exemplary view of a graph showing a main component, a standard price, and a suggested price calculated according to an embodiment of the present disclosure. As shown, the principal component value follows the value of the left data series axis, and the standard price and the suggested price follow the value of the right data series axis. The principal component value reflects the market supply and demand situation, but may include a value that does not directly mean the price of a product.

The standard price may include a value obtained by applying a ratio of a predetermined producer receipt price to the main component by the processor(s) (eg, 210 in FIG. 2).

The suggested price may include a value calculated by applying a predetermined scaling adjustment value to a standard price by the processor(s).

9 is an exemplary view illustrating a method of buying and selling agricultural products according to the presentation of the selling price of agricultural products according to an embodiment of the present disclosure. The interface screen 900 is an agricultural product generated by an information processing system (eg, 110 in FIG. 1) in a seller terminal (eg, 140 in FIG. 1) and a buyer terminal (eg, 150 in FIG. 1). An interface screen 900 for trading agricultural products based on the trading price is shown.

In one embodiment, the search area 910 provides an area in which a user (eg, a buyer or seller) can receive a user input for a product desired to be bought or sold. The information processing system may detect a user input corresponding to a product search, and display a suggested price, a sale or purchase quantity of a product corresponding to the user input in the result areas 920 and 930.

In one embodiment, the result areas 920 and 930 are sub-class names of the searched products, a suggested price, a sales quantity 922 or a purchase quantity 932, a sales/purchase icons 924 and 934, and a price trend icon 926. ), a transaction trend icon 928 may be displayed. In addition, the result areas 920 and 930 may display characteristics of the searched product (eg, additional information such as unique characteristics of agricultural products, strengths and weaknesses, etc.), photos, and the like.

As shown in FIG. 9, the result area 920 shows a case where the sales quantity is greater than the purchase quantity according to the suggested price presented by the information processing system, and the result area 930 shows a case where the quantity of purchase is greater than the quantity sold. Shows the case.

For example, when the number of sales is large, the purchaser can immediately enter into a sales contract through the purchaser terminal. The information processing system displays the sales quantity 922 to convey information that the buyer can immediately enter into a sales contract, and the sales quantity 922 and the sales/purchase icon 924 are displayed in various ways such as highlights, colors, or highlights. Graphic effects can be displayed.

In addition, for example, when the number of purchases is large, the seller may immediately enter into a sales contract through the seller terminal. The information processing system displays the purchase quantity 932 in order to convey information that the seller can immediately enter into a sales contract, and the purchase quantity 934 and the sales/purchase icon 934 are displayed in various ways such as highlights, colors, or highlights. Graphic effects can be displayed.

Further, although not shown, the result may be displayed as shown in the result areas 920 and 930 even when the number of sales quantity and purchase quantity is the same or the sales quantity is 0.

In one embodiment, the price trend icon 926, when detecting a user input for confirming the price trend, is displayed in a daily trend of the suggested price corresponding to the searched product or a public DB (for example, 130 in FIG. 1). Saved price data sets can be displayed.

In one embodiment, the transaction trend icon 928 may display a daily trend of a trading contract corresponding to the searched product when a user input for checking the trend of the transaction volume is detected.

The previous description of the present disclosure is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications of the present disclosure will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to various modifications without departing from the spirit or scope of the present disclosure. Accordingly, this disclosure is not intended to be limited to the examples described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Although exemplary implementations may refer to utilizing aspects of the currently disclosed subject matter in the context of one or more standalone computer systems, the subject matter is not so limited, but rather is associated with any computing environment such as a network or distributed computing environment. It can also be implemented. Furthermore, aspects of the presently disclosed subject matter may be implemented in or across multiple processing chips or devices, and storage may be similarly affected across multiple devices. Such devices may include PCs, network servers, and handheld devices.

Although the present disclosure has been described in connection with some embodiments herein, it should be understood that various modifications and changes may be made without departing from the scope of the present disclosure that can be understood by those skilled in the art to which the present invention belongs. something to do. In addition, such modifications and changes should be considered to fall within the scope of the appended claims in this specification.

100: agricultural product trading price presentation system 110: information processing system
120: network 130: public DB
140: seller terminal 150: buyer terminal

Claims (10)

In the method of presenting the sale price of agricultural products performed by the information processing system,
Receiving, by the communication unit, a market price data set including at least one of a shipping price, an auction price, a wholesale price, and a retail price of agricultural products;
Extracting, by a processor, a principal component reflecting the market supply and demand situation by using a principal component analysis in the price data set;
Calculating a standard price by applying, by the processor, a ratio of a predetermined producer receipt price to the extracted main component; And
Calculating a suggested price by applying a predetermined scaling adjustment value to the calculated standard price by the processor-The scaling adjustment value includes a value reflecting a difference in yield of a product versus a product, and the suggested price is a grade This is the suggested price for other agricultural products-
Including, the method of presenting the sale price of agricultural products.
delete The method of claim 1,
Calculating a smoothing value by applying an autoregression model to the calculated standard price or suggested price, by the processor
Including more, the method of suggesting the sale price of agricultural products.
The method of claim 3,
The step of calculating the smoothing value,
[Equation 1]

(In Equation 1,

Is the smoothing value at point t,

Is the smoothing value obtained 1 time before the time point t,

Is any value from the normal distribution with mean 0 and variance 1, i.e. white noise,

And

Represents the value calculated from the model's estimation result using the data)
Calculating a smoothing value using Equation 1
Including more, the method of suggesting the sale price of agricultural products.
The method of claim 1,
The price data is,
At least one of the shipping price, auction price, wholesale price, and retail price of each agricultural product provided from the public DB
Including, the method of presenting the sale price of agricultural products.
The method of claim 1,
The ratio of the predetermined producer receipt price,
Calculated from the distribution cost rate of each agricultural product provided from the public DB,
How to present the sale price of agricultural products.
A computer-readable medium in which a computer program for executing a method of presenting a sale price of agricultural products on a computer by the information processing system according to claim 1 is recorded.
In the information processing system,
A communication unit configured to receive a market price data set including at least one of a shipping price, an auction price, a wholesale price, and a retail price of agricultural products;
A storage unit configured to store the quote data set and one or more program instructions; And
By executing the stored one or more program instructions, a principal component analysis unit for extracting a principal component using principal component analysis in a market price data set, and a price adjustment unit configured to calculate a standard price by applying a ratio of a predetermined producer receipt price to the extracted principal component. Comprising a configured processor,
The price adjustment unit,
It is further configured to calculate a suggested price by applying a predetermined scaling adjustment value to the calculated standard price, the scaling adjustment value including a value reflecting a difference in yield of a product versus a product, and the suggested price The suggested price,
Information processing system.
delete The method of claim 8,
The processor,
It is configured to further include an autoregressive model calculation unit configured to calculate a smoothing value by applying an autoregressive model to the calculated standard price or suggested price,
Information processing system.

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