JP2020149583A - Program, method, and system for predicting potential ability of race horse, seed horse candidate presentation program, method for presenting seed horse candidate, seed horse candidate presentation system, and prediction career earnings database preparation program used for the same - Google Patents

Abstract

To provide a program, a method, and a system for predicting the potential ability of a race horse capable of predicting information to quantify the potential racing ability of a race horse and maximize the ability, and a prediction career earnings database preparation program used for the program.SOLUTION: The program for predicting the potential racing ability of a race horse causes a computer to execute the steps of: inputting race horse data; and acquiring and displaying prediction information data including prediction career earnings data on the basis of the input race horse data. Also, the program includes the steps of: inputting race horse data; and acquiring and displaying prediction information data including the prediction career earnings data on the basis of the input race horse data.SELECTED DRAWING: None

Description

The present invention relates to a racehorse potential ability prediction program, a racehorse potential ability prediction method, and a racehorse potential ability prediction system, and a stallion candidate presentation program, a stallion candidate presentation method, and a species. It relates to the stallion candidate presentation system and the predictive lifetime winnings database creation program used for these.

Horse racing is a bet in which a racehorse is run a predetermined distance and the spectator predicts the order of arrival, and if the prediction is correct, the spectator is paid a predetermined dividend, including the industry related to the production of racehorses. , The scale is about 3 trillion yen in Japan alone.

It is said that the potential of a racehorse depends largely on its parent, that is, it has a large genetic component. Therefore, attempts have been made to measure its potential by performing genetic testing.

Equinom of Ireland (currently Plasbital), which was established in 2010 for the first time in the world, is a company that undertakes such genetic testing. As of the filing date of the patent application, the company provides a service to genetically test the racehorse's suitability for competitive distance, and supports trainers and owners to decide which race to run the racehorse.

As can be seen from the above description, it is an important factor for trainers to select a race in which a racehorse can maximize its competitive ability.

Regarding the above viewpoint, as a known technique for genetic testing, for example, in Patent Document 1 below, it is determined whether a racehorse is a short-distance type, a medium-distance type, or a long-distance type by performing a genetic test on a racehorse. The method of judgment is disclosed.

Japanese Patent No. 5667057

However, the technique described in Patent Document 1 merely determines the suitability type of a racehorse, and there still remains a problem in evaluating the potential ability of the racehorse.

By the way, at present, in the production of racehorses, traditionally, a producer or owner with specialized knowledge considers the competitive performance, pedigree, physique, personality, etc. of the breedmare, and the breeding piece of the stallion. The breeding stallion is determined by referring to the performance, pedigree, personality, mating amount, or the competition performance of horses with similar pedigree.

That is, for racehorses that trade for tens of millions to hundreds of millions of dollars, a method of determining potential competitiveness, or selection of stallion mates with breeding mares to produce racehorses with high potential competitiveness. Although the method of doing this is supported by the experience and knowledge of the producers, there are still problems in its quantitative and objective judgment.

Therefore, in view of the above problems, the present invention is a racehorse potential ability prediction program and a racehorse potential ability prediction method capable of predicting information for quantifying and maximizing the potential competitive ability of a racehorse. And, one of the purposes is to provide a potential ability prediction system for racehorses, and a predictive lifetime earned prize database creation program used for these.

Further, the present invention is related to the above object, and further pays attention to the relationship between the breeding mare and the stallion, and by applying the above, presents a stallion candidate for presenting the optimum stallion for the breeding mare. One of the other purposes is to provide a program, a mare candidate presentation method, a mare candidate presentation system, and a predictive lifetime earned prize database creation program used for these.

The racehorse potential competitive ability prediction program according to one aspect of the present invention that solves the above problems includes a procedure for inputting racehorse data into a computer and predicted lifetime earned prize data based on the input racehorse data. This is for executing the procedure of acquiring and displaying the prediction information data.

In addition, the method for predicting the potential competitive ability of a racehorse according to another aspect of the present invention is based on a procedure for inputting racehorse data and the input racehorse data, and predictive information data including predicted lifetime earned prize data. It has a procedure for acquiring and displaying.

In addition, the race horse potential competitive ability prediction system according to another aspect of the present invention obtains prediction information data including predicted lifetime earned prize data based on the procedure for inputting race horse data and the input race horse data. A computer that records a race horse's potential competitiveness prediction program to execute the acquisition and display procedure, multiple past race horse data, and breeding mare data and stallion data corresponding to the past race horse data. Predictive lifetime for executing machine learning including data and lifetime earned prize performance data, and creating and recording forecast information data including predicted lifetime earned prize data for each race horse data. It is equipped with a computer on which the winning prize database creation program is recorded.

In addition, the stallion candidate presentation program according to another aspect of the present invention acquires predictive information data including predictive lifetime earned prize data based on the procedure for inputting breeding mare data into a computer and the input breeding mare data. It is for executing the procedure of displaying.

Further, in the method for presenting a stallion candidate according to another aspect of the present invention, a procedure for inputting breeding mare data and based on the input breeding mare data, predictive report data including predicted lifetime earned prize data is acquired. It has a procedure for displaying.

In addition, the stallion candidate presentation system according to another aspect of the present invention acquires and displays forecast information data including forecast lifetime earned prize data based on the procedure for inputting breeding marine data and the input breeding marine data. A computer that records a stallion candidate presentation program to execute the procedure, multiple past race horse data, breeding female horse data corresponding to the past race horse data, stallion data, and lifetime winning prize results. A predictive lifetime earned prize database creation program is recorded to execute the procedure of performing machine learning including data and creating and recording predictive information data including predicted lifetime earned prize data for each race horse data. It is equipped with a computer.

In addition, the predicted lifetime earned prize database creation program according to another aspect of the present invention has a computer, a plurality of past racehorse data, and breeding mare data, stallion data, and lifetime corresponding to the past racehorse data. This is for performing machine learning including the earned prize performance data, and executing a procedure of creating and recording prediction information data including the predicted lifetime earned prize data for each racehorse data.

As described above, according to the present invention, a racehorse potential ability prediction program, a racehorse potential ability prediction method, and a racehorse potential ability prediction method capable of predicting information for quantifying and maximizing the potential competitive ability of a racehorse. Potential prediction system can be provided.

Further, the present invention can further provide a stallion candidate presentation program, a stallion candidate presentation method, and a stallion candidate presentation system for presenting an optimum stallion to a breeding mare.

It is the schematic about the system which concerns on Embodiment 1. FIG. It is a figure which shows the example of the input screen of the customer computer CS in the system which concerns on Embodiment 1. It is an image diagram of the screen when the search of a racehorse is selected in FIG. It is a figure which shows the example of the screen which shows the output result in the system which concerns on Embodiment 1. It is a figure which shows the example of the input screen of the customer computer CS in the system which concerns on Embodiment 2. It is an image diagram of the screen when the search of a breeding mare is selected in FIG. It is a figure which shows the example of the screen which shows the output result in the system which concerns on Embodiment 2.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. However, the present invention can be implemented in many different embodiments and is not construed as limited to the examples specifically shown in the following embodiments.

(Embodiment 1)
(Potential competitiveness prediction system for racehorses)
The racehorse potential competitive ability prediction system (hereinafter referred to as “the system” in the present embodiment) S according to the present embodiment is based on (1) a procedure for inputting racehorse data and the input racehorse data. Computer C1 that records a racehorse potential competitiveness prediction program for executing the procedure of acquiring and displaying forecast information data including forecast lifetime earned prize data, and (2) multiple past racehorse data. , And the breeding mare data corresponding to the past racehorse data, the stallion data, and the lifetime earned prize performance data are included in the machine learning, and the forecast information including the predicted lifetime earned prize data is included for each racehorse data. It comprises a computer C2 in which a predicted lifetime earned prize database creation program for executing a procedure for creating and recording data is recorded. FIG. 1 is a schematic view of a system that realizes the system S.

From the viewpoint of explanation and more efficient system provision, the above computer C1 and computer C2 may be the same computer, but the computer C1 and the computer C2 may be the same computer as shown in this figure, such as the Internet. It is preferable that the connection is made through the telecommunication line W.

Further, in the system S, a customer computer CS exists as a customer who uses this system, and is in a state where it can be connected through the telecommunication line W as described above.

(Computer that records the potential competitiveness prediction program of racehorses)
Here, each component of the system S will be specifically described. First, as described above, the system S executes a procedure for inputting racehorse data and a procedure for acquiring and displaying forecast information data including predicted lifetime earned prize data based on the input racehorse data. It has a computer C1 in which a racehorse potential competitiveness prediction program (hereinafter referred to as "the prediction program" in the present embodiment) is recorded.

Here, the "computer" is a mechanical device that can be driven by the supply of electric power to realize a predetermined process, and is, for example, a central arithmetic device (CPU) that can perform a desired calculation process, and data. A memory such as RAM that can temporarily record data, a recording medium such as a hard disk or flash memory that can stably record data for a predetermined period of time, an input device that can perform a predetermined input such as a keyboard or a mouse. , A bus connecting these, a display device such as a liquid crystal monitor for displaying the result of performing the above desired processing, and the like. This computer can include so-called ordinary desktop personal computers, laptop computers, etc., but in some cases, it may also include so-called smartphones, tablet terminals, etc., which are miniaturized by integrating an input device, a display device, etc. it can. The same applies to this computer. Therefore, the explanation of terms in each part will be omitted except in special cases.

As described above, in the computer C1, the prediction program is recorded on a recording medium such as a hard disk. This prediction program can be temporarily read into a recording medium such as RAM and executed by a user's desired operation to realize the above procedure. That is, this prediction program can realize a predetermined method by being executed. Specifically, it is possible to provide a method for predicting the potential competitive ability of a racehorse having the above-mentioned predetermined procedure (hereinafter referred to as "the present prediction method").

The form of the "program" is not limited, and may be expressed in a language such as HTML (web service type) so that it can be displayed on a web browser, or is described in a predetermined language and downloaded. It may be an installation type that can be executed for the first time by installing it, but the customer can see the web service or application that holds the program in the computer C1 and displays it while performing the predetermined processing while reading it with the browser in the customer computer CS. It is preferable that it is a so-called web service type, such as a web service that is installed in a computer CS and transmits / receives necessary data to / from the computer C1 or the computer C2 via a network such as the Internet, in terms of widespread use. The case where the application is installed on the customer computer CS to directly send and receive data to and from the computer CS corresponds to the case where the computer C1 functions as the customer computer CS.

(This prediction method)
First, as described above, the prediction method realized by this prediction program is based on (1-1) the procedure for inputting racehorse data and (1-2) the input racehorse data, and the predicted lifetime earned prize data. It has a procedure for acquiring and displaying forecast information data including.

The procedure for inputting the racehorse data (1-1) in the present prediction method is not limited, but is performed by transmitting and inputting the desired racehorse data from, for example, the customer computer CS. It becomes. FIG. 2 shows an example of a screen input by the customer computer CS.

Here, "racehorse data" is data including information about racehorses, and more specifically, it is an object for which one wants to predict how much he / she will be able to play an active role when he / she participates in a race as a racehorse. Refers to data containing information for identifying a racehorse. The information contained in this racehorse data is not limited to the above, but for example, pedigree registration number (pedigree registration number data), horse name (horse name data), date of birth (date of birth data). And combinations of this information can be included, but not limited to this.

Further, the procedure for inputting the racehorse data may include a procedure for searching the racehorse data. Specifically, a plurality of stallion data, a plurality of breeding mare data, a plurality of date of birth data, a plurality of horse name data, etc. are recorded in advance, and this is recorded in a computer display device, for example, a customer computer CS. It is also preferable to display the data on the display device and select it according to the operation from the customer who operates the display device to execute a search procedure such as displaying the racehorse data which can be a candidate on the display device. This has the advantage that the target racehorse can be easily selected without necessarily knowing the pedigree registration number of the racehorse. An example of this case is shown in FIG. This figure is an image of a screen when the search for racehorses is selected in FIG.

Further, the procedure for acquiring and displaying the prediction information data including the prediction lifetime earned prize data based on the race horse data (1-2) input in this prediction method is specifically described in the above procedure (1-1). ) Is received, the computer C1 connects to the computer C2, acquires the forecast information data including the predicted lifetime earned prize data recorded in advance, and predicts that the desired target includes the acquired predicted lifetime earned prize data. This is the procedure for displaying information data. The desired target may be the own computer C1, or may be a display device of the customer computer CS that initially input the racehorse data.

Here, the "predicted lifetime earned prize data" is data recorded corresponding to each racehorse data, and refers to numerical data including information on prizes predicted to be earned by the racehorse in the lifetime. ..

The details of this "predicted lifetime prize money data" will be clarified from the description described later, but the data may include only comprehensive amount information, but may include multiple race information and accompanying information. It is preferable that the data includes information obtained by summing the information. By doing so, it becomes possible to consider more detailed contents.

Further, the "prediction information data" includes the above-mentioned predicted lifetime prize money data, but may also include data including various other information. Specifically, but not limited to, "appropriate evaluation data" and "potential evaluation data" may be included.

Here, the "appropriate evaluation data" is data including evaluation information regarding the aptitude of each racehorse, and specifically, exemplifies turf aptitude, dirt aptitude, distance aptitude, racehorse aptitude, racetrack aptitude, jockey aptitude, and the like. can do. By including comprehensive data on racehorses, users (including customers) can make accurate information judgments.

Further, here, the "potential ability evaluation data" is data including evaluation information regarding the potential ability of the racehorse, and specifically, the race first start time, the race retirement time, the stamina evaluation, the speed evaluation, the constitution evaluation, The growth degree evaluation and the like can be exemplified. By including comprehensive data on racehorses, users (including customers) can make accurate information judgments.

By the way, in this method, the prediction information data may be created when the computer C2 that has received the request from the computer C1 receives the request, and the result may be output to the computer C1, but the prediction information data is created in advance in the computer C2. By recording the data as a database, the system can be realized easily and at high speed, which is preferable. That is, the procedure for acquiring and displaying the prediction information data is as follows: (2-1) The prediction information data corresponding to each of the plurality of racehorse data and the plurality of racehorse data is recorded, and the input racehorse data is used. It is preferable that the procedure is to acquire and display the corresponding prediction information data.

In this method, the output of the result is not limited, but the racehorse data can be input and displayed on the screen of the computer used by the person who desires the result, specifically the computer CS for the customer. preferable.

The method of recording the prediction information data is not limited, but it is preferable to use machine learning. By performing machine learning, it is possible to process information including more multidimensional viewpoints and obtain accurate lifetime prize data. An example of a screen displayed on the customer computer CS is shown in FIG.

Here, the data used in machine learning is not limited, but is limited to a plurality of past race horse data, pedigree data recorded corresponding to each of the plurality of past race horse data, and lifetime earned prize data. , Producer data, production area data, date of birth data, hair color data, market data, age data at the time of transaction, transaction price data, race result data, horse body image data, etc. can be exemplified, but are not limited thereto.

Here, the "past racehorse data" is racehorse data different from the "racehorse data" to be predicted, and is "past" from the viewpoint of racehorse data used as data for machine learning. In other respects, there is no significant difference from the above racehorse data. From this point of view, the same information as the above "racehorse data" can be included.

Here, the "pedigree data" is data including information on the pedigree of the corresponding race horse, for example, a breeding mare (mother), a stallion (father), a mother of a mother, a father of a mother, a mother of a father, and a father. Father, mother mother mother, mother mother father, mother father mother, mother father father, father mother mother, father mother father, father father mother, father father father Information on pedigrees of the third degree can be exemplified, but not limited to this.

In addition, here, "lifetime prize money data" is literally data including information on the amount of prize money that the past racehorse has won in his / her life, and data including information on the race that entered the race and the prize money that was won in that race. It is preferable that the total of the above is used for a more detailed examination. In this case, it is obtained by summing the data including the prize money information recorded in the race result data. If the past racehorse data is an active racehorse, this value will be updated at any time.

Further, the "producer data" is literally data including information on the person who produced the racehorse. Of course, this data may be recorded in correspondence with horses such as father and mother in the above pedigree data.

Further, the "production area data" is literally data including information on the place where the racehorse was produced. Of course, this data may also be recorded in correspondence with each horse such as a father and a mother in the above pedigree data.

Further, the "date of birth data" is literally data including information on the date of birth of the racehorse. Of course, this data may also be recorded in correspondence with horses such as fathers and mothers in the above pedigree data.

Further, the "coat color data" is literally data including information on the date of birth of the racehorse. Of course, this data may also be recorded in correspondence with horses such as fathers and mothers in the above pedigree data.

Further, "market data" is literally data including information on the market in which the racehorse is traded. Of course, this data may also be recorded in correspondence with horses such as fathers and mothers in the above pedigree data.

Further, the "age data at the time of trading" is literally data including information on the age at which the racehorse was traded. Of course, this data may also be recorded in correspondence with horses such as fathers and mothers in the above pedigree data.

Further, the "transaction price data" is literally data including information on the price when the racehorse is traded. Of course, this data may also be recorded in correspondence with horses such as fathers and mothers in the above pedigree data.

Further, the "horse body image data" is literally data including information on the appearance of the racehorse, and more specifically, image data obtained by taking a photograph of the horse body. Of course, this data may also be recorded in correspondence with horses such as fathers and mothers in the above pedigree data. The horse body image may be data at a specific age, or may include age information and record image data at a plurality of ages.

Further, the "race performance data" is literally data including information on the race performance of the racehorse. Here, it is preferable that the information regarding the race results includes the conditions of the race and the like. Information on this race result is not limited, but is, for example, date (date data), weather (weather data), racecourse (racetrack data), racecourse status (raceground status data), race number (race). Number data), race name (race name data), grade (grade data), race class (race class data), race conditions (race condition data), turf dirt classification (turf dirt classification data), left-right rotation (left-right rotation data) ), Distance (distance data), inside / outside (inside / outside data), main prize (main prize data), additional prize (additional prize data), frame number (frame number data), horse number (horse number data), order of arrival (arrival order data) ), Burden weight (load weight data), time (time data), difference in arrival (difference data), popularity (popular data), odds (odds data), jockey (joker data), etc. Not limited to. In addition, it is preferable that a large number of race results are recorded for one racehorse. For active racehorses, it is preferable to add this data at any time. When the main prize money and the additional prize money are recorded separately, it is preferable to treat the total prize money, which is the total, as prize money data.

In addition, it is also preferable to modify and record the prize data including the information of the prize money such as the main prize money or the additional prize money in the above. While this system predicts the prize money to be won in the future, there are many cases where the current situation and the prize money of the race are different. In such a case, it is possible to predict a more accurate predicted prize money by modifying this data or information on the prize money of the race in advance.

Further, it is preferable that the "race result data" includes not only the information on each of the above races but also the information on the first race start date and time and the race retirement time.

Here, machine learning is a technique that uses so-called artificial intelligence to find regularity and rules from input data indicating goals and to improve judgment by iterative learning. Regarding artificial intelligence, TensorFlow (registered trademark) provided by Google (registered trademark) is preferable, but not limited to this.

Specific algorithms for machine learning include linear regression by regression, logistic regression, support vector machine, decision tree by tree, regression tree, random forest, gradient boosting tree, simple bay by Bayes, AR, MA, etc. (S) ARIMA model, state space model, k-nearest neighbor method by clustering, boosting, bagging, perceptron, deep learning by neural network, convolutional neural network, regression neural network, residual network, etc. can be exemplified. Not limited to. Although not limited, in the case of a method such as deep learning by the above neural network modeled on the human brain, for example, a cloud server such as Google (registered trademark) Cloud ML Engine (registered trademark) is used. Is preferable.

As described above, as is clear from the above description, in this system, while a large amount of data on past racehorses is used for mechanical learning, this data is used in advance for races scheduled to be traded in the market for racehorses. By entering horse data, you will get information to quantify and maximize the potential competitiveness of the racehorse, such as how much prize the racehorse to be traded can win. You will be able to do it.

By the way, when actually providing a service to a customer through a telecommunication line, money may be exchanged. Specifically, it may be necessary to pay the consideration when providing the above data. In such a case, it is useful to identify the customer and determine whether or not the customer can provide the current service. An example in this case is shown below.

First, the procedure for requesting the customer computer CS to enter (0-1) customer identification number data and its password data, and (0-2) authentication based on the entered customer identification number data and password data. Procedure to be performed, (0-3) If the authenticated customer identification number data is valid, the screen shifts to the above-mentioned race horse data input screen, while if it is not valid, the above-mentioned customer identification number data and password are displayed again. It is preferable to have a procedure for requesting data input or for ending processing. By doing so, it is possible to provide an appropriate service.

In this case, in the procedure (0-2), not only a simple check of whether the customer identification number data and the password data correspond, but also whether the customer is effectively paying the predetermined amount. It is also preferable to judge the customer effectiveness as to whether or not. By doing so, it is possible to provide appropriate services. In order to realize this procedure, it is preferable to record the customer identification number data, the password data thereof, and the data related to the customer effectiveness as a database in the computer C1 or C2, preferably the computer C1.

In this case, it is preferable that the customer performs the registration procedure in advance, the computer C1 notifies the result of the registration procedure, and the customer pays a predetermined fee in advance (adopting the customer pre-registration system). In some cases, money may be exchanged each time the customer wants to obtain data. In this case, instead of customer identification number data and password data, or in addition, request input of credit data including credit information related to credit card and transfer, output this data to a predetermined financial institution, and the answer is valid. If it is determined that the data is not correct, the screen may shift to the above race horse data input screen.

As described above, the system S can predict the information for quantifying and maximizing the potential competitive ability of the racehorse, the potential ability prediction program of the racehorse, the potential ability prediction method of the racehorse, and the race. A horse potential prediction system can be provided.

(Embodiment 2)
(Stallion candidate presentation system)
According to the system according to the first embodiment, the potential ability of a racehorse can be predicted with high reliability. Then, by using this, it becomes possible to provide a new system, specifically, a system for presenting stallion candidates (hereinafter referred to as "this presentation system"). This will be described in detail below. In this embodiment, only the relationship between the data to be transmitted (output) and the data to be received (input) is different, and the description of the same and overlapping parts as in the first embodiment will be omitted.

The outline of the present presentation system S is the same as that in FIG. 1, but the present presentation system S includes (1) the procedure for inputting the breeding marine data and the predicted lifetime earned prize data based on the input breeding mare data. Computer C1 in which the stallion candidate presentation program for executing the procedure for acquiring and displaying the prediction information data is recorded, (2) a plurality of past race horse data, and a breeding female horse corresponding to the past race horse data. Machine learning is performed by including data, stallion data, and lifetime earned prize performance data, and a procedure of creating and recording predicted information data including predicted lifetime earned prize data for each race horse data is executed. It is provided with a computer C2 in which a predicted lifetime earned prize database creation program is recorded.

This presentation system S assumes the producers and owners of racehorses as specific customers, and achieves better results by mating their own breeding mares with any stallion from the customer computer CS. It is used to predict whether a racehorse will be born.

In the present presentation system S, as described above, based on (1-1) the procedure for inputting the breeding marine data and (1-2) the input the breeding marine data, the forecast information data including the forecast lifetime earned prize data is acquired. It has a computer C1 in which a stallion candidate presentation program for executing the procedure of displaying the data is recorded.

Here, the "breeding mare data", as is clear from the above description, is data including information for identifying a breeding mare that is desired to be mated with a stallion. The breeding mare horse data is not limited, but the same data as the racehorse data in the first embodiment can be adopted, for example, a pedigree registration number (pedigree registration number data) and a horse name (horse name data). ), Date of birth (date of birth data) and a combination of this information can be included.

In (1-1) of the present presentation system S, basically, the "racehorse data" in the first embodiment can be read as "breeding mare data".

Further, unlike the first embodiment, the present presentation system S includes a procedure of acquiring and displaying forecast information data including predicted lifetime prize money data based on the input breeding mare data (1-2). .. Here, the definitions of "predicted lifetime prize money data" and "predicted information data" are the same as those in the first embodiment.

However, in the present presentation system S, although the "prediction information data" is displayed based on the input breeding mare data, the racehorse generated when a plurality of "sire data" and each of them are crossed. Display multiple sets of "forecast information data" in. As a result, in this presentation system, when a breeding mare is identified, it becomes possible to evaluate which stallion is mated with to produce a racehorse with a higher lifetime prize money. In this case, FIGS. 5 and 6 show an image of a screen at the input of a customer computer that wants to acquire information, and FIG. 7 shows an image of a screen showing an output result. Note that FIG. 6 is an image diagram of the screen when the search means is adopted in FIG.

The number of stallion is large, and it is not impossible to calculate and display all of them, but a combination of a certain amount or more of the predicted lifetime acquisition amount or a combination of a certain number of predicted lifetime acquisition amounts from the top. Is preferably selected and displayed, and more preferably, it is displayed in descending order of the predicted lifetime earned amount. By doing so, it is possible to provide information that is easier for the customer to judge.

Therefore, in the present presentation system S, the prediction information data is recorded in advance by machine learning using artificial intelligence according to the same procedure as in the first embodiment, and when there is an input from the computer C1, this result is obtained. In order to display, the possibility of mating with multiple breeding stallion for each breeding mare is examined, and the identification number data of the child between the breeding mare and the breeding mare is given, and each identification number is given. It is preferable to create prediction information data and record it in advance.

As described above, in addition to the above-described first embodiment, the present presentation system S pays attention to the relationship between the breeding mare and the stallion, and applies the above to present the optimum stallion to the breeding mare. It is possible to provide a presentation program, a mare candidate presentation method, a mare candidate presentation system, and a predicted lifetime winning prize database creation program used for these.

The present invention relates to a racehorse potential ability prediction program, a racehorse potential ability prediction method, a racehorse potential ability prediction system, a stallion candidate presentation program, a stallion candidate presentation method, and a species. It has industrial potential as a stallion candidate presentation system and as a predictive lifetime winning database creation program used for these. The present invention promotes improvement of operational efficiency in racehorse production, helps to produce racehorses with higher competitive ability, and activates transactions by providing high value-added information on racehorse transactions and racehorse investment. Helps to become. Furthermore, it can be used for information provision and publishing by telecommunication lines such as the Internet, which will contribute to the expansion of the horse racing competition industry.

Claims (7)

On the computer
Procedure for entering racehorse data,
A racehorse potential competitive ability prediction program for executing a procedure of acquiring and displaying prediction information data including predicted lifetime earned prize data based on the input racehorse data. Procedure for entering racehorse data,
A method for predicting the potential competitiveness of a racehorse, which comprises a procedure for acquiring and displaying prediction information data including predicted lifetime earned prize data based on the input racehorse data. A racehorse potential competitiveness prediction program for executing a procedure for inputting racehorse data and a procedure for acquiring and displaying forecast information data including predicted lifetime earned prize data based on the entered racehorse data. The computer on which the data was recorded and
Machine learning is performed by including a plurality of past racehorse data, breeding female horse data corresponding to the past racehorse data, stallion data, and lifetime earned prize performance data, and the predicted lifetime for each racehorse data. A racehorse potential competitiveness prediction system that includes a computer on which a predictive lifetime earned prize database creation program is recorded to perform a procedure for creating and recording forecast information data, including earned prize data. On the computer
Procedure for entering breedmare data,
A stallion candidate presentation program for executing a procedure of acquiring and displaying predicted information data including predicted lifetime earned prize data based on the input breeding mare data. Procedure for entering breedmare data,
A method for presenting a stallion candidate, comprising a procedure for acquiring and displaying predicted information data including predicted lifetime earned prize data based on the input breeding mare data. Procedure for entering breedmare data,
A computer in which a stallion candidate presentation program for executing a procedure of acquiring and displaying predicted information data including predicted lifetime winning prize data based on the input breeding mare data is recorded, and a computer.
Machine learning is performed by including a plurality of past race horse data, breeding female horse data corresponding to the past race horse data, stallion data, and lifetime earned prize performance data, and predicted lifetime for each race horse data. A stallion candidate presentation system that includes a computer on which a predictive lifetime earned prize database creation program is recorded to perform a procedure for creating and recording forecast information data, including earned prize data. On the computer
Machine learning is performed by including a plurality of past racehorse data, breeding mare data, stallion data, and lifetime winning prize data corresponding to the past racehorse data, and the predicted life is predicted for each of the racehorse data. A predictive lifetime earned prize database creation program for the procedure of creating and recording forecast information data, including earned prize data.