JP2003315468A - Wave predictor and wave prediction information provision system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a wave predictor predicting wave information concerning waves near a coast and a wave prediction information provision system. <P>SOLUTION: The wave predictor 1 connected with a terminal 3 by way of a communication line network 5 and predicting wave information of specific items at the coast of an objective point comprises a wave prediction model formula production means for preparing a wave prediction model formula for predicting wave information through a multiple regression analysis based on basic data including a measured results on wave information at the objective point, wave GPV data concerning the measured results and data concerning at least one of geography at the objective point or tide. It also comprises a gaining means for gaining a specific wave GPV data, a wave prediction results calculation means calculating the prediction results by substituting the gained wave GPV data in the prepared wave prediction model formula, and a transmission means transmitting the calculated prediction results of wave information to the terminal 3. <P>COPYRIGHT: (C)2004,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a wave predicting apparatus for predicting wave information about waves generated on a coast, and a wave predicting information providing system using the wave predicting apparatus.

[0002]

2. Description of the Related Art Conventionally, numerical prediction grid point values (hereinafter referred to as GPV) distributed by the Meteorological Agency as prediction information about waves.
There is data (called Grid Point Value). This G
The PV data includes 6 items for 6-minute mesh (about 10 km mesh), wave height, wind direction, wind speed, wave direction, and period.
There is wave numerical prediction model GPV (hereinafter referred to as wave GPV) data predicted up to 72 hours ahead at time intervals, and this wave GPV data is distributed twice a day.

[0003]

By the way, since the above-mentioned wave GPV data is information on waves in units of 10 km centering on the offshore as described above, the wave conditions near the coast are not necessarily the same numerical values. . Therefore, Wave GPV
The data is for those who need wave information near the coast, for example,
It was not very useful information for enthusiasts and other marine sports enthusiasts, anglers, coastal workers, and those engaged in coastal fisheries. On the other hand, examples of information about waves near the coast include wave buoys, actual measurement data from the coast, and visual observations from ships. It was difficult to accurately predict the situation.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a wave prediction device and a wave prediction information providing system for predicting wave information about waves near the coast.

[0005]

In order to solve the above-mentioned problems, the invention according to claim 1 predicts wave information of a predetermined item on the shore of a target point, for example, as shown in FIGS. A wave prediction device (wave prediction system 1),
Predicting the wave information by multiple regression analysis based on wave prediction basic data including the actual measurement result of the wave information at the target point, the wave GPV data related to the actual measurement result, and the data regarding the topography at the target point. A wave prediction model formula creating means for creating a wave prediction model formula (for example, the control unit 11 or the like), and an acquisition unit for acquiring predetermined wave GPV data (for example, the control unit 11, the data storage server 20, or the like). , The wave GPV acquired by the acquisition means
Wave prediction result calculation means (for example, the control unit 11 or the like) that substitutes the data into the wave prediction model expression created by the wave prediction model expression creation means to calculate the prediction result of the wave information on the coast of the target point. And an output unit (for example, the display unit 12, the output unit 14, etc.) that outputs the prediction result of the wave information calculated by the wave prediction result calculation unit.

Here, the wave information is, for example, the size of the wave, the shape of the wave, the evaluation of the state of the wave for a predetermined purpose, the speed of the wave, the shape when the wave collapses, the speed of breaking the wave. However, the information is not limited to these and may be in any form such as a numerical value, text, voice, and image.

The actual measurement result of wave information is actual measurement data in various items of the above-mentioned wave information, and any method may be used for actual measurement. Further, the wave GPV data includes, for example, data on items such as wave height, wave direction, period, wind speed, and wind direction, but is not limited to these. Further, the terrain data may be any data as long as it is the terrain data that affects the waves at the target point, for example, the inclination angle from the offshore to the shallow water,
The size of the shallow side, the shape of the coastline, how the sand accumulates on the shallow, etc. may be any.

According to the first aspect of the present invention, the wave prediction model formula creating means measures the wave information of the target point, the wave GPV data related to the measured result, and the landform data at the target point. Based on the wave prediction basic data, a wave prediction model for predicting wave information is created by multiple regression analysis, and the wave GPV data acquired by the acquisition means by the wave prediction result calculation means is a wave prediction model formula. Since it is substituted into the wave prediction model formula created by the creating means and the prediction result of the wave information on the coast of the target point is calculated, the target point is considered by considering the topography of the target point compared to the wave GPV data. It will be possible to obtain more accurate wave prediction information on the coast.

According to a second aspect of the present invention, there is provided a wave prediction device (wave prediction system 1) for predicting wave information of a predetermined item on a coast of a target point, the measurement result of the wave information of the target point, Wave GPV data related to the measurement results,
Wave prediction model formula creating means for creating a wave prediction model formula for predicting the wave information by multiple regression analysis based on wave prediction basic data including data on the tide at the target point (for example, the control unit 11 Etc.) and an acquisition unit (for example, the control unit 1) that acquires predetermined wave GPV data.
1. Data accumulating server 20, etc.) and the wave GPV data acquired by the acquisition unit are substituted into the wave prediction model formula created by the wave prediction model formula creating unit, and wave information at the coast of the target point is calculated. Wave prediction result calculation means (for example, the control unit 11 or the like) for calculating the prediction result and output means (for example, the display unit 12, the output unit) that outputs the prediction result of the wave information calculated by the wave prediction result calculation unit. 14
Etc.), and are provided.

The tide data is, for example, data relating to items such as tide level, tide, and tidal current, but may be any data as long as it relates to tides that affect waves.

According to the second aspect of the present invention, by the wave prediction model formula creating means, the measurement result of the wave information of the target point, the wave GPV data related to the measurement result, and the data on the tide at the target point, A wave prediction model for predicting wave information by multiple regression analysis is created based on wave prediction basic data including, and the wave GPV data acquired by the acquisition means is calculated by the wave prediction result calculation means,
Since it is substituted into the wave prediction model formula created by the wave prediction model formula creating means to calculate the prediction result of the wave information at the coast of the target point, it is based on the conditions related to the tide at the target point as compared with the wave GPV data. It becomes possible to obtain more accurate wave prediction information on the coast of the target point.

According to a third aspect of the present invention, in the wave prediction apparatus according to the second aspect, the tide-related data includes at least one of tide level data, tide data and tide state data at a target point. Characterize.

Here, the tidal current data is data relating to the degree of influence of the tidal current on the waves. For example, in a place located at the mouth of a river, the current from the river is also included in the tidal current. Further, the tide state data is data regarding the magnitude of the difference in tide level over time, but may be any data as long as it is data regarding the movement of the tide and the strength of the movement.

According to the invention of claim 3, the same effect as that of the invention of claim 2 can be obtained, and in particular, regarding the tide data, the tide level data, the tide data, the tide data at the target point can be obtained. Since at least one of the state data is included, it becomes the wave prediction information considering the influence of the tide level, the tidal current, and the tide state data on the wave, so that it is possible to obtain the prediction information that is closer to the actual measurement value.

According to a fourth aspect of the present invention, in the wave predicting device according to any of the first to third aspects, the prediction result of the wave information is numerical data relating to the magnitude of the wave, and relates to the magnitude of the wave. It is characterized in that it is provided with a text conversion means for converting numerical data into text data relating to the magnitude of the wave.

According to the invention described in claim 4,
Of course, the same effect as that of the invention described in any one of 3) can be obtained, and in particular, since the text conversion means converts the numerical data regarding the wave size into the text data regarding the wave size, The wave prediction information can be obtained in a more concrete and easy-to-understand form.

The invention according to claim 5 is the same as that of claims 1 to 4.
Corresponding to the effect of wind in the wave prediction device described in
Stores predictive information about the conditions of a given wave
Wave condition prediction information storage means (wave condition
Extraction program 16b, text DB 16d, etc.)
Wind data of elephant site and wind of GPV data
The wave condition data due to the influence of wind.
Wave condition prediction information
Wave condition for extracting from prediction information storage means
Prediction information extraction means (for example, control unit 11 or the like) and the wave
Waves extracted by the condition prediction information extraction means
Second output method to output the prediction information about the condition
A stage (for example, the display unit 12, the output unit 14, etc.)
It is characterized by

Here, the wave condition prediction information is
It is information about the state of the wave due to the influence of the wind, the size of the wave, the shape of the wave, the shape and the size of the wave when the wave collapses, but the information is not limited to these.

According to the invention of claim 5, claim 1
Of course, the same effect as that of the invention described in any one of 4) can be obtained. In particular, the wind condition prediction information extracting unit extracts the wind from the data on the wind at the target point and the data on the wind in the GPV data. Prediction information about the wave condition due to the influence is extracted from the wave condition prediction information storage means, and the second output means outputs the wave condition prediction information about the wave condition. Therefore, it is impossible to understand the GPV data. Prediction information of wave conditions due to the influence of nearby wind can be obtained.

According to a sixth aspect of the present invention, the wave prediction device for predicting wave information of a predetermined item on the coast of the target point and the terminal device (for example, the user terminal 3 or the like) are connected to the communication line (network 5 or the like) In the wave prediction information providing system (wave prediction information providing system 100) connected via, the wave prediction device is a measurement result of the wave information at a target point,
Wave prediction for predicting the wave information by multiple regression analysis based on wave prediction basic data including wave GPV data related to the actual measurement result and data on at least one of topography or tide at the target point. Wave prediction model formula creating means for creating a model formula and a predetermined wave GP
The wave GPV data acquired by the acquisition unit that acquires the V data and the acquisition unit is substituted into the wave prediction model formula created by the wave prediction model formula creation unit to obtain the wave information of the coast at the target point. Wave prediction result calculation means for calculating the prediction result, and transmission means for transmitting the prediction result of the wave information calculated by the wave prediction result calculation means to the terminal device (for example, Web server 30, communication unit 32, etc.)
And the terminal device (for example, the user terminal 3 or the like).
The output means (for example, the display unit 3b or the like) that outputs the prediction result of the wave information transmitted by the transmission means.

According to the sixth aspect of the present invention, the wave prediction model equation creating means of the wave predicting apparatus measures the wave information of the target point, the wave GPV data related to the measured result, and the landform at the target point. Alternatively, a wave prediction model formula for predicting wave information by multiple regression analysis is created based on the wave prediction basic data including at least one of the tides, and acquired by the wave prediction result calculation means and the acquisition means. The calculated wave GPV data is substituted into the wave prediction model formula to calculate the prediction result of the wave information on the coast of the target point, the transmitting unit transmits the prediction result of the wave information to the terminal unit, and the output unit of the terminal unit. Since the prediction result of the wave information transmitted from the wave prediction device is output by the wave prediction device, the wave G is transmitted to the user who is the operator of the terminal device.
As compared with PV data, it is possible to easily provide more accurate prediction information on the coast of the target point.

According to a seventh aspect of the present invention, in the wave prediction information providing system according to the sixth aspect, the wave information measuring device (wave information measuring device 4) that actually measures the wave information at the target point is the wave predicting device. A wave information receiving unit (for example, the control unit 11 or the like) that is connected via a communication line and that receives the measurement result of the wave information by the wave information measuring device.
And a wave actual measurement result storage unit (for example, actual measurement D) that stores the actual measurement result of the wave information received by the wave information receiving unit.
B23c etc.) and wave GPV data storage means (for example, G
PVDB23a) and the like.

According to the invention of claim 7, the same effect as that of the invention of claim 6 can be obtained, and in particular, the wave information measuring device for actually measuring the wave information of the target point can predict the wave. The device is connected to the device via a communication line, the wave information receiving means of the wave predicting device receives the measurement result of the wave information by the wave information measuring device, and the wave measurement result storage device stores the measurement result of the wave information. Since the wave GPV data storage means stores the wave GPV data related to the measurement result, the wave prediction information can be calculated by the correlation between the wave information of the measurement result and the related wave GPV data. , It is possible to provide prediction information that is closer to the actual measurement data.

According to an eighth aspect of the invention, in the wave prediction information providing system according to the sixth or seventh aspect, the wave prediction device stores the prediction information regarding the condition of the wave associated with the influence of wind. Prediction information storage means (wave condition extraction program 16b, text DB 16d, etc.), data on wind at the target point,
A wave condition prediction information extracting unit for extracting wave condition prediction information concerning a wave condition due to the influence of the wind from the wave GPV data and the wave condition prediction information extracting unit for extracting from the wave condition prediction information storage unit. A second for transmitting the extracted wave condition prediction information to the terminal device;
Transmission means (for example, Web server 30, communication unit 32)
Etc.), and the terminal device includes second output means (for example, the display unit 3b or the like) that outputs the wave condition prediction information transmitted by the second transmission means.

According to the invention described in claim 8, it goes without saying that the same effect as that of the invention described in claim 6 or 7 can be obtained, and in particular, by the wave condition prediction information extraction means of the wave prediction device, Wind data at the location and wave G
Wave condition prediction information due to the influence of the wind is extracted from the wave condition prediction information storage means from the PV data related to the wind, and the second condition transmitting means transmits the wave condition prediction information to the terminal device. Since the second condition output means outputs the wave condition prediction information, it is possible to provide useful information especially to the user who needs the condition information of the wave near the coast.

[0026]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings.

First, the configuration will be described. FIG. 1 is a diagram showing the overall configuration of a wave prediction information providing system according to the present invention.
The wave prediction information providing system 100 shown in FIG. 1 is a source of the wave prediction information and a wave prediction system 1 capable of predicting wave information about a wave and distributing the predicted wave information as wave prediction information via a network. A GPV distribution server 2 that distributes wave GPV data, a user terminal 3 operated by a user who needs wave prediction information, and a wave information measuring device 4 are connected by a network 5.
Here, the network 5 is a communication line network or the like, and may be any network such as an open network such as the Internet or a dedicated line.

The wave prediction system 1 is used as a wave prediction device.
A system having a function of predicting various kinds of information regarding waves and distributing the prediction information to other terminals or the like via the network 5, and as shown in FIG. 1, a main server 10 and a data storage server 20. , The Web server 30 and the like, and the servers are connected to each other.

The main server 10 is a main device for extracting and calculating the wave prediction information in the wave predicting system 1 according to the present invention, and also has a function as a terminal device operated by an operator and stores data. Storage server 2
0, input of various processing instructions to the Web server 30, etc.,
It is used for maintenance of each part of the above-mentioned servers, management of data input, maintenance, and the like. And the main server 10
2, as shown in FIG. 2, for example, the control unit 11 and the display unit 1
2, input unit 13, output unit 14, communication unit 15, storage unit 1
6, a converter 17 is provided, and each unit is connected by a bus 18.

The control unit 11 includes a control unit for controlling each unit,
It is provided with a CPU that performs data transfer, determination processing, and the like, a storage area that temporarily stores programs and data, and a RAM that forms a work area that is processed by an input instruction and input data. Then, the control unit 11 executes each control process according to various application programs stored in the storage unit 16.

The display unit 12 is composed of, for example, a CRT or LCD, and displays various display data and images input from the control unit 11. Specifically, for example, calculation data for calculating and extracting the wave prediction information, calculation result data, and the like are displayed. The data displayed on the display unit 12 is not limited to the data stored in the main server 10, and the data stored in the data storage server 20 and the Web server 30 can also be displayed. .

The input unit 13 is provided with, for example, a keyboard, a mouse, etc., and selects and specifies the selection information displayed on the screen of the display unit 12, the data storage server 20, and the Web.
It is used as an input for updating various databases stored in the server 30. In addition, the input unit 13
For example, an input device such as a scanner or a CCD camera for inputting the state of the wave, the state of the shore, and the like such as images and sounds may be provided.

The output unit 14 is, for example, a printing machine, and based on the print data output from the control unit 11,
Print the calculated wave prediction information.

The communication unit 15 is composed of, for example, a modem, a terminal adapter, a router, or the like, and performs control for performing communication with an external device via a communication line such as a telephone line, an ISDN line, or a leased line. .

Programs, data and the like are stored in advance in the storage unit 16, and the storage unit 16 includes a recording medium readable by the control unit 11 such as a magnetic or optical recording medium or a semiconductor memory. It is a composition. This recording medium includes, for example, a portable medium such as a CD-ROM and a memory card, and a fixed medium such as a hard disk. Also,
A part or all of the programs, data, etc. stored in the storage unit 16 may be received from the communication unit 15 from another server via a network such as WAN or LAN. It may be a storage unit of the external server constructed above.

The storage unit 16 stores the system program of the present invention, various application software (not shown), and the like, and includes, for example, multiple regression analysis software. As shown in FIG. 2, the storage unit 16 stores, for example, the model formula calculation program 16a,
Wave condition extraction program 16b, tide level calculation program 16c, text DB 16d, model formula DB 16
e is recorded and stored.

The model formula calculation program 16a is a program for calculating a model formula for calculating the wave size (wave height), which is one of the wave prediction information, and is a basic part of the data storage server 20 to be described later. A series of processing operations for calculating a model formula is programmed by extracting a population that meets certain conditions from the basic data stored in the DB 23b and performing multiple regression analysis on the population data. There is. By inputting the wave GPV data relating to the target point into the model formula calculated by the model formula calculation program 16a, the wave size (wave height) of the target point is calculated by numerical data.

Wave condition extraction program 16b
Is a program for extracting the wave condition information from the wave prediction information, and
Is a program for determining a wind influence pattern from data such as a wind direction and a wind speed stored in an actual measurement DB 23c and a GPVDB 23A described later, and extracting wave condition information associated with the wind influence pattern. .
Specifically, the wave condition information is information about the shape, size, undulation state, breaking wave shape, breaking wave speed, etc. of the wave that changes due to the influence of the wind. Then, the condition information of the wave is extracted by a wind influence pattern obtained by multiplying two constituent elements of the wind type (for example, eight types) and the wind strength (for example, five types). ing.

Therefore, in order to extract the wave condition information at the time of the prediction at the target point, it is necessary to first determine the influence pattern of the wind. There are eight types of winds that make up this influence pattern, for example, offshore (wind from the shore), onshore (wind from the offshore), sideshore (crosswind), and crossshore, which are classified by 45 degrees. There is. The number of types is not limited to eight. And this kind of wind is related to the wind direction of the target point,
For example, at the point A, when the wind direction is northwest, it is associated with offshore, and when it is southeast, it is associated with onshore.

The strength of the wind, which is another component of the influence pattern of the wind, is related to the wind speed. For example, when the wind speed (m / sec) is 0 m to 2 m, there is no wind / light breeze.
When 2.1 m to 3.5 m, the wind is weak, 3.6 m to 5 m is medium wind, 5.1 m to 8 m is medium strong wind, and 8 m or more is strong wind.

Therefore, for example, when the wind direction at the time of prediction at the point A, which is the target point, is southeast,
It is classified as onshore and when the predicted wind speed is 7 m, it is classified as medium wind. In this onshore, the influence pattern of the wind is determined by the combination of the condition of the medium wind, and the influence pattern of the wind is digitized into the influence pattern number of the wind in order to extract the condition information of the wave. The wind influence pattern number may be determined from composite condition data such as the wind direction and wind speed of the target point and the wind direction and wind speed data of the GPV corresponding to the prediction.

The tide level calculation program 16c is a program for calculating the tide level data which changes depending on the date and time due to the influence of the tide. For example, by inputting the date and time and the point data to be predicted into a predetermined arithmetic expression, the tide level is calculated. The data is configured to be calculated.

The text DB 16d is a database for storing text data of wave prediction information provided to the user. Specifically, the numerical data of the wave size calculated by inputting the wave GPV data into the model formula calculated by the model formula calculation program and the influence pattern of the wind extracted by the wave condition extraction program 16b. A text conversion program 16da for converting a number and predetermined text data,
Text conversion data 16db and measured text data 1
6 dc, wave condition text data 16 dd, etc. are stored. Then, based on the configuration data of the text DB 16d, the numerical data of the wave size is converted into the text data related to the wave size, and the wind influence pattern number extracted by the wave condition extraction program 16d is converted into the text data related to the wave condition. To be converted.

Specifically, the text conversion data 16db is associated with the wave size value data 310 and the text data 320 representing the size of the wave as a part of a person. For example, as shown in FIG. The conversion table 300 is stored. Here, the wave size value data refers to numerical data of significant waves. Here, the significant wave is a concept defined as a statistical average amount of waves to represent the height of irregular waves. Specifically, for example, all waves of the waveform record data measured by a wavemeter for a predetermined time are selected in descending order of wave height, and one-third of the total number is counted from the largest one, and the average of those wave heights and periods is taken. Is the data obtained. And the wave height of this significant wave and the period data are
It is almost the same as the wave height and period data (that is, observation data) visually observed by an expert. Wave size value data 310 in the conversion table 300 of FIG. 3 indicates numerical data of wave size in units of 10 cm. For example, text data 3
"Sune", which is 20, represents the height of the wave of 25 cm, and "peach" represents the height of the wave of 70 cm. Also,
“Set”, “tamano”, “upper”, “a little” and the like are coefficients used for fine adjustment for calculating the significant wave.
More specifically, for example, “Set” and “sometimes” are used when the wave period is long and a large wave sometimes occurs. As a result, numerical data of simple wave height is
It becomes possible to express in detail the state of the wave according to the human interval by visual inspection.

Among the measured data, the visually observed data is based on the items of the text data 320, for example,
It is actually measured in the form of observation text data such as "Koshi-Munetamakata". Therefore, this text conversion data 16db is used when digitizing the observed text data. Also, the text conversion data 16db is
On the contrary, it is also used as reference data when converting the numerical data of the wave size calculated as the wave prediction information into the text data to be provided to the user.

The actual measurement text data 16dc is the above-mentioned visual observation data. For example, the observation text data, the observation date and time, the observation place, the observation numerical value (data digitized based on the conversion table 300), and the observation time It is data that is associated with various data in items such as the type of wind. Then, the measured text data 16dc is used as reference data when converting the wave size value data as the above-described wave prediction information into text data. Specifically, the numerical data of the wave size as the wave prediction information is calculated by the model formula described later, but when the numerical data of the wave size is converted into text, a plurality of text data may be applicable. For example, when the numerical data of 11.0 (110 cm) is calculated, when performing text conversion based on the text conversion data 16db, there are text conversion candidates such as “before and after Hara” and “Kosi-Mune”. Therefore, the various condition data of the measured text data 16dc is compared with the various conditions as the wave prediction information, and the optimum text data regarding the size of the wave is determined based on the observed text data of the approximate condition. . The condition data may be any data,
In particular, wind type data such as offshore (wind from shore) and onshore (wind from offshore) is particularly important. For example, in case of offshore, wave height (size)
In the case of onshore where the variation of is small and the period is long,
This is because the type of wind is an important factor in determining which wave size is converted into text data, because the wave height has a large variation and the cycle is short. The observed text data in the measured text data 16dc may be included in the basic DB 23b.

Wave condition text data 16dd
Is data in which different types of wind, which are components of the wind influence pattern, are associated with different text data for each prediction target point depending on the combination of wind strength. That is, for example, wind type (8 types) x wind strength (5
It is the condition text data of the wave corresponding to each prediction target point of the wind influence pattern of (type) = 40. Therefore, the wave condition text data 16dd is determined and extracted according to the wind influence pattern number.
The text data of the wave condition is text data related to the influence of the wind type (for example, onshore, offshore, sideshore, crossshore, etc.) and the strength of the wind on the wave. Correlates with text data about size.

The model formula DB 16e is a database for storing a plurality of model formulas calculated by the model formula calculation program 16a. And the model formula is
It is a model formula for calculating the numerical data of the wave size of the wave prediction information. Then, the calculation method of the model formula is as follows. First, a population of the model formula is created from the data of the basic DB 23b described later and predetermined condition data input by the operator, and then the population is subjected to multiple regression analysis. It is created by doing. Therefore, various model formulas are calculated according to the condition data input to create the population, and thus the model formula DB 16e stores a plurality of various model formulas. As will be described later, the condition data is, for example, latitude and longitude of the target point. In addition, basic DB23
As each piece of data in b is updated, new model formulas are sequentially calculated and stored in the model formula DB 16e.
The model formula DB 16e stores new model formulas one after another and, for example, by sequentially comparing a plurality of model formulas, for example, the degree of importance of the correlation coefficient of the items constituting the model formula can be determined. Since this is possible, it is possible to calculate a more accurate model formula.

The converter 17 is a device for amplifying the measured data signal of the wave information transmitted from the wave information measuring device 4, AD-converting it, and outputting it to the control unit 11.

The data storage server 20 is the main server 1
A database server that stores various data used for extraction and calculation processing of wave prediction information executed by 0,
System for searching databases, eg RD
BMS (Relational DataBase Management System)
And so on. As shown in FIG. 4, the data storage server 20 internally includes a control unit 21, a communication unit 22, and a storage unit 23, whose functions are the main server 1
Since they are similar to those of No. 0, detailed description thereof will be omitted, and only different points will be described below.

The control unit 21 of the data storage server 20 retrieves the data stored in the storage unit 23 according to the data request signal output from the control unit 11 of the main server 10 and outputs it to the main server 10. It controls the data retrieval process and the data transmission process.

The storage unit 23, as shown in FIG.
It has a DB 23a, a basic DB 23b, and an actual measurement DB 23c.

The GPVDB 23a is the GPV distribution server 2
It is a database that manages and stores the GPV data that is distributed. Here, GPV data means 1 by the Japan Meteorological Agency.
The GPVDB 23a stores the wave data PVP, which is announced twice a day at 6-hour intervals up to 72 hours ahead, and in particular, the wave data GPV data, which is the wave data prediction data of 10 km mesh. Specific record items include, for example, the date and time of the announcement, the estimated date and time (how many hours after the time of the announcement the forecast), the predicted location (latitude, longitude), the wave height (height of wave, size), The direction in which the energy of the waves is transmitted), wind direction, wind speed, period, etc. are included. This GPV data is 10K as described above.
Since the data is in units of m, it is offshore data rather than the data of the target point provided as the wave prediction information.

The basic DB 23b is a database for storing basic data for extracting the model formula,
Measured data of wave size at a target point near a certain coast, GPV data for which the measured time (or almost measured time) of the measured data is predicted, and tide level data and predicted tide state data for the predicted target of the GPV data , Topographic data, tidal current data, weather map data, etc. are stored in association with each other. The constituent data of these basic data are all digitized data.

The actual measurement data includes actual measurement data of wave size. And, while the GPV data is prediction data such as wave heights offshore in units of 10 Km mesh, the actual measurement data is actual measurement data regarding wave height (wave size numerical data) in a predetermined latitude and longitude unit corresponding to the prediction target point. Is. The actual measurement data is numerical data and also includes numerical data of wave size of breaking waves near the coast. The actual measurement data is observation data obtained by visual observation, data measured by an arbitrary measuring device, or the like. In the case of the observation data by visual observation, the actual measurement data is data in which the size of the wave is visually expressed by the part of the person based on the items of the text data 320 of the conversion table 300. It is data quantified by a predetermined calculation formula based on 300. For example, "Sune" = 2.5
A wave size of 25 cm, "Hara" = 11 is 110c
It represents the size of a wave of m. The observation text data of the measurement text data 16dc may be included in the basic DB 23b as the measurement data.

The tide level data is data obtained by the above-mentioned tide level calculation program 16c or the like, or data announced by a predetermined institution or the like. This tide level data is
For example, it may be a plurality of tide level data such as high tide, low tide, and average. Further, the tide state data is, for example, data regarding the types of tide states such as ebb tide, rising tide, tide at high tide, and tide at low tide. Shows. That is,
It is data of the change in the tide flow whether the predicted time is toward the rising tide or the ebb tide, and the magnitude of the change. Specifically, for example, the value calculated by adding the difference between the tide level of the actual measurement time and the tide level one hour before, and the difference between the tide level of the actual measurement time and the tide level one hour after the actual tide It is data that is classified into types and is further digitized by a predetermined conversion table. For example, the types of low tide, high tide, high tide, and low tide are numerically classified (for example, low tide: minus 10, high tide: plus 10, etc.), and the corresponding tide state, that is, tide. It is quantified according to the movement and strength status data.

The topographical data is obtained by classifying the topographical features of the seabed at the point where the waves at the prediction target point break and classifying them into a predetermined pattern. More specifically, this topographical data has a great influence on the shape and size of the waves that are breaking waves, so the depth and slope angle of the offshore area and shallow shallow water on the slope should be Several patterns are provided for each item such as size and how to attach sand, and the pattern of the target point is classified for each item, and it is comprehensively calculated according to a predetermined numerical conversion table. It is the data evaluated by. For example, there are 3 patterns for the depth of the offshore and the angle of the slope, 3 patterns for the depth of the shallow water on the slope, 6 patterns for how the sand is attached, and 54 patterns obtained by multiplying these are the total patterns of the terrain data, and each of the 54 patterns is It is classified numerically (for example, 1 to
54) and 54 patterns, the numerical evaluation point of the topographical data is determined depending on which one is applied.

The tidal current data is data numerically obtained by classifying by a predetermined numerical conversion table whether or not the target point is easily influenced by the environmental tidal current such as the river mouth and the inland sea. For example, the power flow data can be obtained by classifying numerical values from 1 to 4 by dividing into 4 stages of “very susceptible”, “prone to impact”, “less affected” and “little impact”. Digitize. As a specific example, the vicinity of the estuary and the Seto Inland Sea are easily affected by tidal currents,
In this case, the impact figures are highly evaluated. Note that the configuration is not limited to the numerical classification methods 1 to 4 of the tidal current data, and may be a configuration using more detailed classification methods and specific numerical data regarding the tidal current data.

The weather chart data is data obtained by classifying, for each predetermined weather chart pattern, whether or not the influence on the wave is large by a predetermined numerical conversion table. For example, the weather map pattern is classified into 30 patterns, and for example, the evaluation numbers 1 to 30 are set according to the degree of influence on the waves, and the weather map data is represented by numerical values.

As shown in FIG. 5, the GPV data is data of wave height, wave direction, wind speed, wind direction, and cycle for each latitude and longitude, and data at the same time as the time to be predicted is extracted from the data of the GPVDB 23a. It is a thing.

As shown in FIG. 5, the basic data composed of the data on the above items is recorded so as to be identifiable by giving an ID number for each actual measurement date and actual measurement range.

Here, the actual measurement data (wave size data) in the basic data is not exactly the same time as the predicted time of the wave GPV data, and can be predicted by the wave GPV data at 0:00, 6:00, 12:00, and 18:00. It is associated with the closest time and is used by correcting the actual measurement time. In this case, the corrected date and time data and the corrected time difference data are also included and recorded as basic data. At the same time, based on the predicted interval of the wave GPV data of 6 hours, the measured data is recorded in association with the wave GPV data of 6 hours before and 12 hours before the measured time of the measured data. The reason is that, first of all, the wave GPV data is data at 6-hour intervals, and therefore a time difference from the measured data occurs. Secondly, since the wave GPV data is offshore data, when compared with the data near the coast of the actual measurement point (target point) at the same time, the spatial distance of 10 Km mesh unit data and the speed of the wave. There is a time difference due to. In order to eliminate this time difference, it is necessary to fix the time difference at 6 hours and obtain the position of the most highly correlated wave GPV data 6 hours ago or 12 hours ago. Therefore, as the basic data, the measured data (wave size value) associated with the wave GPV data is the data corrected to the time closest to the predicted time, and the time difference data by the correction and the measured time 6 hours before And 12 hours before the wave GPV data are related and included for recording.
It should be noted that the means for associating the data having the closest estimated times of the measured data and the wave GPV data and storing them in the basic DB 23b is not limited, and, for example, from the measured data at a certain measurement date and time, the wave GPV data, etc. Method to obtain highly correlated data based on time difference data obtained by calculating arrival time to the coast using wave velocity data obtained from wave height and period data, or wave velocity information obtained from actual measurement, etc. May be

Further, actual measurement data, tide level data, terrain data, tide state data, tidal current data, weather chart data, etc.
It may be observation data by visual observation or measurement data by a measuring device, and the acquisition source may be either a private institution or a public institution.

Then, from the basic data stored in the basic DB 23b as described above, a model formula for calculating the numerical data of the wave size is created. The method for creating it will be described below.

First, according to a predetermined operation by the operator, the control unit 11 of the main server 10 reads the model formula calculation program 16a from the storage unit 16, stores it in the RAM, and starts controlling each unit. Then, the control unit 11
Causes the display unit 12 to display a population extraction condition data input screen for inputting a condition for extracting a population for creating a model formula. Therefore, the operator uses the input unit 13 to conditionally input various information of the target point to be predicted. As specific condition input contents, for example, a condition that the actual measurement date and time is from July to September, the tide state value is -10 or less (low tide), and the predicted time is 18:00 is input.

Next, the control unit 11 of the main server 10
Performs a population extraction process of extracting a population corresponding to the above condition data from the basic DB 23b stored in the data storage server 20. It should be noted that a plurality of model formulas can be calculated by changing the condition data for extracting the population, and therefore, the model formula DB 16e having the higher accuracy may be stored. The constituent elements of the population can be appropriately increased or decreased by the operation of the operator, and are not limited to the above-described constituent elements. For example,
It may be configured to add salt concentration, water temperature data and the like to the configuration.

Next, the control unit 11 of the main server 10
Activates a multiple regression analysis program (not shown) to perform multiple regression analysis on the extracted population, calculate a model formula, and record and store it in the model formula DB 16e. The general formula of the model formula calculated here is, for example, wave size value = constant + tide level * coefficient + terrain evaluation value * coefficient + tide current evaluation * coefficient + tide state value * coefficient + 139342
The equation is * coefficient + 1393433 * coefficient. Here, "1390342" means longitude 139 degrees 0.
Min, wave height of wave GPV data at a position of latitude 34 degrees 2 minutes,
It means to multiply each coefficient of wind direction, wind speed, wave direction and period. This model formula naturally has different coefficients depending on the results of the multiple regression analysis, and the components of the model formula also differ. That is, components determined to be insignificant by a predetermined method of multiple regression analysis are omitted from the model formula by, for example, the stepwise method.

The actual measurement DB 23c is data of actual measurement for each actual measurement point (target point) unit near the coast provided as wave prediction information, which is included in the basic DB 23b, and includes an ID number for identifying the data, actual measurement date and time, actual measurement. Data such as target points (latitude, longitude), wave height, wave direction, cycle, wind speed, wind direction, topography, tidal current, tide level, and tide state are recorded and stored.
This data is the original data of the basic data and also includes the original data for extracting the wave condition information. The data included in this actual measurement DB 23c is
It may be numerical data or text data.

The Web server 30 is a device for providing the wave prediction information to the user terminals 3 ... And the HTML document D based on the command information requested from the user terminals 3.
This is a device that acquires necessary data from B, converts it into HTML, and transmits the HTML-converted data to the user terminal 3.

The Web server 30 internally has, for example, as shown in FIG. 6, a control unit 31, a communication unit 32, and a storage unit 33.
And so on. Since the respective functions are the same as those of the main server 10, detailed description will be omitted and only different points will be described.

The control unit 31 controls the URL from the user terminal 3.
In response to the request signal of, the CGI program is executed, the HTML document designated by the user is searched, and the HTML document is searched.
It controls the operation of transmitting a document to the user terminal 3 and the like.
The storage unit 33 is application software (not shown) corresponding to the process of providing the wave prediction information to the user terminal 3.
HTML document data DB 33 for providing wave information, etc.
a, member registration data (not shown), authentication data (not shown) and the like are stored. It should be noted that the form of providing wave information to the user terminal 3 is not limited to the one via HTML, and it is assumed to be in accordance with the type and specifications of the user terminal 3.

The GPV distribution server 2 is an existing server for distributing the wave GPV data announced by the Meteorological Agency.

The user terminal 3 is a general-purpose personal computer, a mobile communication terminal such as a mobile phone, PHS, or PDA, or a car navigation device configured to access the network 5 such as the Internet. As shown in FIG. 7, as a configuration required in the main-wave prediction information providing system 100, for example, the control unit 3
a, display unit 3b, input unit 3c, storage unit 3d, and communication unit 3
e.

The control unit 3a includes therein a control unit for controlling each unit,
It is provided with a CPU that performs data transfer, determination processing, and the like, a storage area that temporarily stores programs and data, and a RAM that forms a work area that is processed by an input instruction and input data. Then, the control unit 3a executes each control process according to various application programs of the storage unit 3d.

The display section 3b is composed of, for example, a CRT or LCD, and displays various display data and images input from the control section 3a. Specifically, for example, a display screen of wave prediction information transmitted from the wave prediction system 1 is displayed on the display unit 3b.

The input section 3c is provided with, for example, a ten-key pad, a keyboard, a pointing device, etc., and selects and specifies the selection information displayed on the screen of the display section 3b, or, for example, inputs authentication data and the like. Used to do.

Programs, data and the like are stored in advance in the storage unit 3d, and the storage unit 3d includes a recording medium readable by the control unit 3a such as a magnetic or optical recording medium or a semiconductor memory. It is a composition. This recording medium includes, for example, a portable medium such as a CD-ROM and a memory card, and a fixed medium such as a hard disk. Also,
The programs, data, and the like stored in the storage unit 3d may be partially or wholly received from another server from the communication unit 3e via a network such as WAN or LAN. It may be a storage unit of an external server built in.

The storage section 3d stores the system program of the present invention, various application software such as an internet browser (not shown), and the like.

The communication section 3e is composed of, for example, a modem, a terminal adapter, a router or the like, and controls for communication with an external device via a communication line such as a telephone line, an ISDN line or a leased line. .

The wave information measuring device 4 is a device for measuring actually measured value data for increasing the accuracy of the wave prediction information in the wave prediction information providing system 100 according to the present invention. More specifically, it is an existing device that includes a wave meter (not shown) and measures data such as wave height and wave motion. The actual measurement form will be described later.

Next, the operation of this embodiment will be described. The operation of this embodiment will be described assuming that the wave prediction information is information for surfers. As shown in FIG. 8, the overall operation of the wave prediction information providing system 100 of the present invention is as follows.
Based on the wave GPV data distributed from the distribution server 2, calculation and extraction processing of wave prediction information is executed (step S1). Next, a wave prediction information providing process of providing this wave prediction information to the user is executed (step S2). Next, based on the actual measurement data for the predicted wave prediction information, the original data for extracting the wave prediction information, the adjustment and correction of the calculation method, etc. are performed, and the feedback processing for extracting the more accurate wave prediction information is performed. It is executed (step S3). Next, unless the operation of the wave prediction information providing system 100 is terminated (step S4: No), each processing of the above steps S1 to S3 is repeatedly executed at an arbitrary frequency and at an interval according to the distribution of the wave GPV. It

Next, a series of operations of the wave prediction information extraction processing for calculating and extracting the wave prediction information in the wave prediction system 1 will be described with reference to the flowchart shown in FIG.

In the wave prediction system 1, the wave GPV data is acquired from the GPV distribution server 2 based on the operation by the operator or automatically (step S101). The wave GPV data acquired here is
It is stored in the GPVDB 23a of the data storage server 20.

Next, the control unit 11 of the main server 10 of the wave prediction system 1 causes the display unit 12 to display an input screen for inputting conditions for searching for the optimum model formula. Therefore, the operator uses the input unit 13 to conditionally input various information of the target point to be predicted (step S102). The specific condition input contents are data such as latitude and longitude of the target point to be predicted, and accordingly, the control unit 11 automatically acquires, for example, tide level data, wind speed data, etc. of the target position to be used as condition data. To do.

Next, the control unit 11 of the main server 10
Extracts a model formula that matches the condition data by searching the model formula DB 16e in the storage unit 16 (step S103).

Next, as a result of the search processing in step S103, the control unit 11 confirms whether or not there is a model expression that matches the input condition data (step S104), and if there is no model expression that meets the conditions (step S104). : No), the process returns to step S102, and if there is a model expression that matches the condition data (step S104: Yes), the process proceeds to step S105. In addition, when a plurality of relevant model expressions are extracted, the number of items of the condition data may be increased to narrow down.

Next, in step S105, the control section 11 causes the display section 12 to display the model formula confirmed in step S104.
Numerical data corresponding to the constituent elements are input to the model formula created by using the above model formula. Specifically, the input numerical data is, for example, the data included in the wave GPV data acquired in step S101.

Then, according to the input of the numerical data for the model formula, the control unit 11 of the main server 10 executes the calculation process of the model formula, calculates the numerical data of the wave size, and displays it on the display unit 12 (step S106).
The calculation process of the numerical data of the wave size in step S106 is not limited to the method performed each time, and may be a method of extracting the data calculated in advance.

Then, by a predetermined operation of the operator, the control unit 11 of the main server activates the wave condition extraction program 16b, and executes the acquisition process of the original data for extracting the wave condition according to the program. . Specifically, for example, the wind direction and wind speed data at the target point (land) and the wind direction and wind speed data of the wave GPV are included. Then, by performing numerical classification and numerical evaluation of the data in the above items by a predetermined method,
Define applicable wind impact patterns. (Step S10
7).

Next, first, text conversion processing of the numerical data of this wave size calculated in step S106, and wave prediction information text conversion for extracting wave condition information based on the wind influence pattern extracted in step S107. , Extraction processing is executed (step S10).
8). Specifically, the control unit 11 firstly performs step S10.
Numerical data of wave size calculated in 6 is used for text DB1
According to the text conversion program 16da of 6d, the text conversion is performed based on the conversion table 300 of the text conversion data 16db and the actually measured text data 16dc, such as "Koshi occasionally Mune". Then, the wave condition text data 1 associated with the wind influence pattern extracted in step S107
6dd is acquired from the text DB 16d.

Next, the control unit 11 of the main server 10
Displays wave size data as wave prediction information and wave condition data on the display unit 12, so that the operator confirms the wave prediction information (step S109).
Here, as the wave prediction information, for example, the predicted location, the predicted date and time, the numerical data of the wave size (6.6), the text data of the wave size (Knee to Momotama Set Kosi), the condition data of the wave (constant at Grassy Break condition. GOOD WAVE!), Weather forecast information, caution information, etc. are included. Note that the content of the wave prediction information is not limited to the above content, and may be, for example, a configuration including information based on the cycle data of the wave GPV. In detail, for example, in the case of wave prediction information that a wave of the size of "Katatama occasionally" is generated, the wave of "Occasional Atma" is calculated based on the period data of the wave GPV or the period data of an arbitrary maximum wave. Information is added about how often the occurrence occurs. As a result, more detailed wave information can be provided.

Then, the control unit 11 of the main server 10
Is the extraction processing of the wave prediction information by the operator (step S
It is determined whether or not the end signal of 1) is input (step S110), and when it is determined that the end signal is input (step S110: Yes), the extraction processing of the wave prediction information is ended and the end signal When it is determined that there is no input (step S110: No), the process proceeds to step S101. Incidentally, the above steps S101 to S110.
In the wave prediction information extraction processing in
Processing executed by the operator such as 0, for example, condition input processing in step S102, data input processing into the model formula in step S105, wave prediction information confirmation processing in step S109, and execution instructions in other processing. The operation may be programmed in a predetermined program, and all or part of the operation may be automatically executed by the control unit 11 of the main server 10. In this case, the labor cost can be reduced and the processing can be speeded up.

Next, the wave prediction information providing process for providing the user with the wave prediction information calculated by the wave prediction system 1 as described above will be described with reference to the flowchart shown in FIG. The method of providing this wave prediction information is
For example, any information provision method such as information provision via the Internet or the like, information provision to a specific terminal connected by a dedicated line, information provision via a television, radio or the like is included. Hereinafter, as an example of the method of providing the wave prediction information, an information providing method of providing the wave prediction information to the user terminal 3 that has registered as a member via the Internet will be described. The wave prediction information extracted in step S1 is assumed to be stored in the HTML document DB 33a of the Web server 30 by the main server 10.

First, by the operation of the operator of the user terminal 3, the user terminal 3 is connected to the Web server 30 via the network 5, such as the Internet and the intranet, and the request signal for the wave prediction information page is transmitted to the Web server 30. Yes (step S201).

Next, the Web that received the above request signal
The control unit 31 of the server 30 reads the authentication screen data from the HTML document DB 33a and transmits the same screen data to the user terminal 3 (step S202).

Next, the control unit 3a of the user terminal 3 which has received the screen data displays an authentication screen (not shown) (step S203). Therefore, the terminal operator uses the input unit 3c to input the authentication data such as the user's ID number and password set in advance as member registration, and the input data for the above authentication is input via the communication unit 3e. And transmits it to the Web server 30 (step S20).
4).

Next, the control unit 31 of the Web server 30
Is the input data for authentication transmitted from the user terminal 3,
It is received via the communication unit 32. Then, the control unit 31
An authentication process for determining whether or not the user is a registered member is executed by comparing it with the authentication data stored in the storage unit 33 (step S205). Then, when the authentication is successful (step S2).
If 05: Yes), the process proceeds to step S206, and if the authentication fails (step S205: No), the process returns to step S202.

In step S 206, the control unit 31 of the Web server 30 sends the wave prediction information search screen data to the user terminal 3. Next, the control unit 3 of the user terminal 3
The wave prediction information search screen is displayed on the display unit 3b by a (step S207). The wave prediction information search screen is a screen for searching the wave prediction information of the target point and the date and time desired by the user. Therefore, the user uses the input unit 3c to input points, date and time, which are search data, and transmits the points to the Web server 30 (step S20).
8). Next, the Web server 30 which has received the above-mentioned search data from the user terminal 3 has the HTML document DB 33a.
To obtain the wave prediction information corresponding to the search condition, create search result screen data, and send it to the user terminal 3 (step S209).

Then, the search result screen including the wave prediction information extracted in step S1 is displayed on the display unit 3b of the user terminal 3 (step S210), and the wave prediction information providing process is completed. . The wave prediction information displayed on the search result screen is not limited to the data of the character medium, and a wave simulation image or the like that matches the wave condition information may be displayed.

The wave prediction information providing process is not limited to the one-way information providing process of providing information from the wave prediction system 1 to the user terminal 3. For example, We
b The server 30 has a function of providing a bulletin board on HP,
It is also possible that the user terminal 3 provides actual information via the bulletin board or the like, or two-way information provision or information exchange between users is possible. Furthermore, in order to provide accurate information, the user terminal 3 transmits information about the size of the wave and the condition of the wave to the main server 10 via the Web server 30 and uses it for correction of the wave prediction information. Good. In this case, the data transmitted from the user terminal 3 is digitized by a predetermined method and reflected in the model formula of the wave prediction information. Then, for example, by adding points to the user who provided the information, or by incorporating a game element such as growing a character set by the user in advance, the information can be easily collected. In that case, by checking the predetermined reference data and the like, whether the numerical value of the data provided from the user terminal 3 is far from the predetermined numerical data, that is, whether the user has input random data. It will be decided. By executing the method as described above, it is possible to update the prediction information to be accurate at any time, and it can be expected that the number of users will increase.

Also, the above-mentioned wave prediction information providing process (S3)
In the wave prediction information, the wave prediction information is stored in the storage unit 3 of the Web server 30.
3 has been described, the web server 30 sends the request signal main server 10 each time based on the request signal of the wave prediction information from the user terminal 3.
And the wave prediction information may be transmitted to the user terminal 3 under the control of the control unit 11 of the main server 10.

Next, the feedback processing (step S3) for improving the accuracy of the model formula for extracting the wave prediction information predicted and provided with information as described above will be described below. First, the size of the wave provided as the wave prediction information, the condition of the wave, or the wind speed, wind direction, period, tide level, etc., which are components of the prediction information, are measured at the predicted time. Then, the difference between the measured data and the prediction data by the wave prediction system 1 or the wave GPV data is calculated. Then, based on the difference, the coefficient in the model formula, the contents of the constituent elements, and the like are reviewed to correct the model formula with higher accuracy. In addition to the data such as wave height, wave direction, cycle, etc. of wave information, which is announced hourly by public organizations such as the Japan Meteorological Agency, wind speed, wind direction, etc. It is assumed that it is the measurement data of the anemometer installed, etc., or the observation data by visual observation. Alternatively, the method via the information provision from the user terminal 3 described above in step S2 may be used.

In particular, as a method of acquiring the actual measurement data of the wave size, for example, there is a method of using a buoy provided on the coast. Since this buoy is provided in large numbers near the coast, it is possible to install the wave information measuring device 4 for measuring the wave height and the tide level on this buoy and measure the wave information measuring device 4 with this. In this measurement method, the wave information measuring device 4 is provided on a buoy fixing part on the seabed so as to be fixed to the seabed. For example, the wave information measuring device 4 is provided by a submarine cable or a wireless device provided on the buoy. Server 1
Connect with 0. Here, it is assumed that the main server 10 is provided with a converter 17 that AD-converts the pulse signal of the wave information measuring device 4. Detailed measurement method, for example,
Attach a wave gauge to the buoy or the rope that connects the buoy,
The up and down movement of the wave is measured by the wave meter, and the measurement data is transmitted to the main server 10 via a dedicated line, a radio or the like. Then, the converter 17 of the main server 10 amplifies the received measurement signal and the like with an amplifier circuit, performs digital conversion processing with the AD conversion circuit, and outputs the digital signal to the control unit 11. Then, the control unit 11 calculates a tide level and a wave height by performing a predetermined calculation based on the digital data.
The measurement data measured by the wave meter of the wave information measuring device 4 may be a digital signal, and in this case, the main server 10 does not need to include the converter 17. According to this method, accurate measured data can be acquired, and this measured data is used as the measured DB 23c and the basic DB 23.
The data can be stored in b as needed, and the coefficient of the model formula and the like can be adjusted based on the measured data. Therefore, it is possible to calculate a more accurate model formula. The measurement method is not limited to the method including all the constituent elements of the wave information measuring device 4 described above. As another measurement method, the wave information measuring device 4 includes a transducer (not shown) that transmits and receives ultrasonic waves and a transducer (not shown) that generates ultrasonic waves, and the transducer of the transducer is provided. The ultrasonic pulse signal generated by is emitted from the transducer in the vertical direction of the sea surface, the ultrasonic pulse signal signal is reflected on the sea surface, the reflected pulse signal is received by the transducer, and Alternatively, the wave information may be measured by transmitting the wave information to the main server 10 on land by a predetermined method. Alternatively, the wave information measuring device 4 is provided with an ultrasonic wave transmitter provided on the seabed and an ultrasonic wave receiver on the sea surface side such as a buoy near the sea surface or a rope connecting the buoys. The configuration may be such that a pulse emitted through the child is received by a receiver and the ultrasonic pulse signal is transmitted to the main server 10. Furthermore, the wave information measuring device 4
Is equipped with an image acquisition means for acquiring wave image information such as a CCD camera, and the main server 10 analyzes wave information such as wave height based on the wave image data acquired by this image acquisition means. It may be configured to be used as actual measurement data. As a method of analyzing wave information from wave image data, for example, a method of judging from wave color may be used. More specifically, the wave height near the coast (especially the height of breaking waves)
When the image is measured by an image acquisition means fixed on land such as a surveillance camera, the reflection of light reflected on the wavefront is used to analyze the image based on the color depth of the sea. At that time, in order to derive an accurate numerical value, it becomes a problem to measure the distance between the point where the image processing means is fixed and the actual wave breaking position at the observation target point. This is because the size of the wave and the tidal phenomenon change the surrounding environment such as the position where the wave breaks. Therefore, as an image analysis method, for example, the boundary line of the discontinuous portion related to the shade and color of the image is extracted (edge / contour / line component extraction), and the object to be measured is extracted from the image. Then, in the present invention, the accurate distance between the land-based image acquisition means and the observation target point is predicted from the highly accurate wave size value that can be predicted, the tidal condition, the effect of the wave due to the wind, and the like, and the image analysis device is used. Is the main server 1
By reflecting the above data value in 0, accurate wave height analysis becomes possible. Then, when predicting the wave prediction information (wave height size value of breaking waves), the position at which the predicted wave height breaks, for example, tide level information for determining the water depth, tide state information, topographic information, wind information Data values such as will be used when calculating the distance prediction. Therefore, the user can see the moving images and images taken in real time,
It is difficult to accurately grasp the size value of the wave, but by adding the wave height (mainly the size of the breaking wave) obtained above to the image as text (may be voice, image, etc.) Can be provided,
It is convenient.

Next, the actual results of the wave prediction data calculated by the wave prediction information providing system 100 executed as described above will be described below with reference to FIGS. 11 and 12. FIG. 11 shows the wave prediction data 11A calculated by the wave prediction system 1, and the actual wave actual measurement data 11B at the prediction point and the prediction time which are the targets of the prediction.
It is a table comparing the latest point and the same time of the same prediction point, or the wave GPV data having the highest correlation.

More specifically, FIG. 11 shows "each data from January 1 to January 7, 2002 on Kugenuma coast".
Therefore, the actual measurement data 11B includes the observation time data B
1. Numerical data B2 of wave size and text data B3 of wave size are included. In addition, the wave GPV data 11C is numerical data of wave size (wave height), and more specifically, it is a predicted value at a point closest to Kugenuma Beach, which is a target point for prediction, at 35 ° 12 'north latitude and 139 ° 24' east longitude. . Then, as the wave prediction data 11A for the Kugenuma coast calculated by the wave prediction system, data on the items A1 to A7 is included. A1 extracts the wave height numerical data of the past wave GPV from the basic DB 23b of the wave prediction system 1 based on the wave size (wave height) numerical data of the wave GPV data, and corresponds to the predicted date and time of the wave GPV data. Numerical data of wave size calculated based on previously measured wave size data that does not take into account, for example, topographic data, tide level at the predicted date and time, tide condition, wind data, etc. It is data calculated based on the formula. A2 is predicted wave size numerical data calculated by considering the arrival speed of waves and the time difference in distance between the wave GPV data and the coast in addition to the data of A1. A3 is wave size numerical data calculated by considering the topographical data of the predicted point in the calculated model formula of the data of A1, A4 is tide level data instead of topographical data, and A5 is tide condition. Numerical data of wave size calculated in consideration of the data. And
A6 is numerical data of the size of the wave calculated in step S107 in consideration of all the items A2 to A5 and the other items described above. A7 is wave size text data obtained by text-converting the numerical data of A6 based on the predicted wind direction data, wind speed data acquired in step S108, and the storage data of the text DB 16d described above. In addition, the numerical data of the wave size in FIG.
The unit is 10 cm.

Further, FIG. 12A is a line graph showing the numerical data regarding the wave sizes of 11C, B1 and A1 to A6 in FIG. 11 by a line graph for each date. FIG. 12B shows the wave GP from FIG.
It is the figure expanded except V data 11C. As is clear from FIG. 11 and FIG. 12, the wave GPV data 11C
Is a value far from the actually measured wave size data B3. On the other hand, the wave prediction system 1 of the present invention
The data of A1 to A6 calculated using is an approximate value to the numerical data of the actual measurement, and in particular, considering the data related to various surrounding environments of the prediction target point like A6, it is almost the same as the actual measurement data B3. It becomes clear that this is accurate forecast data. Further, it is clear that the data of A6 and the predicted text information of A7, which is made into text based on the wind direction and wind speed data at the predicted date and time, are very similar to the actually measured text data. Therefore, in addition to the numerical data of the wave size, it is apparent that the user can be provided with accurate wave prediction information regarding the variation and the period of the wave size.

As described above, according to the present embodiment, the wave G
Comprehensively considering PV data, past measured data, and comprehensive environmental information such as topographical data near the coast,
Since the wave prediction information near the coast is extracted, it is possible to calculate more accurate wave prediction information near the coast as compared to the offshore wave information GPV. In addition, when it is provided to the user, it is converted into an expression and text data according to the usage method of the user, so that it is easier to understand than the numerical data, and the number of users can be expected to increase. In particular, it is very easy to understand because not only the numerical value of the wave size is provided, but also detailed information about the visual impression of the wave is provided in a content very close to the actual observation data. Also, by the feedback processing of the wave prediction information, it is possible to increase the number of classification patterns by updating the model formula created once and the measured data at any time and adding it, and the model formula is accumulated at any time. The higher the number of layers, the more accurate the wave prediction information can be calculated and extracted.

Also, stored in the basic DB 23b,
The actual measurement data and the wave GPV data are temporally and distancewise so that the data having the highest correlation are recorded in association with each other in consideration of the velocity of the wave and the time difference in distance between the coast and the offshore. Since it is corrected to, it is possible to provide more accurate wave information near the coast when calculating wave prediction information based on wave GPV data.

The above embodiment is merely an example and can be changed as appropriate. For example, it is assumed that the users to whom the wave prediction information is provided are not limited to surf enthusiasts, but are users who are engaged in sports or occupations that are affected by waves near the coast. Specifically, marine sports in general, fishing, coastal construction, coastal fishery, etc. are considered, depending on the target user,
The text content provided as wave prediction information can be converted and provided in different formats. For example, in the case of wave prediction information for fishing, it provides the optimum fishing point, fish that is likely to be caught, time zone when it is likely to be caught, index of ease of fishing, attention information of storm surge, and the like.

The constituent elements of the model expression are not limited to those described above, and may be any elements that affect the waves. Conversely, the constituent elements of the model expression do not include all of the above constituent elements. The method of calculating the model formula may be used.

The extraction processing and the providing processing of the wave prediction information are performed at least in accordance with the date and time of distribution of the wave GPV data and the number of times, and are appropriately executed according to the update by the actual measurement data. I shall.

The internal structure of the wave prediction system 1 is not limited to the above-mentioned structure, and may be any structure as long as the extraction process of the wave prediction information according to the present invention is possible. . For example, all of them may be installed in one device, or may be distributed over the network 5, or may be independent of the Web server 30.

[0113]

According to the present invention, the wave prediction model formula creating means of the wave predicting apparatus produces the actual measurement result of the wave information at the target point and the wave GPV data related to the actual measurement result.
Based on the wave prediction basic data including at least one of the terrain or the tide at the target point, a wave prediction model formula for predicting wave information by multiple regression analysis is created, and by the wave prediction result calculation means, The wave GPV data acquired by the acquisition means is substituted into the wave prediction model formula to calculate the prediction result of the wave information on the coast of the target point, and the prediction result of the wave information is transmitted to the terminal device by the transmission means, Since the output unit of the terminal device outputs the prediction result of the wave information transmitted from the wave prediction device, the wave GP is provided to the user who is the operator of the terminal device.
As compared with the V data, it is possible to easily provide accurate prediction information on the coast of the target point.

[Brief description of drawings]

FIG. 1 is a wave prediction information providing system 100 according to the present invention.
3 is a block diagram showing the overall configuration of FIG.

FIG. 2 is a block diagram showing an internal configuration of a main server 10 of the wave prediction system 1 (wave prediction device) of FIG.

FIG. 3 is a diagram showing an example of a text conversion table of a text DB 16d shown in FIG.

4 is a block diagram showing an internal configuration of a data storage server 20 of FIG.

5 is a diagram showing an example of a data table of a basic DB 23b of FIG.

6 is a block diagram showing an internal configuration of the Web server 30 of FIG. 1. FIG.

7 is a block diagram showing an internal configuration of a user terminal 3 of FIG.

FIG. 8 is a flowchart for explaining the overall operation of the wave prediction information providing system of the present invention.

9 is a flowchart for explaining the operation of the wave prediction information extraction processing of FIG.

10 is a flowchart for explaining the operation of the wave prediction information providing process of FIG.

FIG. 11 is an explanatory diagram showing a table for comparing wave prediction information by the wave prediction system 1, wave GPV data, and actual measurement data.

FIG. 12 is a line graph of the numerical data of FIG. 11.

[Explanation of symbols]

1 wave prediction system (wave prediction device) 2 GPV distribution server 3 user terminal (terminal device) 3a control unit 3b display unit (output means, second output means) 4 wave information measurement device 5 network (communication line network) 10 main Server 11 Control Unit (Wave Prediction Model Formula Creation Means, Acquisition Means, Wave Prediction Result Calculation Means, Output Means, Wave Condition Prediction Information Extraction Means, Text Conversion Means, Wave Information Receiving Means) 12 Display Unit (Output Means, Second Means) Output unit) 14 Output unit (output unit, second output unit) 16 Storage unit 16a Model formula calculation program 16b Wave condition extraction program (Wave condition prediction information storage unit) 16d Text DB (Wave condition prediction information storage unit) 20 data Storage server (acquisition means, storage means) 23a GPVDB (wave GPV data storage means) 23b Basic DB 23c Found DB (wave measured result storing means) 30 Web server (transmission means, second transmission means) 32 communication unit (transmitting means, second transmission means) 100 waves prediction information provision system

Claims (8)

[Claims] 1. A wave predicting device for predicting wave information of a predetermined item on a shore of a target point, the actual measurement result of the wave information of the target point, the wave GPV data related to the actual measurement result, and the target. Wave prediction model formula creating means for creating a wave prediction model formula for predicting the wave information by multiple regression analysis based on the wave prediction basic data including the data on the landform at the point, and the predetermined wave GPV data. Substituting the acquisition means for acquiring and the wave GPV data acquired by the acquisition means into the wave prediction model formula created by the wave prediction model formula creation means to obtain the prediction result of the wave information on the coast of the target point. A wave characterized by comprising: a wave prediction result calculation means for calculating; and an output means for outputting a prediction result of the wave information calculated by the wave prediction side result calculation means. Measuring apparatus. 2. A wave predicting device for predicting wave information of a predetermined item on a shore of a target point, the measurement result of the wave information of the target point, wave GPV data related to the measurement result, and the target. Based on the wave prediction basic data including the data on the tide at the point,
Wave prediction model formula creating means for creating a wave prediction model formula for predicting the wave information by multiple regression analysis; acquisition means for acquiring predetermined wave GPV data; and wave GPV data acquired by the acquiring means. , A wave prediction result calculation unit that calculates a prediction result of wave information on the coast of the target point by substituting it into the wave prediction model formula created by the wave prediction model formula creation unit; An output unit that outputs a prediction result of the generated wave information; 3. The wave prediction device according to claim 2, wherein the tide-related data includes at least one of tide level data, tidal current data, and tide state data at a target point. . 4. The wave prediction device according to claim 1, wherein the prediction result of the wave information is numerical data related to the size of the wave, and the numerical data related to the size of the wave is A wave predicting device comprising a text converting means for converting into text data regarding the size of the wave. 5. The wave prediction device according to claim 1, further comprising: wave condition prediction information storage means for storing wave condition prediction information regarding a wave condition associated with the influence of wind; and a target point. Wave condition prediction information extraction means for extracting wave condition prediction information related to the wave condition due to the influence of the wind from the wave condition prediction information storage means from the data related to the wind and the data related to the wind of the GPV data, and the wave condition prediction. A second output means for outputting the wave condition prediction information extracted by the information extraction means, and the wave prediction device. 6. A wave prediction information providing system in which a wave prediction device for predicting wave information of a predetermined item on a shore of a target point and a terminal device are connected via a communication line. Is based on the wave prediction basic data including the measurement result of the wave information at the target point, the wave GPV data related to the measurement result, and the data on at least one of the topography and the tide at the target point. A wave prediction model formula creating means for creating a wave prediction model formula for predicting the wave information by regression analysis; an acquiring means for acquiring predetermined wave GPV data; and a wave GPV data acquired by the acquiring means, Wave prediction result calculation for substituting into the wave prediction model formula created by the wave prediction model formula creation means to calculate the prediction result of the wave information on the coast of the target point And a transmitting unit that transmits the prediction result of the wave information calculated by the wave prediction result calculating unit to the terminal device, the terminal device including the prediction result of the wave information transmitted by the transmitting unit. An output device for outputting, and a wave prediction information providing system, comprising: 7. The wave prediction information providing system according to claim 6, wherein a wave information measuring device for actually measuring the wave information at a target point is connected to the wave predicting device via a communication line, and the wave predicting device is A wave information receiving unit that receives a measurement result of the wave information by the wave information measuring device; a wave measurement result storage unit that stores a measurement result of the wave information received by the wave information receiving unit; A wave prediction information providing system, comprising: wave GPV data storage means for storing related wave GPV data. 8. The wave prediction information providing system according to claim 6 or 7, wherein the wave prediction device stores wave condition prediction information regarding wave condition prediction information regarding a condition of a wave associated with an influence of wind. Wave condition prediction information extraction for extracting the wave condition prediction information concerning the wave condition due to the influence of the wind from the wave condition prediction information storage means from the means, the data on the wind at the target point, and the wind data of the wave GPV data. Means, and second transmitting means for transmitting the wave condition prediction information extracted by the wave condition prediction information extracting means to the terminal device, wherein the terminal device is transmitted by the second transmitting means. Second output means for outputting wave condition prediction information is provided. A wave prediction information providing system characterized in that