CN117669126B - Large-scale buoy networking method and system for marine environment research - Google Patents
Large-scale buoy networking method and system for marine environment research Download PDFInfo
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Abstract
The invention discloses a large-scale buoy networking method and system for marine environment research, wherein the method comprises the following steps: dividing an ocean area needing buoy networking into a plurality of subareas, and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea; setting a large-scale buoy networking model, and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density; and completing large-scale buoy networking through the number of buoys in the buoy network.
Description
Technical Field
The invention belongs to the technical field of large-scale buoy networking, and particularly relates to a large-scale buoy networking method and system for marine environment research.
Background
Buoy networking is an important method for marine environmental research that can help scientists monitor various physical, chemical and biological processes in the ocean. At present, the buoy networking generally needs to be carried out through the following steps:
buoy selection and design: the type of buoy selected for use in the marine environment may include floating buoys, submerged buoys, surface drifting buoys, etc. The buoy should be durable, adaptable and versatile to operate under different conditions.
Dividing the area: the investigation region is divided into a plurality of sub-regions according to the investigation objective and the marine process of interest. Each sub-area is provided with a group of buoys to form a buoy network.
Buoy sensor: various sensors are installed on each buoy to measure ocean parameters such as temperature, salinity, flow rate, plankton concentration, etc. These sensors will collect data in real time and transmit it to a central data processing unit.
Communication system: each buoy should be equipped with communication equipment, such as satellite communication or a wireless network connection, to enable data transmission between buoys and communication with ground stations.
Data collection and transmission: the buoy transmits the collected data to a central data processing unit. This may be accomplished through a communication link between buoys, or through a communication link with a ground station.
However, in the prior art, there is no technical solution that can combine multiple parameters to provide a solution for buoy networking.
Disclosure of Invention
In order to solve the technical problems, the invention provides a large-scale buoy networking method for marine environment research, which comprises the following steps:
Dividing an ocean area needing buoy networking into a plurality of subareas, and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
setting a large-scale buoy networking model, and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
And completing large-scale buoy networking through the number of buoys in the buoy network.
Further, the large-scale buoy networking model includes:
，
where N is the number of buoys in the buoy network, N is the number of subregions, For/>The area of the sub-region is such that,For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>For/>Rate of change of ocean current velocity in sub-region,/>Is a function of the influence of variations in ocean temperature, salinity and ocean current velocity on buoy density.
Further, the influence function of the changes of ocean temperature, salinity and ocean current velocity on the density of the buoyThe method comprises the following steps:
，
Wherein, Is an overall adjustment factor,/>Is ocean temperature adjustment factor,/>For the ocean current speed adjustment factor,/>Index adjustment factor sum for salinity/>Is an exponential adjustment factor for ocean temperature.
Further, the influence function of the changes of ocean temperature, salinity and ocean current velocity on the density of the buoyThe method comprises the following steps:
，
Wherein, For the first adjustment factor,/>Is a second adjustment factor.
Further, a set of buoys is deployed for each of the sub-regions.
Further, the data collected by each buoy is received by a central data processing unit.
The invention also provides a large-scale buoy networking system for marine environment research, which comprises:
The data acquisition module is used for dividing the ocean area needing buoy networking into a plurality of subareas and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
The model setting module is used for setting a large-scale buoy networking model and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
And the networking module is used for completing large-scale buoy networking according to the number of buoys in the buoy network.
Further, the large-scale buoy networking model includes:
，
where N is the number of buoys in the buoy network, N is the number of subregions, For/>The area of the sub-region is such that,For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>For/>Rate of change of ocean current velocity in sub-region,/>Is a function of the influence of variations in ocean temperature, salinity and ocean current velocity on buoy density.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
The invention divides an ocean area needing buoy networking into a plurality of subareas, and acquires area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea; setting a large-scale buoy networking model, and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density; and completing large-scale buoy networking through the number of buoys in the buoy network. According to the technical scheme, the number and the scheme of the buoy networking can be automatically given according to a plurality of parameters.
Drawings
FIG. 1 is a flow chart of embodiment 1 of the present invention;
FIG. 2 is a block diagram of the system of embodiment 2 of the present invention;
fig. 3 is an overall flowchart of embodiment 1 of the present invention.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
The method provided by the invention can be implemented in a terminal environment, wherein the terminal can comprise one or more of the following components: processor, storage medium, and display screen. Wherein the storage medium has stored therein at least one instruction that is loaded and executed by the processor to implement the method described in the embodiments below.
The processor may include one or more processing cores. The processor connects various parts within the overall terminal using various interfaces and lines, performs various functions of the terminal and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the storage medium, and invoking data stored in the storage medium.
The storage medium may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (ROM). The storage medium may be used to store instructions, programs, code sets, or instructions.
The display screen is used for displaying a user interface of each application program.
All subscripts in the formula of the invention are only used for distinguishing parameters and have no practical meaning.
In addition, it will be appreciated by those skilled in the art that the structure of the terminal described above is not limiting and that the terminal may include more or fewer components, or may combine certain components, or a different arrangement of components. For example, the terminal further includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, a power supply, and the like, which are not described herein.
Example 1
As shown in fig. 3, the method of the present invention comprises the steps of:
1. Buoy selection and design: the type of buoy selected for use in the marine environment may include floating buoys, submerged buoys, surface drifting buoys, etc. The buoy should be durable, adaptable and versatile to operate under different conditions.
2. Dividing the area: the investigation region is divided into a plurality of sub-regions according to the investigation objective and the marine process of interest. Each sub-area is provided with a group of buoys to form a buoy network.
3. Setting a buoy sensor: various sensors are installed on each buoy to measure ocean parameters such as temperature, salinity, flow rate, plankton concentration, etc. These sensors will collect data in real time and transmit it to a central data processing unit.
4. Setting a communication system: each buoy should be equipped with communication equipment, such as satellite communication or a wireless network connection, to enable data transmission between buoys and communication with ground stations.
5. Data collection and transmission: the buoy transmits the collected data to a central data processing unit. This may be accomplished through a communication link between buoys, or through a communication link with a ground station.
6. Data processing and analysis: the central data processing unit receives data from all buoys and processes and analyzes the data in real time. Scientists can monitor changes in the marine environment, study ocean currents, ocean temperatures, marine ecosystems, and the like.
7. Real-time feedback and adjustment: according to the data analysis result, the deployment position of the buoy can be adjusted in real time so as to optimize the data acquisition strategy and the research direction.
8. Data sharing and propagation: the collected data can be shared with the scientific community and the public through scientific research papers, databases, online platforms and other approaches, so that marine environment research and protection are promoted.
Specifically, as shown in fig. 1, an embodiment of the present invention provides a large-scale buoy networking method for marine environmental research, including:
step 101, dividing a marine area needing buoy networking into a plurality of subareas, and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
Step 102, setting a large-scale buoy networking model, and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
specifically, the large-scale buoy networking model includes:
，
where N is the number of buoys in the buoy network, N is the number of subregions, For/>The area of the sub-region is such that,For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>Is the firstRate of change of ocean current velocity in sub-region,/>Is a function of the influence of variations in ocean temperature, salinity and ocean current velocity on buoy density.
Influence function of specific sea temperature, salinity and ocean current velocity changes on buoy densityThe method comprises the following steps:
，
Wherein, Is an overall adjustment factor,/>Is ocean temperature adjustment factor,/>For the current velocity adjustment factor to be used,Index adjustment factor sum for salinity/>An index adjustment factor for ocean temperature, influencing the function/>Nonlinear functions have been introduced to take into account the nonlinear effects of ocean temperature, salinity and ocean current velocity in order to more accurately describe the effects of these ocean environmental factors on buoy density. The technical effects and roles of this formula are as follows:
modeling of nonlinear effects: by introducing a nonlinear function, the formula can better capture the nonlinear effects of marine environmental factors. This is important for the complex relationships that exist in practice, as changes in temperature, salinity and ocean current velocity may not linearly affect buoy density.
Weighing the importance of each factor: adjustment factor、/>、/>、/>、/>Allowing the user to customize the function to reflect the relative importance of the marine environmental factors, as the case may be. Thus, the user can determine the weight of each factor on the density of the buoy according to the project requirement, so that the model is more suitable for different situations.
Integrating a plurality of environmental factors: the function integrates a plurality of environmental factors such as ocean temperature, salinity, ocean current velocity and the like into one function so as to more comprehensively evaluate the buoy deployment density.
Scientific support decision: the function can be used as a decision support tool to help a decision maker optimize the design and deployment of the buoy network in the marine environmental research project. By taking into account a number of environmental factors, a decision maker may more scientifically formulate a decision strategy to meet a particular goal of research, monitoring, or management.
More accurate model: compared with a simple linear function, the function can reflect complex interaction and nonlinear relation in a real marine environment more accurately, so that accuracy and reliability of buoy network deployment decisions are improved.
In particular, the influence function of the sea temperature, salinity and ocean current velocity changes on the buoy density in the inventionIt can also be:
，
Wherein, For the first adjustment factor,/>Is a second adjustment factor.
And 103, completing large-scale buoy networking according to the number of buoys in the buoy network.
Example 2
The system in this embodiment has the following functions:
1. Buoy selection and design: the type of buoy selected for use in the marine environment may include floating buoys, submerged buoys, surface drifting buoys, etc. The buoy should be durable, adaptable and versatile to operate under different conditions.
2. Dividing the area: the investigation region is divided into a plurality of sub-regions according to the investigation objective and the marine process of interest. Each sub-area is provided with a group of buoys to form a buoy network.
3. Setting a buoy sensor: various sensors are installed on each buoy to measure ocean parameters such as temperature, salinity, flow rate, plankton concentration, etc. These sensors will collect data in real time and transmit it to a central data processing unit.
4. Setting a communication system: each buoy should be equipped with communication equipment, such as satellite communication or a wireless network connection, to enable data transmission between buoys and communication with ground stations.
5. Data collection and transmission: the buoy transmits the collected data to a central data processing unit. This may be accomplished through a communication link between buoys, or through a communication link with a ground station.
6. Data processing and analysis: the central data processing unit receives data from all buoys and processes and analyzes the data in real time. Scientists can monitor changes in the marine environment, study ocean currents, ocean temperatures, marine ecosystems, and the like.
7. Real-time feedback and adjustment: according to the data analysis result, the deployment position of the buoy can be adjusted in real time so as to optimize the data acquisition strategy and the research direction.
8. Data sharing and propagation: the collected data can be shared with the scientific community and the public through scientific research papers, databases, online platforms and other approaches, so that marine environment research and protection are promoted.
Specifically, as shown in fig. 2, the embodiment of the present invention further provides a large-scale buoy networking system for marine environment research, including:
The data acquisition module is used for dividing the ocean area needing buoy networking into a plurality of subareas and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
The model setting module is used for setting a large-scale buoy networking model and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
specifically, the large-scale buoy networking model includes:
，
where N is the number of buoys in the buoy network, N is the number of subregions, For/>The area of the sub-region is such that,For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>For/>Rate of change of ocean current velocity in sub-region,/>Is a function of the influence of variations in ocean temperature, salinity and ocean current velocity on buoy density.
Influence function of specific sea temperature, salinity and ocean current velocity changes on buoy densityThe method comprises the following steps:
，
Wherein, Is an overall adjustment factor,/>Is ocean temperature adjustment factor,/>For the ocean current speed adjustment factor,/>Index adjustment factor sum for salinity/>An index adjustment factor for ocean temperature, influencing the function/>Nonlinear functions are incorporated to take into account the nonlinear effects of ocean temperature, salinity and ocean current velocity in order to more accurately describe the effects of these ocean environmental factors on buoy density. The technical effects and roles of this formula are as follows:
modeling of nonlinear effects: by introducing a nonlinear function, the formula can better capture the nonlinear effects of marine environmental factors. This is important for the complex relationships that exist in practice, as changes in temperature, salinity and ocean current velocity may not linearly affect buoy density.
Weighing the importance of each factor: adjustment factor、/>、/>、/>、/>Allowing the user to customize the function to reflect the relative importance of the marine environmental factors, as the case may be. Thus, the user can determine the weight of each factor on the density of the buoy according to the project requirement, so that the model is more suitable for different situations.
Integrating a plurality of environmental factors: the function integrates a plurality of environmental factors such as ocean temperature, salinity, ocean current velocity and the like into one function so as to more comprehensively evaluate the buoy deployment density.
Scientific support decision: the function can be used as a decision support tool to help a decision maker optimize the design and deployment of the buoy network in the marine environmental research project. By taking into account a number of environmental factors, a decision maker may more scientifically formulate a decision strategy to meet a particular goal of research, monitoring, or management.
More accurate model: compared with a simple linear function, the function can reflect complex interaction and nonlinear relation in a real marine environment more accurately, so that accuracy and reliability of buoy network deployment decisions are improved.
In particular, the influence function of the sea temperature, salinity and ocean current velocity changes on the buoy density in the inventionIt can also be:
，
Wherein, For the first adjustment factor,/>Is a second adjustment factor.
And the networking module is used for completing large-scale buoy networking according to the number of buoys in the buoy network.
Example 3
The embodiment of the invention also provides a storage medium which stores a plurality of instructions for realizing the large-scale buoy networking method for marine environment research.
Alternatively, in this embodiment, the storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.
Alternatively, in the present embodiment, the storage medium is configured to store program code for performing the steps of: the method comprises the following steps:
1. Buoy selection and design: the type of buoy selected for use in the marine environment may include floating buoys, submerged buoys, surface drifting buoys, etc. The buoy should be durable, adaptable and versatile to operate under different conditions.
2. Dividing the area: the investigation region is divided into a plurality of sub-regions according to the investigation objective and the marine process of interest. Each sub-area is provided with a group of buoys to form a buoy network.
3. Setting a buoy sensor: various sensors are installed on each buoy to measure ocean parameters such as temperature, salinity, flow rate, plankton concentration, etc. These sensors will collect data in real time and transmit it to a central data processing unit.
4. Setting a communication system: each buoy should be equipped with communication equipment, such as satellite communication or a wireless network connection, to enable data transmission between buoys and communication with ground stations.
5. Data collection and transmission: the buoy transmits the collected data to a central data processing unit. This may be accomplished through a communication link between buoys, or through a communication link with a ground station.
6. Data processing and analysis: the central data processing unit receives data from all buoys and processes and analyzes the data in real time. Scientists can monitor changes in the marine environment, study ocean currents, ocean temperatures, marine ecosystems, and the like.
7. Real-time feedback and adjustment: according to the data analysis result, the deployment position of the buoy can be adjusted in real time so as to optimize the data acquisition strategy and the research direction.
8. Data sharing and propagation: the collected data can be shared with the scientific community and the public through scientific research papers, databases, online platforms and other approaches, so that marine environment research and protection are promoted.
Specifically, as shown in fig. 1, an embodiment of the present invention provides a large-scale buoy networking method for marine environmental research, including:
step 101, dividing a marine area needing buoy networking into a plurality of subareas, and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
Step 102, setting a large-scale buoy networking model, and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
specifically, the large-scale buoy networking model includes:
，
where N is the number of buoys in the buoy network, N is the number of subregions, For/>The area of the sub-region is such that,For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>For/>Rate of change of ocean current velocity in sub-region,/>Is a function of the influence of variations in ocean temperature, salinity and ocean current velocity on buoy density.
Influence function of specific sea temperature, salinity and ocean current velocity changes on buoy densityThe method comprises the following steps:
，
Wherein, Is an overall adjustment factor,/>Is ocean temperature adjustment factor,/>For the ocean current speed adjustment factor,/>Index adjustment factor sum for salinity/>An index adjustment factor for ocean temperature, influencing the function/>Nonlinear functions have been introduced to take into account the nonlinear effects of ocean temperature, salinity and ocean current velocity in order to more accurately describe the effects of these ocean environmental factors on buoy density. The technical effects and roles of this formula are as follows:
modeling of nonlinear effects: by introducing a nonlinear function, the formula can better capture the nonlinear effects of marine environmental factors. This is important for the complex relationships that exist in practice, as changes in temperature, salinity and ocean current velocity may not linearly affect buoy density.
Weighing the importance of each factor: adjustment factor、/>、/>、/>、/>Allowing the user to customize the function to reflect the relative importance of the marine environmental factors, as the case may be. Thus, the user can determine the weight of each factor on the density of the buoy according to the project requirement, so that the model is more suitable for different situations.
Integrating a plurality of environmental factors: the function integrates a plurality of environmental factors such as ocean temperature, salinity, ocean current velocity and the like into one function so as to more comprehensively evaluate the buoy deployment density.
Scientific support decision: the function can be used as a decision support tool to help a decision maker optimize the design and deployment of the buoy network in the marine environmental research project. By taking into account a number of environmental factors, a decision maker may more scientifically formulate a decision strategy to meet a particular goal of research, monitoring, or management.
More accurate model: compared with a simple linear function, the function can reflect complex interaction and nonlinear relation in a real marine environment more accurately, so that accuracy and reliability of buoy network deployment decisions are improved.
In particular, the influence function of the sea temperature, salinity and ocean current velocity changes on the buoy density in the inventionIt can also be:
，
Wherein, For the first adjustment factor,/>Is a second adjustment factor.
And 103, completing large-scale buoy networking according to the number of buoys in the buoy network.
Example 4
The embodiment of the invention also provides electronic equipment, which comprises a processor and a storage medium connected with the processor, wherein the storage medium stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute a large-scale buoy networking method for marine environment research.
Specifically, the electronic device of the present embodiment may be a computer terminal, and the computer terminal may include: one or more processors, and a storage medium.
The storage medium may be used to store a software program and a module, such as a large-scale buoy networking method for marine environment research in the embodiment of the present invention, and the processor executes various functional applications and data processing by running the software program and the module stored in the storage medium, that is, implements the large-scale buoy networking method for marine environment research. The storage medium may include a high-speed random access storage medium, and may also include a non-volatile storage medium, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage medium. In some examples, the storage medium may further include a storage medium remotely located with respect to the processor, and the remote storage medium may be connected to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor may invoke the information stored in the storage medium and the application program via the transmission system to perform the following steps: the method comprises the following steps:
1. Buoy selection and design: the type of buoy selected for use in the marine environment may include floating buoys, submerged buoys, surface drifting buoys, etc. The buoy should be durable, adaptable and versatile to operate under different conditions.
2. Dividing the area: the investigation region is divided into a plurality of sub-regions according to the investigation objective and the marine process of interest. Each sub-area is provided with a group of buoys to form a buoy network.
3. Setting a buoy sensor: various sensors are installed on each buoy to measure ocean parameters such as temperature, salinity, flow rate, plankton concentration, etc. These sensors will collect data in real time and transmit it to a central data processing unit.
4. Setting a communication system: each buoy should be equipped with communication equipment, such as satellite communication or a wireless network connection, to enable data transmission between buoys and communication with ground stations.
5. Data collection and transmission: the buoy transmits the collected data to a central data processing unit. This may be accomplished through a communication link between buoys, or through a communication link with a ground station.
6. Data processing and analysis: the central data processing unit receives data from all buoys and processes and analyzes the data in real time. Scientists can monitor changes in the marine environment, study ocean currents, ocean temperatures, marine ecosystems, and the like.
7. Real-time feedback and adjustment: according to the data analysis result, the deployment position of the buoy can be adjusted in real time so as to optimize the data acquisition strategy and the research direction.
8. Data sharing and propagation: the collected data can be shared with the scientific community and the public through scientific research papers, databases, online platforms and other approaches, so that marine environment research and protection are promoted.
Specifically, as shown in fig. 1, an embodiment of the present invention provides a large-scale buoy networking method for marine environmental research, including:
step 101, dividing a marine area needing buoy networking into a plurality of subareas, and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
Step 102, setting a large-scale buoy networking model, and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
specifically, the large-scale buoy networking model includes:
,
where N is the number of buoys in the buoy network, N is the number of subregions, For/>The area of the sub-region is such that,For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>For/>Rate of change of ocean current velocity in sub-region,/>Is a function of the influence of variations in ocean temperature, salinity and ocean current velocity on buoy density.
Influence function of specific sea temperature, salinity and ocean current velocity changes on buoy densityThe method comprises the following steps:
,
Wherein, Is an overall adjustment factor,/>Is ocean temperature adjustment factor,/>For the ocean current speed adjustment factor,/>Index adjustment factor sum for salinity/>An index adjustment factor for ocean temperature, influencing the function/>Nonlinear functions have been introduced to take into account the nonlinear effects of ocean temperature, salinity and ocean current velocity in order to more accurately describe the effects of these ocean environmental factors on buoy density. The technical effects and roles of this formula are as follows:
modeling of nonlinear effects: by introducing a nonlinear function, the formula can better capture the nonlinear effects of marine environmental factors. This is important for the complex relationships that exist in practice, as changes in temperature, salinity and ocean current velocity may not linearly affect buoy density.
Weighing the importance of each factor: adjustment factor、/>、/>、/>、/>Allowing the user to customize the function to reflect the relative importance of the marine environmental factors, as the case may be. Thus, the user can determine the weight of each factor on the density of the buoy according to the project requirement, so that the model is more suitable for different situations.
Integrating a plurality of environmental factors: the function integrates a plurality of environmental factors such as ocean temperature, salinity, ocean current velocity and the like into one function so as to more comprehensively evaluate the buoy deployment density.
Scientific support decision: the function can be used as a decision support tool to help a decision maker optimize the design and deployment of the buoy network in the marine environmental research project. By taking into account a number of environmental factors, a decision maker may more scientifically formulate a decision strategy to meet a particular goal of research, monitoring, or management.
More accurate model: compared with a simple linear function, the function can reflect complex interaction and nonlinear relation in a real marine environment more accurately, so that accuracy and reliability of buoy network deployment decisions are improved.
In particular, the influence function of the sea temperature, salinity and ocean current velocity changes on the buoy density in the inventionIt can also be:
，
Wherein, For the first adjustment factor,/>Is a second adjustment factor.
And 103, completing large-scale buoy networking according to the number of buoys in the buoy network.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the embodiments provided in the present invention, it should be understood that the disclosed technology may be implemented in other manners. The system embodiments described above are merely exemplary, and for example, the division of the units is merely a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or partly in the form of a software product or all or part of the technical solution, which is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random-access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, etc., which can store program codes.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.
Claims (6)
1. A method for large scale buoys networking for marine environmental research, comprising:
Dividing an ocean area needing buoy networking into a plurality of subareas, and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
setting a large-scale buoy networking model, and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
wherein, the large-scale buoy networking model includes:
，
where N is the number of buoys in the buoy network, N is the number of subregions, For/>Area of sub-region,/>For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>For/>Rate of change of ocean current velocity in sub-region,/>Is the influence function of the change of ocean temperature, salinity and ocean current velocity on the density of the buoy;
And completing large-scale buoy networking through the number of buoys in the buoy network.
2. A method of large scale buoys networking for marine environmental studies, as claimed in claim 1, wherein the sea temperature, salinity and ocean current velocity changes are a function of the buoy densityThe method comprises the following steps:
，
Wherein, Is an overall adjustment factor,/>Is ocean temperature adjustment factor,/>For the ocean current speed adjustment factor,/>Index adjustment factor sum for salinity/>Is an exponential adjustment factor for ocean temperature.
3. A method of large scale buoys networking for marine environmental studies, as claimed in claim 1, wherein the sea temperature, salinity and ocean current velocity changes are a function of the buoy densityThe method comprises the following steps:
，
Wherein, For the first adjustment factor,/>Is a second adjustment factor.
4. A method of large scale buoys networking for marine environmental studies, as claimed in claim 1, wherein a set of buoys is deployed for each of the sub-areas.
5. A method of large scale buoys networking for marine environmental studies, as claimed in claim 1, wherein the data collected by each buoy is received by a central data processing unit.
6. A large scale buoy networking system for marine environmental research, comprising:
The data acquisition module is used for dividing the ocean area needing buoy networking into a plurality of subareas and acquiring area data of each subarea, wherein the area data comprises: the method comprises the steps of determining the area of a subarea, the priority of the subarea, the boundary length of the subarea, the underwater geological characteristics of the subarea, the ocean temperature change rate of the subarea, the salinity change rate of the subarea and the ocean current speed change rate of the subarea;
The model setting module is used for setting a large-scale buoy networking model and calculating the number of buoys in a buoy network according to the regional data of each sub-region, wherein the large-scale buoy networking model comprises: an influence function of the changes in ocean temperature, salinity and ocean current velocity on the buoy density;
wherein, the large-scale buoy networking model includes:
，
where N is the number of buoys in the buoy network, N is the number of subregions, For/>Area of sub-region,/>For/>Priority of individual sub-regions,/>For/>Boundary length of sub-region,/>For/>Underwater geological properties of individual sub-regions,/>For/>Ocean temperature rate of change of sub-region,/>For/>Salinity change rate of individual subregions,/>For/>Rate of change of ocean current velocity in sub-region,/>Is the influence function of the change of ocean temperature, salinity and ocean current velocity on the density of the buoy;
And the networking module is used for completing large-scale buoy networking according to the number of buoys in the buoy network.
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