Adaptive culture management method and system for penaeus vannamei in plateau saline-alkali water body

Abstract

The invention relates to the technical field of aquaculture management, and discloses an adaptive aquaculture management method and system for penaeus vannamei in plateau saline-alkali water. The system comprises a white prawn culture area sampling point information acquisition module, a white prawn culture area adaptability culture strategy evaluation module and a white prawn culture area adaptability culture management module. Precise evaluation of an optimal plateau saline-alkali water body culture strategy required by different growth stages of white shrimps is carried out by combining plateau saline-alkali water body culture strategy parameters stored in different growth stages of the white shrimps based on big data, an intelligent search algorithm and white shrimp growth stage judgment information in a culture area. The optimal culture strategy is adopted for the penaeus vannamei in different growth stages of plateau saline-alkali water body adaptive culture, and the refinement of penaeus vannamei plateau saline-alkali water body adaptive culture management is improved.

Description

Technical Field

[0001] The invention relates to the technical field of aquaculture management, and in particular to an adaptive aquaculture management method and system for Penaeus vannamei in plateau saline-alkali water bodies. Background Art

[0002] Penaeus vannamei is a decapod Penaeididae genus animal, also known as white shrimp, white shrimp. Penaeus vannamei is mainly distributed in the Pacific coast of America, and is also farmed in the Yellow Sea and Bohai Sea of ​​China. Penaeus vannamei is a tropical shrimp with wide temperature and salt content, often living in muddy seabed. During the day, it crawls or lurks on the surface of the seabed, and is active at night. Adult shrimps mostly live in coastal waters close to the shore, while young shrimps like to forage and grow in estuaries rich in bait organisms. Penaeus vannamei is an omnivorous carnivorous animal with low requirements for feed protein. In natural sea areas, when the average body length of Penaeus vannamei reaches 12 cm, it begins to migrate to the nearshore, leaving the shallow waters and living in deeper seas to mate, lay eggs, and hatch young. With the increase in domestic consumption demand for white shrimp, how to scientifically utilize China's plateau saline-alkali land to form plateau saline-alkali water bodies for the promotion of white shrimp farming has become a very important issue. The main differences between plateau saline-alkali water bodies and seawater are the salinity, pH value, carbonate alkalinity and ion coefficient of the water bodies; at the same time, the composition stability of plateau saline-alkali water bodies is poor compared with that of seawater; the existing adaptive farming management of white shrimp in plateau saline-alkali water bodies cannot realize intelligent and accurate identification of white shrimp growth stage information, nor can it realize scientific and accurate management of white shrimp adaptive farming operations in plateau saline-alkali water bodies based on the white shrimp growth stage information.

[0003] A Chinese invention patent application with publication number CN118096422A discloses an aquaculture feeding management method, device, computer equipment and storage medium, which collects environmental parameters, a first number of fish and shrimp on the water surface, the intensity of the sound of fish and shrimp eating and a second number of fish and shrimp underwater and uploads them to a control center simultaneously, reads the control parameters and combines the aquaculture feeding algorithm and the control parameters to generate a feeding strategy, thereby achieving precise feeding in aquaculture; however, the above technical solutions cannot comprehensively and scientifically formulate reasonable aquaculture feeding plans based on the growth stages of fish and shrimp, which reduces the scientificity and quality of aquaculture management. Summary of the invention

[0004] 1. Technical issues to be resolved To solve the problem that the existing intelligent and accurate identification of the growth stage information of white shrimp in plateau saline-alkali water bodies cannot be achieved, and the scientific and accurate management of the adaptive aquaculture operation of white shrimp in plateau saline-alkali water bodies cannot be realized based on the growth stage information of white shrimp, and to achieve the above purposes of accurately collecting the three-dimensional model of the white shrimp aquaculture area, scientifically establishing the coordinate information of the white shrimp aquaculture sampling points, efficiently collecting the real-time growth appearance image information of white shrimp, intelligently analyzing the growth stage information of white shrimp at the aquaculture sampling points, comprehensively judging the growth stage information of white shrimp in the aquaculture area, scientifically evaluating the optimal aquaculture strategy of white shrimp in the current growth stage in plateau saline-alkali water bodies, and autonomously and efficiently executing the adaptive aquaculture management operation of white shrimp in plateau saline-alkali water bodies.

[0005] (2) Technical solution The present invention is achieved through the following technical solutions: A method for the adaptive aquaculture management of Litopenaeus vannamei in plateau saline-alkali water bodies, the method comprising the following steps: S1. Collect three-dimensional model data of the white shrimp aquaculture area; S2. Based on the three-dimensional model data of the white shrimp aquaculture area, perform processing for establishing the coordinates of the growth stage monitoring sampling points of white shrimp in the white shrimp aquaculture area, generate coordinate data of the white shrimp aquaculture sampling points, and perform the operation of collecting the real-time growth appearance images of white shrimp at the positions of the white shrimp aquaculture sampling points to generate real-time growth appearance image data of white shrimp aquaculture; S3. Based on the real-time growth appearance image data of white shrimp aquaculture and the standard growth stage image data of white shrimp, perform processing for analyzing the growth stage of white shrimp at the positions of the white shrimp aquaculture sampling points to generate analysis data of the growth stage of white shrimp at the aquaculture sampling points; S4. According to the analysis data of the growth stage of white shrimp at the aquaculture sampling points, perform processing for statistically calculating the weight values of white shrimp at different growth stages in the aquaculture area to generate weight data of the growth stage of white shrimp in the aquaculture area; S5. Based on the weight data of the growth stage of white shrimp in the aquaculture area and the judgment weight threshold of the growth stage of white shrimp in the aquaculture area, perform comprehensive judgment processing on the growth stage of white shrimp in the aquaculture area to generate judgment data of the growth stage of white shrimp in the aquaculture area; S6. Based on the judgment data of the growth stage of white shrimp in the aquaculture area and the aquaculture strategy data of plateau saline-alkali water bodies at different growth stages of white shrimp, perform evaluation processing on the optimal aquaculture strategy of plateau saline-alkali water bodies required at different growth stages of white shrimp to generate data of the optimal aquaculture strategy of plateau saline-alkali water bodies at the current growth stage of white shrimp; S7. Construct evaluation result data of the optimal adaptive aquaculture strategy of white shrimp in the current plateau saline-alkali water bodies and execute the adaptive aquaculture management operation of white shrimp in plateau saline-alkali water bodies.

[0006] Preferably, the operation steps for collecting three-dimensional model data of the white shrimp aquaculture area are as follows: S11. Use a drone equipped with a 3D laser scanner to online scan the geospatial 3D model parameters of the target white shrimp farming area, and generate 3D model data of the white shrimp farming area .

[0007] Preferably, based on the 3D model data of the white shrimp farming area, establish and process the coordinates of the monitoring sampling points for the growth stage of white shrimp in the white shrimp farming area, generate the coordinate data of the white shrimp farming sampling points, and perform the operation of collecting the growth appearance images of white shrimp at the positions of the white shrimp farming sampling points, and generate the operation steps of the real scene growth appearance image data of white shrimp as follows: S21. For the water surface of the white shrimp farming area corresponding to the 3D model data of the white shrimp farming area Perform a planar grid division process using a square grid with a side length of L, and establish monitoring sampling points for the growth stage of white shrimp in the farming area with the center points of the square grids; S22. Establish a spatial spherical coordinate system with the earth sphere as the base, obtain the coordinate data of the monitoring sampling points for the growth stage of white shrimp in step S21, and construct a set of coordinate data of the white shrimp farming sampling points , ; where represents the coordinate data of the white shrimp farming sampling point corresponding to the th farming sampling point, represents the maximum value of the number of farming sampling points, and the coordinate data of the white shrimp farming sampling points includes the longitude, latitude, and altitude of the farming sampling points; S23. The drone is equipped with an underwater camera and, according to the set of coordinate data of the white shrimp farming sampling points in the coordinate data of the white shrimp farming sampling points in the set, perform the operation of collecting the growth appearance images of white shrimp in the real scene state in the water body of the farming sampling points in order according to the farming sampling point numbers, and generate a set of real scene growth appearance image data of white shrimp , where represents the real scene growth appearance image data of white shrimp corresponding to the th farming sampling point.‌ Preferably, based on the real scene growth appearance image data of white shrimp and the standard growth stage image data of white shrimp, perform an analysis process on the growth stage of white shrimp at the positions of the white shrimp farming sampling points, and generate the operation steps of the growth stage analysis data of white shrimp at the farming sampling points as follows: S31. Establish a set of standard growth stage image data of white shrimp , ; where represents the standard growth stage image data of white shrimp corresponding to the th growth stage type of white shrimp, Represents the maximum value of the number of white shrimp growth stage types, where the white shrimp growth stage types include the fertilized egg growth stage, nauplius growth stage, zoea larva growth stage, mysis larva growth stage, postlarva growth stage, juvenile shrimp growth stage, and adult shrimp growth stage; the white shrimp aquaculture standard growth stage image data represents the standard growth appearance image data set according to different growth stages in the white shrimp aquaculture process; S32. For the set of white shrimp aquaculture actual growth appearance image data The white shrimp aquaculture actual growth appearance image data in Is orderly matched with the set of white shrimp aquaculture standard growth stage image data according to the aquaculture sampling point number The white shrimp aquaculture standard growth stage image data in Perform image feature matching, search and analyze the white shrimp aquaculture standard growth stage image data that matches the white shrimp aquaculture actual growth appearance image data And generate the white shrimp growth stage analysis data set corresponding to the aquaculture sampling point , and the specific operation steps for generating the white shrimp growth stage analysis data set corresponding to the aquaculture sampling point Are as follows: S321. Initialize and set the maximum number of iterations T; S322. After initialization, perform the growth stage analysis moth selection flame. Initially generate Growth stage analysis moths and In the solution space of the set of white shrimp aquaculture standard growth stage image data Flames, and And = , search for the white shrimp aquaculture standard growth stage image data that matches the white shrimp aquaculture actual growth appearance image data in the search space of the set of white shrimp aquaculture standard growth stage image data The growth stage analysis moths fly around the selected flame in the search space of the set of white shrimp aquaculture standard growth stage image data The white shrimp aquaculture standard growth stage image data that matches , and Search space, Growth stage analysis moths and Flames are sorted by quality, and the sorted Flames are moved to the positions of the top With better positions. Each growth stage analysis moth selects different white shrimp aquaculture standard growth stage image data in the search space of the set of white shrimp aquaculture standard growth stage image data Flame, as the number of iterations increases, the number of flames decreases. The formula for calculating the number of flames is as follows: ,in Indicates The first iteration is to collect the image data of the standard growth stage of white shrimp farming The number of flames in the search space, represents a random function with values ​​between 0 and 1, Represents a set of image data at the standard growth stage of white shrimp farming The total number of flames initially generated in the search space, T represents the maximum number of iterations; S323, growth stage analysis moths select flames and then fly around the flames. For growth stage analysis moths fly around the flames in the white shrimp farming standard growth stage image data set. Searching for positions in space , Growth stage analysis of moths around flames in the white shrimp farming standard growth stage image data set Searching for positions in space The image data set of the growth stage of the white shrimp culture standard after the moth flies around the flame and the growth stage analysis New position in the search space , the new position calculation formula is as follows: ,in Indicates the growth stage analysis of moths With flame Image data collection of standard growth stages of white shrimp farming The distance value in the search space, represents the exponential function, is the current iteration number, where The coefficient is 2. Indicates angle value The corresponding cosine value, represents pi; S324, growth stage analysis of moths in the white shrimp farming standard growth stage image data set Flying and moving the flame to the corresponding position in the search space, Growth stage analysis of moths in the standard growth stage image data set of white shrimp farming Search space around After the flames flew, update to new position, calculate this Image data of standard growth stages of white shrimp farming in new locations Image data of the actual growth appearance of white shrimp farming The fitness value of A new position and flames are based on + The positions are sorted according to their advantages and disadvantages, and the positions with better advantages are used as the positions of the flames in the next round, that is, in the image data set of the standard growth stage of white shrimp farming Search space to search for the image data of the standard growth stage of white shrimp farming that best matches the actual growth appearance image data of white shrimp farming ; ; S325. When the maximum number of iterations T is met, output the image data of the standard growth stage of white shrimp farming that best matches the actual growth appearance image data of white shrimp farming ; otherwise, loop and execute steps S322 to S324; S326. According to the image data of the standard growth stage of white shrimp farming that matches the actual growth appearance image data of white shrimp farming output in step S325 The corresponding white shrimp growth stage text information of the image data of the standard growth stage of white shrimp farming is generated, and the analysis data set of the white shrimp growth stage at the aquaculture sampling point is generated through data identification , where represents the analysis data of the white shrimp growth stage at the aquaculture sampling point corresponding to the th aquaculture sampling point.

[0008] Preferably, the operation steps for statistically processing the weight values of white shrimp at different growth stages in the aquaculture area according to the analysis data of the white shrimp growth stage at the aquaculture sampling point are as follows: S41. Use the XGBoost algorithm to statistically process the analysis data of the white shrimp growth stage at the aquaculture sampling point in the analysis data set of the white shrimp growth stage at the aquaculture sampling point The number of aquaculture sampling points occupied by different types of white shrimp growth stages in the white shrimp aquaculture area is statistically processed according to the keywords of the white shrimp growth stage type, and a summary data set of the number of aquaculture sampling points for the white shrimp growth stage in the aquaculture area is generated , where represents the summary data set of the number of aquaculture sampling points for the white shrimp growth stage in the aquaculture area corresponding to the th growth stage type of white shrimp; The unit of is individual; S42. The summary data set of the number of aquaculture sampling points for the white shrimp growth stage in the aquaculture area The summary data of the number of aquaculture sampling points for the white shrimp growth stage in the aquaculture area ​Take the quotient of the maximum number of aquaculture sampling points in the white shrimp aquaculture area to generate a set of growth stage weight data for white shrimp in the aquaculture area , where represents the growth stage weight data of white shrimp in the aquaculture area corresponding to the th growth stage type of white shrimp; The value of is

[0009] Preferably, based on the growth stage weight data of white shrimp in the aquaculture area and the growth stage judgment weight threshold of white shrimp in the aquaculture area, the operation steps for comprehensively judging the growth stage of white shrimp in the aquaculture area to generate growth stage judgment data of white shrimp in the aquaculture area are as follows: S51. Establish a growth stage judgment weight threshold for white shrimp in the aquaculture area , where The value of is The growth stage judgment weight threshold of white shrimp in the aquaculture area represents the minimum growth stage weight value for judging the specific growth stage type of white shrimp in the white shrimp aquaculture area; S52. Compare the weight value of the growth stage weight data of white shrimp in the aquaculture area in the set of growth stage weight data of white shrimp in the aquaculture area with the growth stage judgment weight threshold of white shrimp in the aquaculture area , search for the text information of the growth stage of white shrimp corresponding to the growth stage weight data of white shrimp in the aquaculture area not less than the growth stage judgment weight threshold of white shrimp in the aquaculture area , and generate growth stage judgment data of white shrimp in the aquaculture area through data identification . The growth stage judgment data of white shrimp in the aquaculture area represents the current growth stage type judgment information of white shrimp in the white shrimp aquaculture area.

[0010] Preferably, based on the growth stage judgment data of white shrimp in the aquaculture area and the high-altitude saline-alkali water body aquaculture strategy data for different growth stages of white shrimp, the operation steps for evaluating the optimal high-altitude saline-alkali water body aquaculture strategy required for different growth stages of white shrimp to generate the optimal high-altitude saline-alkali water body aquaculture strategy data for the current growth stage of white shrimp are as follows: S61. Establish a set of high-altitude saline-alkali water body aquaculture strategy data for different growth stages of white shrimp , where represents the th growth stage of white shrimpData on the breeding strategies for white shrimp at different growth stages corresponding to different growth stage types in plateau saline-alkali water bodies; the data on the breeding strategies for white shrimp at different growth stages in plateau saline-alkali water bodies represents information on the adaptive breeding technology strategies for plateau saline-alkali water bodies set according to the different growth stages in the process of white shrimp breeding. Among them, the information on the adaptive breeding technology strategies for plateau saline-alkali water bodies includes environmental management technology strategies, feed management technology strategies, and disease management technology strategies for the adaptive breeding of white shrimp in plateau saline-alkali water bodies; the environmental management technology strategies include water quality management technology strategies, water temperature management technology strategies, and light management technology strategies for the breeding of white shrimp in plateau saline-alkali water bodies; the feed management technology strategies include feed type management technology strategies, feed ratio management technology strategies, and feed feeding management technology strategies for the breeding of white shrimp in plateau saline-alkali water bodies; the disease management technology strategies include shrimp seedling disinfection management technology strategies and disease management technology strategies for the breeding of white shrimp in plateau saline-alkali water bodies; S62. Use the uniform cost search algorithm to process the data on the growth stage judgment of white shrimp in the breeding area and the set of data on the breeding strategies for white shrimp at different growth stages in plateau saline-alkali water bodies in the data on the breeding strategies for white shrimp at different growth stages in plateau saline-alkali water bodies to perform character matching of the growth stage types, and search for the data on the breeding strategies for white shrimp at different growth stages in plateau saline-alkali water bodies corresponding to the data on the growth stage judgment of white shrimp in the breeding area and generate the optimal data on the breeding strategies for white shrimp at the current growth stage in plateau saline-alkali water bodies through data identification . .

[0011] Preferably, the operation steps for constructing the optimal evaluation result data on the current adaptive breeding strategy of white shrimp in plateau saline-alkali water bodies and performing the adaptive breeding management operation of white shrimp in plateau saline-alkali water bodies are as follows: S71. Perform data identification processing on the optimal data on the breeding strategies for white shrimp at the current growth stage in plateau saline-alkali water bodies to construct the optimal evaluation result data on the current adaptive breeding strategy of white shrimp in plateau saline-alkali water bodies ; S72. The white shrimp breeding management platform controls the aquaculture equipment to perform the adaptive breeding management operation of white shrimp in plateau saline-alkali water bodies in an orderly manner according to the information on the environmental management technology strategy, feed management technology strategy, and disease management technology strategy for the adaptive breeding of white shrimp in plateau saline-alkali water bodies in the optimal evaluation result data on the current adaptive breeding strategy of white shrimp in plateau saline-alkali water bodies . The aquaculture equipment includes feed feeding equipment, water quality adjustment equipment, temperature adjustment equipment, light adjustment equipment, and disinfection equipment.

[0012] An adaptive aquaculture management system for Litopenaeus vannamei in plateau saline-alkali water bodies, which is used to implement the adaptive aquaculture management method for Litopenaeus vannamei in plateau saline-alkali water bodies. The system includes an information acquisition module for sampling points in the Litopenaeus vannamei aquaculture area, an evaluation module for adaptive aquaculture strategies in the Litopenaeus vannamei aquaculture area, and an adaptive aquaculture management module for the Litopenaeus vannamei aquaculture area; The information acquisition module for sampling points in the Litopenaeus vannamei aquaculture area includes a three-dimensional model acquisition unit for the Litopenaeus vannamei aquaculture area, a coordinate establishment unit for sampling points in the Litopenaeus vannamei aquaculture, and an image acquisition unit for the actual growth appearance of Litopenaeus vannamei in the aquaculture area; The three-dimensional model acquisition unit for the Litopenaeus vannamei aquaculture area collects three-dimensional model data of the Litopenaeus vannamei aquaculture area by using a three-dimensional laser scanner carried by an unmanned aerial vehicle; the coordinate establishment unit for sampling points in the Litopenaeus vannamei aquaculture processes the coordinates of the sampling points for monitoring the growth stages of Litopenaeus vannamei in the Litopenaeus vannamei aquaculture area based on the three-dimensional model data of the Litopenaeus vannamei aquaculture area to generate coordinate data for sampling points in the Litopenaeus vannamei aquaculture; the image acquisition unit for the actual growth appearance of Litopenaeus vannamei in the aquaculture area performs the operation of collecting images of the growth appearance of Litopenaeus vannamei at the positions of the sampling points in the Litopenaeus vannamei aquaculture in combination with an underwater camera carried by an unmanned aerial vehicle according to the coordinate data for sampling points in the Litopenaeus vannamei aquaculture to generate image data of the actual growth appearance of Litopenaeus vannamei in the aquaculture area; The evaluation module for adaptive aquaculture strategies in the Litopenaeus vannamei aquaculture area includes an image storage unit for standard growth stages of Litopenaeus vannamei, an information analysis unit for the growth stages of Litopenaeus vannamei at sampling points in the aquaculture, a weight statistics unit for the growth stages of Litopenaeus vannamei in the aquaculture area, a storage unit for judgment weights of the growth stages of Litopenaeus vannamei in the aquaculture area, a judgment unit for the growth stages of Litopenaeus vannamei in the aquaculture area, a storage unit for aquaculture strategies for Litopenaeus vannamei in plateau saline-alkali water bodies at different growth stages, and an evaluation unit for the optimal aquaculture strategy for Litopenaeus vannamei in plateau saline-alkali water bodies at the current growth stage; The white shrimp farming standard growth stage image storage unit is used to store white shrimp farming standard growth stage image data; the white shrimp growth stage information analysis unit at the farming sampling point analyzes and processes the white shrimp growth stage at the white shrimp farming sampling point position based on the white shrimp farming actual growth appearance image data and the white shrimp farming standard growth stage image data, and generates white shrimp growth stage analysis data at the farming sampling point; the white shrimp growth stage weight statistics unit in the farming area statistically processes the white shrimp weight values at different growth stages in the farming area according to the white shrimp growth stage analysis data at the farming sampling point, and generates white shrimp growth stage weight data in the farming area; the white shrimp growth stage judgment weight storage unit in the farming area is used to store the white shrimp growth stage judgment weight threshold in the farming area; the white shrimp growth stage judgment unit in the farming area comprehensively judges the white shrimp growth stage in the farming area based on the white shrimp growth stage weight data in the farming area and the white shrimp growth stage judgment weight threshold in the farming area, and generates white shrimp growth stage judgment data in the farming area; the white shrimp different growth stage plateau saline-alkali water body farming strategy storage unit is used to store white shrimp different growth stage plateau saline-alkali water body farming strategy data; the optimal white shrimp current growth stage plateau saline-alkali water body farming strategy evaluation unit evaluates and processes the optimal plateau saline-alkali water body farming strategy required for different growth stages of white shrimp based on the white shrimp growth stage judgment data in the farming area and the white shrimp different growth stage plateau saline-alkali water body farming strategy data, and generates optimal white shrimp current growth stage plateau saline-alkali water body farming strategy data; The white shrimp farming area adaptability farming management module includes an optimal white shrimp plateau saline-alkali water body adaptability farming strategy evaluation result construction unit and a white shrimp plateau saline-alkali water body adaptability farming management execution unit; The optimal white shrimp plateau saline-alkali water body adaptability farming strategy evaluation result construction unit is used to construct optimal white shrimp current plateau saline-alkali water body adaptability farming strategy evaluation result data; the white shrimp plateau saline-alkali water body adaptability farming management execution unit, and the white shrimp farming management platform orderly controls the aquaculture equipment to execute the white shrimp plateau saline-alkali water body adaptability farming management operation according to the optimal white shrimp current plateau saline-alkali water body adaptability farming strategy evaluation result data.

[0013] (III) Beneficial effects The present invention provides a method and system for the adaptability farming management of Litopenaeus vannamei in plateau saline-alkali water bodies. It has the following beneficial effects: 1. By accurately generating the three-dimensional model parameters of the white shrimp farming area online with a drone-mounted three-dimensional laser scanner, reliable data support is provided for scientifically and efficiently establishing the coordinates of growth stage monitoring sampling points. Based on the scientific processing of plane grid division data, the coordinate parameters of white shrimp farming sampling points are collected, and at the same time, combined with the underwater camera mounted on the drone, the growth appearance images of white shrimp at the positions of the farming sampling points are efficiently and reliably collected point by point, realizing the secure dynamic monitoring of the growth appearance image information of white shrimp in the adaptive farming in the high-altitude saline-alkali water body, and improving the reliability of the adaptive farming management of white shrimp in the high-altitude saline-alkali water body.

[0014] 2. By scientifically setting the image parameters of the standard growth stages of white shrimp farming and combining with intelligent recognition algorithms to analyze the growth stage type of white shrimp at the positions of the farming sampling points based on the actual growth appearance image parameters of white shrimp farming, the growth stage information of white shrimp at the adaptive farming sampling points in the high-altitude saline-alkali water body is efficiently and accurately analyzed, improving the intelligence and scientificity of the adaptive farming management of white shrimp in the high-altitude saline-alkali water body. Based on numerical analysis, the weight parameters of the growth stages of white shrimp in the farming area are accurately counted and comprehensively and accurately judged against the judgment weight threshold of the growth stages of white shrimp in the farming area, realizing the comprehensive and scientific analysis of the growth stage information of white shrimp in the adaptive farming in the high-altitude saline-alkali water body, and improving the quality of the adaptive farming management of white shrimp in the high-altitude saline-alkali water body. Based on the big data storage of the aquaculture strategy parameters of white shrimp at different growth stages in the high-altitude saline-alkali water body, combined with intelligent search algorithms and the growth stage judgment information of white shrimp in the farming area, the optimal aquaculture strategies required for different growth stages of white shrimp in the high-altitude saline-alkali water body are accurately evaluated, realizing the adoption of the optimal aquaculture strategies at different growth stages of white shrimp in the adaptive farming in the high-altitude saline-alkali water body, and improving the refinement of the adaptive farming management of white shrimp in the high-altitude saline-alkali water body.

[0015] 3. By scientifically constructing the optimal evaluation result parameters of the current adaptive aquaculture strategy of white shrimp in the high-altitude saline-alkali water body based on data processing, the efficient and accurate collection of the optimal aquaculture strategy parameters for different growth stages of white shrimp in the adaptive farming in the high-altitude saline-alkali water body is realized, improving the efficiency of the adaptive farming management of white shrimp in the high-altitude saline-alkali water body. The white shrimp farming management platform orderly controls the aquaculture equipment according to the optimal evaluation result parameters of the current adaptive aquaculture strategy of white shrimp in the high-altitude saline-alkali water body to accurately and autonomously execute the adaptive aquaculture management operations of white shrimp in the high-altitude saline-alkali water body, realizing the accuracy of the adaptive aquaculture management of white shrimp in the high-altitude saline-alkali water body, and improving the quality and yield of the adaptive aquaculture of white shrimp in the high-altitude saline-alkali water body. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the modules of the adaptive aquaculture management system of white shrimp in the high-altitude saline-alkali water body provided by the present invention; Figure 2 Flow chart of the adaptive aquaculture management method of Litopenaeus vannamei in plateau saline-alkali water bodies provided by the present invention. Detailed implementation manners

[0017] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] Embodiments of the adaptive aquaculture management method and system of Litopenaeus vannamei in plateau saline-alkali water bodies are as follows: Embodiment 1:

[0019] Please refer to Figure 1 - Figure 2 , the adaptive aquaculture management method of Litopenaeus vannamei in plateau saline-alkali water bodies, the method includes the following steps: S1. Collect three-dimensional model data of the Litopenaeus vannamei aquaculture area; S2. Based on the three-dimensional model data of the Litopenaeus vannamei aquaculture area, establish and process the coordinates of the sampling points for monitoring the growth stages of Litopenaeus vannamei in the aquaculture area, generate the coordinate data of the sampling points for Litopenaeus vannamei aquaculture, and perform the operation of collecting the growth appearance images of Litopenaeus vannamei at the positions of the sampling points for Litopenaeus vannamei aquaculture, and generate the real-scene growth appearance image data of Litopenaeus vannamei aquaculture; S3. Based on the real-scene growth appearance image data of Litopenaeus vannamei aquaculture and the standard growth stage image data of Litopenaeus vannamei, perform the analysis and processing of the growth stages of Litopenaeus vannamei at the positions of the sampling points for Litopenaeus vannamei aquaculture, and generate the analysis data of the growth stages of Litopenaeus vannamei at the sampling points for aquaculture; S4. According to the analysis data of the growth stages of Litopenaeus vannamei at the sampling points for aquaculture, perform the statistical processing of the weight values of Litopenaeus vannamei at different growth stages in the aquaculture area, and generate the weight data of the growth stages of Litopenaeus vannamei in the aquaculture area; S5. Based on the weight data of the growth stages of Litopenaeus vannamei in the aquaculture area and the judgment weight threshold of the growth stages of Litopenaeus vannamei in the aquaculture area, perform the comprehensive judgment processing of the growth stages of Litopenaeus vannamei in the aquaculture area, and generate the judgment data of the growth stages of Litopenaeus vannamei in the aquaculture area; S6. Based on the judgment data of the growth stages of Litopenaeus vannamei in the aquaculture area and the aquaculture strategy data of plateau saline-alkali water bodies at different growth stages of Litopenaeus vannamei, perform the evaluation processing of the optimal aquaculture strategy of plateau saline-alkali water bodies required at different growth stages of Litopenaeus vannamei, and generate the optimal aquaculture strategy data of plateau saline-alkali water bodies at the current growth stage of Litopenaeus vannamei; S7. Construct the evaluation result data of the optimal adaptive aquaculture strategy of Litopenaeus vannamei in the current plateau saline-alkali water bodies and execute the adaptive aquaculture management operation of Litopenaeus vannamei in the plateau saline-alkali water bodies.

[0020] Further, please refer to Figure 1 - Figure 2 , the operation steps for collecting the three-dimensional model data of the white shrimp farming area are as follows: S11. Use a drone to carry a three-dimensional laser scanner to online scan the geospatial three-dimensional model parameters of the target white shrimp farming area, and generate the three-dimensional model data of the white shrimp farming area .

[0021] Based on the three-dimensional model data of the white shrimp farming area, perform processing to establish the coordinates of the white shrimp growth stage monitoring sampling points in the white shrimp farming area, generate the white shrimp farming sampling point coordinate data, and perform the operation of collecting the white shrimp growth appearance images at the positions of the white shrimp farming sampling points, and the operation steps for generating the white shrimp farming real-scene growth appearance image data are as follows: S21. For the water surface of the white shrimp farming area corresponding to the three-dimensional model data of the white shrimp farming area , perform planar grid division processing using a square grid with a side length of L, and establish the white shrimp growth stage monitoring sampling points in the farming area with the center points of the square grids; S22. Establish a spatial spherical coordinate system with the earth sphere as the base body, obtain the coordinate data of the white shrimp growth stage monitoring sampling points in step S21, and construct a set of white shrimp farming sampling point coordinate data , where represents the white shrimp farming sampling point coordinate data corresponding to the th farming sampling point, represents the maximum value of the number of farming sampling points, and the white shrimp farming sampling point coordinate data includes the longitude, latitude, and altitude of the farming sampling points; S23. The drone carries an underwater camera to perform the operation of collecting the white shrimp growth appearance images in the real scene in the water body of the farming sampling points in an orderly manner according to the white shrimp farming sampling point coordinate data in the set of the white shrimp farming sampling point coordinate data , and generate a set of white shrimp farming real-scene growth appearance image data , where represents the white shrimp farming real-scene growth appearance image data corresponding to the th farming sampling point.‌ Through the three-dimensional model acquisition unit for the white shrimp farming area, a drone is used to carry a three-dimensional laser scanner to accurately generate the three-dimensional model parameters of the white shrimp farming area online, providing reliable data support for scientifically and efficiently establishing the coordinates of the growth stage monitoring sampling points; the white shrimp farming sampling point coordinate establishment unit and the white shrimp farming real-scene growth appearance image acquisition unit cooperate with each other to scientifically collect the white shrimp farming sampling point coordinate parameters based on the plane grid division data processing. At the same time, combined with the underwater camera carried by the drone, it realizes the efficient and reliable point-to-point acquisition of the white shrimp growth appearance images at the white shrimp farming sampling point positions, realizing the secure dynamic monitoring of the growth appearance image information of the white shrimp in the plateau saline-alkali water body, and improving the reliability of the management of the white shrimp's adaptation to the plateau saline-alkali water body.

[0022] Further, please refer to Figure 1 - Figure 2 , and based on the white shrimp farming real-scene growth appearance image data and the white shrimp farming standard growth stage image data, the operation steps for analyzing and processing the white shrimp growth stage at the white shrimp farming sampling point positions to generate the white shrimp growth stage analysis data at the farming sampling points are as follows: S31. Establish a set of white shrimp farming standard growth stage image data , ; where represents the white shrimp farming standard growth stage image data corresponding to the th growth stage type of white shrimp, represents the maximum value of the number of white shrimp growth stage types. The white shrimp growth stage types include the fertilized egg growth stage, nauplius growth stage, zoea larva growth stage, mysis larva growth stage, postlarva growth stage, juvenile shrimp growth stage, and adult shrimp growth stage; the white shrimp farming standard growth stage image data represents the standard growth appearance image data set according to different growth stages in the white shrimp farming process; S32. Arrange the white shrimp farming real-scene growth appearance image data in the white shrimp farming real-scene growth appearance image data set in an orderly manner according to the farming sampling point numbers and perform image feature matching with the white shrimp farming standard growth stage image data in the white shrimp farming standard growth stage image data set . Search and analyze the white shrimp growth stage text information corresponding to the white shrimp farming standard growth stage image data that matches the white shrimp farming real-scene growth appearance image data , and generate a set of white shrimp growth stage analysis data at the farming sampling points . The specific operation steps for generating the set of white shrimp growth stage analysis data at the farming sampling points are as follows: S321. Initialize and set the maximum number of iterations T; S322. After initialization, perform the growth stage analysis. The moths select the flames. In the solution space of the white shrimp aquaculture standard growth stage image data set initially generate growth stage analysis moths and flames, and = . In the white shrimp aquaculture standard growth stage image data set search space, search for the white shrimp aquaculture standard growth stage image data that matches the white shrimp aquaculture actual growth appearance image data . The growth stage analysis moths fly around the selected flames in the white shrimp aquaculture standard growth stage image data set search space. The growth stage analysis moths and flames are sorted by quality. Then move the sorted flames to the positions of the top with better positions. Each growth stage analysis moth selects distinct white shrimp aquaculture standard growth stage image data flames in the white shrimp aquaculture standard growth stage image data set search space. As the number of iterations increases, the number of flames decreases. The flame number calculation formula is as follows: , where represents the number of flames in the white shrimp aquaculture standard growth stage image data set at the th iteration, represents a random function with values from 0 to 1, represents the total number of initially generated flames in the white shrimp aquaculture standard growth stage image data set search space, and T represents the maximum number of iterations; S323. After the growth stage analysis moths select the flames, the growth stage analysis moths fly around the flames. For the position of the growth stage analysis moths in the white shrimp aquaculture standard growth stage image data set search space, the flame around which the growth stage analysis moths fly, its position in the white shrimp aquaculture standard growth stage image data set search space, and the new position of the growth stage analysis moths in the white shrimp aquaculture standard growth stage image data set search space after flying around the flame, the new position calculation formula is as follows: , where Indicating the growth stage analysis moth and the flame in the image data set of the standard growth stage of white shrimp farming The distance value in the search space, indicating the exponential function, is the current iteration number, where is the coefficient value 2, indicating the angle value the corresponding cosine value, indicating pi; S324. The growth stage analysis moth moves the flying mobile flame to the corresponding position in the image data set of the standard growth stage of white shrimp farming in the search space, Only the growth stage analysis moth in the image data set of the standard growth stage of white shrimp farming in the search space around After flying around the flame, update to a new position, calculate the image data of the standard growth stage of white shrimp farming at these new positions and the image data of the actual growth appearance of white shrimp farming of the fitness value, and sort these new positions and the flame according to + the positions from good to bad, and take the positions with good quality as the positions of the flame in the next round, that is, search in the image data set of the standard growth stage of white shrimp farming for the image data of the standard growth stage of white shrimp farming that best matches the image data of the actual growth appearance of white shrimp farming ; ; S325. When the maximum iteration number T is satisfied, output the image data of the standard growth stage of white shrimp farming that best matches the image data of the actual growth appearance of white shrimp farming otherwise, loop to execute steps S322 to S324; S326. According to the image data of the standard growth stage of white shrimp farming that matches the image data of the actual growth appearance of white shrimp farming output in step S325 the corresponding text information of the white shrimp growth stage, and generate the analysis data set of the white shrimp growth stage at the farming sampling point through data identification where indicating the analysis data of the white shrimp growth stage at the farming sampling point corresponding to the ​​

[0023] Based on the analysis data of the growth stages of white shrimp at the aquaculture sampling points, the operation steps for statistically processing the weight values of white shrimp at different growth stages in the aquaculture area and generating the weight data of white shrimp growth stages in the aquaculture area are as follows: S41. Use the XGBoost algorithm for the analysis data set of the growth stages of white shrimp at the aquaculture sampling points in the analysis data of the growth stages of white shrimp at the aquaculture sampling points Statistically process the number of aquaculture sampling points occupied by white shrimp at different growth stage types in the white shrimp aquaculture area according to the keywords of white shrimp growth stage types, and generate a summary data set of the number of aquaculture sampling points for white shrimp growth stages in the aquaculture area , where represents the summary data of the number of aquaculture sampling points for the growth stages of white shrimp in the aquaculture area corresponding to the th growth stage type of white shrimp; The unit of is "pcs"; S42. Divide the summary data of the number of aquaculture sampling points for the growth stages of white shrimp in the aquaculture area in the summary data set of the number of aquaculture sampling points for the growth stages of white shrimp in the aquaculture area by the maximum value of the number of aquaculture sampling points in the white shrimp aquaculture area to generate a data set of the weight data of white shrimp growth stages in the aquaculture area , where represents the weight data of white shrimp growth stages in the aquaculture area corresponding to the th growth stage type of white shrimp; The value of is

[0024] Based on the weight data of white shrimp growth stages in the aquaculture area and the judgment weight threshold of white shrimp growth stages in the aquaculture area, the operation steps for comprehensively judging the growth stages of white shrimp in the aquaculture area and generating the judgment data of white shrimp growth stages in the aquaculture area are as follows: S51. Establish the judgment weight threshold of white shrimp growth stages in the aquaculture area , where The value of is S52. Compare the weight data of white shrimp growth stages in the aquaculture area in the data set of the weight data of white shrimp growth stages in the aquaculture area with the judgment weight threshold of white shrimp growth stages in the aquaculture area Compare the weight values, and search for the weight data of white shrimp in the growth stage in the farming area Not less than the judgment weight threshold of the growth stage of white shrimp in the farming area The corresponding text information of the growth stage of white shrimp, and generate the judgment data of the growth stage of white shrimp in the farming area through data identification The judgment data of the growth stage of white shrimp in the farming area represents the judgment information of the current growth stage type of white shrimp in the farming area.

[0025] Based on the judgment data of the growth stage of white shrimp in the farming area and the farming strategy data of white shrimp in different growth stages in the high-altitude saline-alkali water body, conduct an evaluation process on the optimal farming strategy of white shrimp in different growth stages in the high-altitude saline-alkali water body, and the operation steps for generating the optimal farming strategy data of white shrimp in the current growth stage in the high-altitude saline-alkali water body are as follows: S61. Establish a data set of farming strategies for white shrimp in different growth stages in the high-altitude saline-alkali water body , where represents the farming strategy data of white shrimp in different growth stages corresponding to the th growth stage type of white shrimp; the farming strategy data of white shrimp in different growth stages in the high-altitude saline-alkali water body represents the information of the adaptive farming technology strategy of the high-altitude saline-alkali water body set for different growth stages in the farming process of white shrimp. The information of the adaptive farming technology strategy of the high-altitude saline-alkali water body includes the environmental management technology strategy, feed management technology strategy, and disease management technology strategy for the adaptive farming of white shrimp in the high-altitude saline-alkali water body; the environmental management technology strategy includes the water quality management technology strategy, water temperature management technology strategy, and light management technology strategy for farming in the high-altitude saline-alkali water body; the feed management technology strategy includes the feed type management technology strategy, feed ratio management technology strategy, and feed feeding management technology strategy for farming in the high-altitude saline-alkali water body; the disease management technology strategy includes the shrimp seedling disinfection management technology strategy and the disease management technology strategy for farming in the high-altitude saline-alkali water body; S62. Use the uniform cost search algorithm to match the judgment data of the growth stage of white shrimp in the farming area with the data set of farming strategies for white shrimp in different growth stages in the high-altitude saline-alkali water body to match the farming strategy data of white shrimp in different growth stages in the high-altitude saline-alkali water body in the data set, search for the farming strategy data of white shrimp in different growth stages corresponding to the judgment data of the growth stage of white shrimp in the farming area , and generate the optimal farming strategy data of white shrimp in the current growth stage in the high-altitude saline-alkali water body through data identification . .

[0026] Through the cooperation of the standard growth stage image storage unit of white shrimp farming and the growth stage information analysis unit of white shrimp at the farming sampling points, scientifically set the image parameters of the standard growth stage of white shrimp, and combine the intelligent recognition algorithm with the image parameters of the actual growth appearance of white shrimp in the farming scene to intelligently and accurately analyze the growth stage type of white shrimp at the farming sampling points of white shrimp farming, so as to realize the efficient and accurate analysis of the growth stage information of Litopenaeus vannamei at the adaptive farming sampling points in the high-altitude saline-alkali water body, and improve the intelligence and scientific nature of the adaptive farming management of Litopenaeus vannamei in the high-altitude saline-alkali water body; the growth stage weight statistics unit of white shrimp in the farming area and the growth stage judgment unit of white shrimp in the farming area cooperate with each other, accurately count the growth stage weight parameters of white shrimp in the farming area based on numerical analysis, and perform a comprehensive and accurate judgment of the growth stage of white shrimp in the farming area with the growth stage judgment weight threshold of white shrimp in the farming area, so as to realize a comprehensive and scientific analysis of the growth stage information of Litopenaeus vannamei in the adaptive farming in the high-altitude saline-alkali water body, and improve the quality of the adaptive farming management of Litopenaeus vannamei in the high-altitude saline-alkali water body; the storage unit of the farming strategies for different growth stages of white shrimp in the high-altitude saline-alkali water body and the evaluation unit of the optimal farming strategy for the current growth stage of white shrimp in the high-altitude saline-alkali water body cooperate with each other, store the farming strategy parameters for different growth stages of white shrimp in the high-altitude saline-alkali water body based on big data, combine the intelligent search algorithm with the growth stage judgment information of white shrimp in the farming area to accurately evaluate the optimal farming strategy required for different growth stages of white shrimp in the high-altitude saline-alkali water body, so as to realize the adoption of the optimal farming strategy for different growth stages of Litopenaeus vannamei in the adaptive farming in the high-altitude saline-alkali water body, and improve the refinement of the adaptive farming management of Litopenaeus vannamei in the high-altitude saline-alkali water body.

[0027] Further, please refer to Figure 1 - Figure 2 to construct the evaluation result data of the optimal farming strategy for the current high-altitude saline-alkali water body adaptability of white shrimp and the operation steps for performing the farming management operation of white shrimp in the high-altitude saline-alkali water body are as follows: S71. Process the data of the optimal farming strategy for the current growth stage of white shrimp in the high-altitude saline-alkali water body to perform data identification processing and construct the evaluation result data of the optimal farming strategy for the current high-altitude saline-alkali water body adaptability of white shrimp ; S72. According to the evaluation result data of the optimal farming strategy for the current high-altitude saline-alkali water body adaptability of white shrimp in the white shrimp farming management platform, the environmental management technical strategy information, feed management technical strategy information, and disease management technical strategy information for the high-altitude saline-alkali water body adaptability farming of white shrimp are used to orderly control the aquaculture equipment to perform the farming management operation of white shrimp in the high-altitude saline-alkali water body. The aquaculture equipment includes feeding equipment, water quality adjustment equipment, temperature adjustment equipment, light adjustment equipment, and disinfection equipment.

[0028] By constructing a unit for evaluating the optimal aquaculture strategy for white shrimp in plateau saline-alkali water bodies, based on data processing science, the evaluation result parameters of the optimal aquaculture strategy for white shrimp in the current plateau saline-alkali water bodies are constructed, enabling the efficient and accurate collection of the optimal aquaculture strategy parameters for different growth stages of white shrimp in plateau saline-alkali water bodies, and improving the efficiency of the aquaculture management of white shrimp in plateau saline-alkali water bodies; the implementation unit for the aquaculture management of white shrimp in plateau saline-alkali water bodies, where the white shrimp aquaculture management platform orderly controls the aquaculture equipment according to the evaluation result parameters of the optimal aquaculture strategy for white shrimp in the current plateau saline-alkali water bodies to accurately and autonomously execute the aquaculture management operations of white shrimp in plateau saline-alkali water bodies, realizing the accuracy of the aquaculture management of white shrimp in plateau saline-alkali water bodies and improving the aquaculture quality and yield of white shrimp in plateau saline-alkali water bodies.

[0029] Embodiment 2:

[0030] Please refer to Figure 1 - Figure 2 , an adaptive aquaculture management system for white shrimp in plateau saline-alkali water bodies, which is used to implement the adaptive aquaculture management method for white shrimp in plateau saline-alkali water bodies. The system includes an information acquisition module for sampling points in the white shrimp aquaculture area, an evaluation module for the adaptive aquaculture strategy in the white shrimp aquaculture area, and an adaptive aquaculture management module in the white shrimp aquaculture area; The information acquisition module for sampling points in the white shrimp aquaculture area includes a three-dimensional model acquisition unit for the white shrimp aquaculture area, a coordinate establishment unit for the white shrimp aquaculture sampling points, and an image acquisition unit for the actual growth appearance of white shrimp in the aquaculture area; The three-dimensional model acquisition unit for the white shrimp aquaculture area collects the three-dimensional model data of the white shrimp aquaculture area by using a three-dimensional laser scanner carried by a drone; the coordinate establishment unit for the white shrimp aquaculture sampling points performs coordinate establishment processing on the sampling points for monitoring the growth stages of white shrimp in the white shrimp aquaculture area based on the three-dimensional model data of the white shrimp aquaculture area to generate the coordinate data of the white shrimp aquaculture sampling points; the image acquisition unit for the actual growth appearance of white shrimp in the aquaculture area performs the operation of collecting the growth appearance images of white shrimp at the positions of the white shrimp aquaculture sampling points by combining the coordinate data of the white shrimp aquaculture sampling points with an underwater camera carried by a drone to generate the image data of the actual growth appearance of white shrimp in the aquaculture area; The evaluation module for the adaptive aquaculture strategy in the white shrimp aquaculture area includes an image storage unit for the standard growth stages of white shrimp in aquaculture, an information analysis unit for the growth stages of white shrimp at the aquaculture sampling points, a weight statistics unit for the growth stages of white shrimp in the aquaculture area, a storage unit for the judgment weights of the growth stages of white shrimp in the aquaculture area, a judgment unit for the growth stages of white shrimp in the aquaculture area, a storage unit for the aquaculture strategies of white shrimp in plateau saline-alkali water bodies at different growth stages, and an evaluation unit for the current growth stage of the optimal white shrimp in plateau saline-alkali water bodies; The white shrimp farming standard growth stage image storage unit is used to store the white shrimp farming standard growth stage image data; the white shrimp growth stage information analysis unit at the farming sampling point analyzes and processes the white shrimp growth stage at the white shrimp farming sampling point location based on the white shrimp farming actual growth appearance image data and the white shrimp farming standard growth stage image data, and generates the white shrimp growth stage analysis data at the farming sampling point; the white shrimp growth stage weight statistics unit in the farming area statistically processes the white shrimp weight values at different growth stages in the farming area according to the white shrimp growth stage analysis data at the farming sampling point, and generates the white shrimp growth stage weight data in the farming area; the white shrimp growth stage judgment weight storage unit in the farming area is used to store the white shrimp growth stage judgment weight threshold in the farming area; the white shrimp growth stage judgment unit in the farming area comprehensively judges the white shrimp growth stage in the farming area based on the white shrimp growth stage weight data in the farming area and the white shrimp growth stage judgment weight threshold in the farming area, and generates the white shrimp growth stage judgment data in the farming area; the white shrimp different growth stage high-altitude saline-alkali water body farming strategy storage unit is used to store the white shrimp different growth stage high-altitude saline-alkali water body farming strategy data; the optimal white shrimp current growth stage high-altitude saline-alkali water body farming strategy evaluation unit evaluates and processes the optimal high-altitude saline-alkali water body farming strategy required for different growth stages of white shrimp based on the white shrimp growth stage judgment data in the farming area and the white shrimp different growth stage high-altitude saline-alkali water body farming strategy data, and generates the optimal white shrimp current growth stage high-altitude saline-alkali water body farming strategy data; The white shrimp farming area adaptability farming management module includes an optimal white shrimp high-altitude saline-alkali water body adaptability farming strategy evaluation result construction unit and a white shrimp high-altitude saline-alkali water body adaptability farming management execution unit; The optimal white shrimp high-altitude saline-alkali water body adaptability farming strategy evaluation result construction unit is used to construct the optimal white shrimp current high-altitude saline-alkali water body adaptability farming strategy evaluation result data; the white shrimp high-altitude saline-alkali water body adaptability farming management execution unit, and the white shrimp farming management platform orderly controls the aquaculture equipment to execute the white shrimp high-altitude saline-alkali water body adaptability farming management operation according to the optimal white shrimp current high-altitude saline-alkali water body adaptability farming strategy evaluation result data.

[0031] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An adaptive breeding management method for Penaeus vannamei in plateau saline-alkali water bodies, characterized in that: The method comprises the following steps: S1. Collect three-dimensional model data of white shrimp breeding area; S2, based on the three-dimensional model data of the white shrimp breeding area, the white shrimp growth stage monitoring sampling point coordinates are established in the white shrimp breeding area, the white shrimp breeding sampling point coordinate data are generated, and the white shrimp growth appearance image collection operation is performed at the white shrimp breeding sampling point position, and the white shrimp breeding real-life growth appearance image data is generated; S3, performing white shrimp growth stage analysis processing at the white shrimp farming sampling point location based on the white shrimp farming real-life growth appearance image data and the white shrimp farming standard growth stage image data, and generating white shrimp growth stage analysis data at the farming sampling point; S4, performing numerical statistical processing on weights of white shrimp at different growth stages in the breeding area according to the white shrimp growth stage analysis data at the breeding sampling points, and generating white shrimp growth stage weight data in the breeding area; S5, performing a comprehensive judgment process on the growth stage of whiteleg shrimp in the breeding area according to the weight data of the growth stage of whiteleg shrimp in the breeding area and the weight threshold for judging the growth stage of whiteleg shrimp in the breeding area, and generating judgment data on the growth stage of whiteleg shrimp in the breeding area; S6, based on the white shrimp growth stage judgment data of the breeding area and the plateau saline-alkali water breeding strategy data of white shrimp at different growth stages, the optimal plateau saline-alkali water breeding strategy required for white shrimp at different growth stages is evaluated and processed to generate the optimal plateau saline-alkali water breeding strategy data of white shrimp at the current growth stage; S7. Construct the optimal evaluation result data of the current adaptive breeding strategy for white shrimp in plateau saline-alkali water bodies and implement the adaptive breeding management operation for white shrimp in plateau saline-alkali water bodies.

2. The adaptive breeding management method of Penaeus vannamei in plateau saline-alkali water according to claim 1, characterized in that: The S1 comprises the following steps: S11. Scan the geographic spatial 3D model parameters of the target white shrimp farming area online through a drone equipped with a 3D laser scanner, and generate 3D model data of the white shrimp farming area .

3. The adaptive breeding management method of Penaeus vannamei in plateau saline-alkali water according to claim 2 is characterized in that: The S2 comprises the following steps: S21, the three-dimensional model data of the white shrimp breeding area The water surface of the corresponding white shrimp breeding area is divided into plane grids using square grids with a side length of L, and the white shrimp growth stage monitoring sampling points in the breeding area are established at the center points of the square grids; S22, establish a spatial spherical coordinate system based on the earth sphere, obtain the coordinate data of the sampling points for monitoring the growth stage of white shrimp in step S21, and construct a set of coordinate data of the sampling points for white shrimp farming , ;in Indicates The coordinate data of the white shrimp farming sampling points corresponding to the farming sampling points, Indicates the maximum number of aquaculture sampling points; S23, drones equipped with underwater cameras according to the As stated in According to the aquaculture sampling point number, the white shrimp growth appearance image collection operation in the water body of the aquaculture sampling point in real scene state is carried out in order, and the white shrimp aquaculture real scene growth appearance image data set is generated ,in Indicates The real-life growth appearance image data of white shrimp farming corresponding to the farming sampling points.

4. The adaptive breeding management method of Penaeus vannamei in plateau saline-alkali water according to claim 3 is characterized in that: The S3 comprises the following steps: S31. Establishing a standard growth stage image data set for white shrimp farming , ;in Indicates white shrimp Standard growth stage image data of white shrimp farming corresponding to the growth stage types, Indicates the maximum number of growth stage types of white shrimp; S32, the As stated in The sampling points are numbered in order according to the As stated in Perform image feature matching and search and analyze the Matching the Corresponding white shrimp growth stage text information, and generate white shrimp growth stage analysis data set of breeding sampling points , execute to generate the The specific steps are as follows: S321, initialization, setting the maximum number of iterations T; S322, after initialization, perform growth phase analysis to select flames for moths, in the Initial generation in the solution space Analysis of moths and A flame, and = , in the Search the search space for Matching the , growth stage analysis of moths in the Flying around the selected flame in the search space, Analysis of moths and The flames are sorted by quality, and the sorted The flame moves to the front of the optimal position Each growth stage was analyzed for moths in the In the search space, different Flame, as the number of iterations increases, the number of flames decreases; S323, after the growth stage analysis moth selects the flame, the growth stage analysis moth flies around the flame, and the growth stage analysis moth flies around the flame. Searching for positions in space , growth stage analysis of moths around the flame in the Searching for positions in space and growth stage analysis of moths after flying around a flame New position in the search space ; S324, growth stage analysis of moths in the Flying and moving the flame to the corresponding position in the search space, Only the growth stages of moths were analyzed in Search space around After the flames flew, update to new position, calculate this New location With the The fitness value of New locations and Flame basis + The positions are sorted by quality and the ones with good quality are The position is used as the position of the flame in the next round, that is, in the Search the search space for The best match for ; S325. When the maximum number of iterations T is met, output the same as described above. The best match for , otherwise, the steps S322 to S324 are executed in a loop; S326, output according to step S325 and the Matching the The corresponding white shrimp growth stage text information is used to generate the white shrimp growth stage analysis data set of the breeding sampling point through data identification. ,in Indicates Analysis data of white shrimp growth stages at the aquaculture sampling points corresponding to the aquaculture sampling points.

5. The adaptive breeding management method of Penaeus vannamei in plateau saline-alkali water according to claim 4, characterized in that: The S4 comprises the following steps: S41, using XGBoost algorithm to As stated in According to the keywords of the growth stage type of white shrimp, the number of breeding sampling points occupied by different types of white shrimp growth stages in the white shrimp breeding area is statistically processed, and a summary data set of the number of sampling points of white shrimp growth stages in the breeding area is generated ,in Indicates white shrimp Summary data on the number of sampling points for white shrimp growth stages in the aquaculture area corresponding to the growth stage types; The unit of is piece; S42, the As stated in The maximum number of sampling points in the white shrimp farming area Perform numerical quotient processing to generate a weighted data set of white shrimp growth stages in the breeding area ,in Indicates white shrimp Weight data of white shrimp growth stages in the farming area corresponding to the growth stage types; The value of .

6. The adaptive breeding management method of Penaeus vannamei in plateau saline-alkali water according to claim 5, characterized in that: The S5 comprises the following steps: S51. Establish weight threshold for judging the growth stage of white shrimp in the breeding area ,in The value of ; S52, the As stated in With the Compare the weight values ​​and search for the Not less than the The corresponding white shrimp growth stage text information, and the white shrimp growth stage judgment data of the breeding area is generated through data identification .

7. The adaptive breeding management method of Penaeus vannamei in plateau saline-alkali water according to claim 6, characterized in that: The S6 comprises the following steps: S61. Establish a data set of aquaculture strategies for white shrimp in plateau saline-alkali water bodies at different growth stages ,in Indicates white shrimp The data of culture strategies of white shrimp in plateau saline-alkali water bodies at different growth stages corresponding to the growth stage types; S62, using a unified cost search algorithm to With the As stated in Perform growth stage type character matching to search for the The corresponding , and generate the optimal white shrimp current growth stage plateau saline-alkali water culture strategy data through data identification .

8. The adaptive breeding management method of Penaeus vannamei in plateau saline-alkali water according to claim 7, characterized in that: The S7 comprises the following steps: S71, the Data identification processing was performed to construct the optimal evaluation data of the breeding strategy for white shrimp adaptability to plateau saline-alkali water bodies. ; S72, white shrimp farming management platform according to the The environmental management technical strategy information, feed management technical strategy information and disease management technical strategy information for the adaptive breeding of white shrimp in plateau saline-alkali waters, orderly control aquaculture equipment to perform the adaptive breeding management operations of white shrimp in plateau saline-alkali waters, wherein the aquaculture equipment includes feeding equipment, water quality regulating equipment, temperature regulating equipment, light regulating equipment and disinfection equipment.

9. An adaptive breeding management system for Penaeus vannamei in plateau saline-alkali waters, used to implement the adaptive breeding management method for Penaeus vannamei in plateau saline-alkali waters according to any one of claims 1 to 8, characterized in that: The system comprises a sampling point information acquisition module for a white shrimp breeding area, an adaptive breeding strategy evaluation module for a white shrimp breeding area, and an adaptive breeding management module for a white shrimp breeding area.

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