Transportation environment intelligent adjusting method and system for long-distance lateolabrax japonicus transportation

Abstract

The invention discloses a transportation environment intelligent adjusting method and system for long-distance lateolabrax japonicus transportation, and relates to the technical field of long-distance lateolabrax japonicus safe transportation. The method comprises the steps that lateolabrax japonicus transportation characteristics are constructed according to the estimated transportation duration, the average size of lateolabrax japonicus, the number of lateolabrax japonicus and the water temperature; constructing an anesthetic dosage recommendation model, importing the transport characteristics of lateolabrax japonicus into the trained anesthetic dosage recommendation model, obtaining the recommended anesthetic dosage for lateolabrax japonicus transport, anesthetizing to-be-transported lateolabrax japonicus, collecting the temperature, water quality and oxygen concentration of a transport water body in the transport process, and evaluating the activeness of lateolabrax japonicus bodies. And generating an adjustment gradient based on the activeness to dynamically adjust the transportation water body environment, and additionally setting an emergency and an emergency plan library to process the transportation emergency. By optimizing water quality management, improving an oxygen supply system and introducing an intelligent monitoring and regulating means, dynamic regulation and fine management in the whole transportation process are achieved, and health and survival of lateolabrax japonicus in the transportation process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of long-distance safe transportation of striped seabass, and more specifically, to an intelligent regulation method and system for a transportation environment for long-distance transportation of striped seabass. Background Art

[0002] In the construction of modern marine ranches, deep-sea farming of japonica seabass has become an important part of improving marine economic benefits and achieving sustainable development. However, as an aquaculture species with extremely high economic value, a key link in the production chain of japonica seabass is the safe transportation technology of live fish. The transportation of live fish not only involves the relay work from land to sea, but also serves as a bridge between farms and markets, which directly affects the success and efficiency of deep-sea farming. Live fish transportation technology is crucial for the sales of japonica seabass, especially fresh fish. The growing demand for fresh fish by consumers has put higher requirements on the safety and efficiency of the transportation process. Traditional transportation methods often have problems such as long transportation time, improper environmental control, and strong stress response of the fish body, resulting in high mortality during transportation, stagnant growth, and even affecting the quality of its meat. This not only causes economic losses, but also affects the stability of market supply.

[0003] The current live fish transportation technology needs to take into account water quality control, oxygen supply, temperature regulation, and transportation time to reduce the negative impact of transportation stress. At the same time, biosafety issues are becoming increasingly important, and the risk of pathogen transmission can be minimized through scientific transportation methods. With the development of science and technology, innovation and optimization of transportation modes, and the use of advanced transportation equipment and biotechnology have become the key to solving this problem. Therefore, efficient long-distance safe transportation technology for sea bass is needed, which can significantly improve the transportation survival rate and ensure the quality of the fish, thereby meeting the market demand for high-quality fresh sea bass. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes an intelligent adjustment method and system for the transportation environment for long-distance transport of sea bass, which utilizes comprehensive health management and treatment measures to optimize the cost and efficiency of transportation while ensuring the safety of fish during transportation.

[0005] A first aspect of the present invention provides a method for intelligently adjusting the transportation environment for long-distance transport of brown perch, comprising the following steps: Obtain destination information for the transshipment of striped sea bass, estimate the transshipment time based on the destination information, and construct transshipment characteristics of striped sea bass according to the estimated transshipment time, the average size of striped sea bass, the number of striped sea bass, and the water temperature; Constructing an anesthetic dosage recommendation model, using historical live fish transportation examples to train the model, importing the striped seabass transportation characteristics into the trained anesthetic dosage recommendation model, and obtaining the recommended anesthetic dosage for striped seabass transportation; Anesthetize the striped seabass to be transported according to the recommended usage of the anesthetic, collect the temperature, water quality and oxygen concentration of the transport water during transportation, evaluate the activity of the striped seabass, and generate an adjustment gradient based on the activity to dynamically adjust the transport water environment; By setting up an emergency event and emergency plan library, an emergency warning will be generated when an emergency event is detected, and the water environment adjustment equipment will be used to ensure the stability of the transportation water environment.

[0006] In this plan, the overall health and stress resistance of the japonica seabass are improved during the preparation stage before transportation, specifically: By adding multi-dimensional nutrition, bile acid and Clostridium butyricum to the feed of japonicus, the liver, gallbladder and intestinal health of japonicus are enhanced, and a large number of historical live fish transportation examples are retrieved and obtained. Multi-dimensional nutrition, bile acid and Clostridium butyricum are used as search keywords in the large number of historical live fish transportation examples to obtain examples that meet the search criteria and mark them; Obtaining average size and quantity information of the striped sea bass to be transported, performing similarity comparison in the marked instances according to the average size and quantity information, screening instances with a similarity greater than a preset threshold, determining the addition ratio of multidimensional nutrition, bile acid and Clostridium butyricum according to the screened instances, and performing feeding based on the addition ratio; In addition, the transported sea bass are disinfected for parasites, and virus and bacteria are sampled and tested and targeted for prevention and control to reduce the risk of pathogen infection during transportation and ensure the health of the sea bass before transportation.

[0007] In this scheme, an anesthetic dosage recommendation model is constructed, and the model is trained using historical live fish transportation examples. The transport characteristics of the striped sea bass are imported into the trained anesthetic dosage recommendation model to obtain the recommended anesthetic dosage for the transport of the striped sea bass, specifically: Initializing the anesthetic dosage recommendation model based on the LSTM network, using the improved sparrow algorithm to optimize the initial hidden layer node number and learning rate of the LSTM network, and taking the initial hidden layer node number and learning rate as optimization targets; Initialize the population and algorithm parameters of the sparrow algorithm, initialize the original population, calculate the fitness of individual sparrows, select the corresponding number of sparrow individuals as discoverers based on the fitness sorting and the proportion of discoverers, and the remaining sparrows as joiners to update their positions; Randomly select alerters from individual sparrows according to the alerter ratio, and update the position. Calculate and update the fitness of each individual sparrow. In the position update, introduce the golden sine algorithm to guide the individual sparrow to update to the new position. Update the optimal position of the sparrow through repeated iterations, and output the optimal parameters of the LSTM network. Extracting transportation characteristics based on the estimated transportation time, average fish size, number of live fish and water temperature in historical live fish transportation examples, matching the transportation characteristics with the anesthetic dosage in the examples to generate data samples, and dividing the data samples into a training set and a validation set; The anesthetic dosage recommendation model is configured using the optimal parameters of the LSTM network, and the training set is used to train the model, and a validation set is introduced to verify the predicted anesthetic dosage in the iteration process, and when the performance standard is met, the trained anesthetic dosage recommendation model is output; The transport characteristics of the striped seabass to be transported are imported into the trained anesthetic dosage recommendation model, the recommended anesthetic dosage for the transport of the striped seabass is predicted and output, and the recommended anesthetic dosage is used to completely anesthetize the striped seabass to be transported, thereby reducing the risk of physical stress and injury.

[0008] In this plan, the temperature, water quality and oxygen concentration of the transport water are collected during transportation to evaluate the activity of the sea bass. Specifically: In the actual transportation process, the multi-source water environment data of the transport water was obtained according to the temperature index, water quality index and oxygen concentration index, the activity was characterized by the metabolic rate and oxygen consumption of the sea bass, and the mutual information between different indicators and the mutual information between different indicators and the metabolic rate and oxygen consumption of the sea bass was calculated; Based on the mutual information, the mRMR algorithm is used to obtain the correlation of different indicators, the correlation is normalized to generate weight information of each indicator, the multi-source transport water environment data is decomposed by wavelet packets, and the scatter entropy of the reconstructed data of different indicators is calculated; The dispersion entropy is used as an indicator parameter of different indicators to characterize the non-stationary and nonlinear environmental change characteristics of the transport water body, a fuzzy comprehensive evaluation method is introduced, and a comprehensive evaluation level of the activity of the sea bass is preset; The membership of the index parameters of different indicators to each comprehensive evaluation level is judged according to the membership function to obtain a membership matrix, and the activity level of the sea bass body is obtained according to the membership matrix and weight information.

[0009] In this scheme, a regulation gradient is generated based on the activity to dynamically regulate the transport water environment, specifically: Obtaining the activity level sequence of the Lateolabrax body at each detection step during the Lateolabrax transportation process, extracting the activity level change cycle and change direction, determining the adjustment direction according to the change direction, presetting the activity change cycle threshold interval, and setting different adjustment gradients for different threshold intervals; Obtain the threshold interval that the activity level change cycle in the current detection step falls into to determine the corresponding adjustment gradient as the adjustment gradient of the water quality and oxygen concentration of the transport water body; Obtaining the influence coefficient of the external temperature on the transport water body according to the transport container for transporting the sea bass, compensating the adjustment gradient by the influence coefficient, and using the compensated adjustment gradient as the adjustment gradient of the transport water body temperature; According to the adjustment gradient of the water quality, oxygen concentration and temperature of the transport water body, the next activity level change cycle is predicted based on the activity level change cycle in the current detection step. When the next activity level change cycle is less than the preset time threshold, the transport water body environment is dynamically adjusted according to the adjustment gradient and adjustment direction.

[0010] In this solution, an emergency detection head is set up, and the emergency detection head is used to obtain the emergency events of the transport water body in real time. If the current multi-source transport water body environmental data is consistent with the emergency events and the historical emergency event data in the emergency plan library, an emergency warning is generated; According to the type of emergency, the corresponding emergency plan is obtained, and the corresponding water environment adjustment equipment in the emergency plan is extracted to optimize the water environment. Early warning monitoring is carried out within a preset time period to obtain the water environment parameter change sequence corresponding to the transport water body. The deviation from the preset standard is judged according to the water environment parameter change sequence. When the deviation gradually decreases and meets the preset standard, the emergency warning is cancelled. Otherwise, a higher level emergency warning is generated.

[0011] In this scheme, after the striped perch arrives at the transshipment destination, the mortality rate of the striped perch is statistically obtained. When the mortality rate is less than the preset mortality rate threshold, the striped perch transshipment characteristics and the dynamic adjustment data stream of the transport water environment of this striped perch transshipment are obtained and stored in a preset database; The water environment regulation scheme for subsequent sea bass transportation tasks is configured using the preset database, and the sea bass transportation characteristics of the sea bass transportation tasks are screened by similarity calculation in the preset database to screen the dynamic regulation data streams that meet the similarity standards; The deviations between the seabass transport task and the transport water temperature, water quality and oxygen concentration in the dynamic adjustment data stream are collected, and the recommended dosage of anesthetics and the water environment adjustment gradient in the dynamic adjustment data stream are adjusted according to the deviations to perform the initial configuration of the seabass transport task.

[0012] The second aspect of the present invention provides a transport environment intelligent regulation system for long-distance sea bass transportation, the system comprising a transport preparation module, a transport anesthetic dosage recommendation module, a sea bass body activity assessment module, a transport water body regulation module, and an emergency warning module; The transport preparation module obtains the estimated transport time, average size, number and water temperature of the transport water of the sea bass to be transported to construct the transport characteristics of the sea bass, and improves the overall health and stress resistance of the sea bass in the preparation stage before the transport of the sea bass; The transport anesthetic dosage recommendation module constructs an anesthetic dosage recommendation model, uses historical live fish transportation examples to train the model, imports the transport characteristics of the striped sea bass into the trained anesthetic dosage recommendation model, obtains the recommended anesthetic dosage for the transport of the striped sea bass, and anesthetizes the transported striped sea bass; The striped sea bass body activity evaluation module collects the temperature, water quality and oxygen concentration of the transport water during transportation, and introduces a fuzzy comprehensive evaluation method to evaluate the activity of the striped sea bass body; The transport water body regulation module generates a regulation gradient based on the activity level of the sea bass to dynamically regulate the transport water body environment; The emergency warning module is provided with an emergency and emergency plan library, and generates an emergency warning when an emergency is detected, and utilizes water environment adjustment equipment to ensure the stability of the transport water environment.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a safe transportation technology for sea bass that can effectively reduce mortality and loss rates under long-distance and high-temperature conditions. By optimizing water quality management, improving the oxygen supply system, and introducing intelligent monitoring and control methods, dynamic adjustment and fine management can be achieved throughout the transportation process to ensure the health and survival of sea bass during transportation, significantly improve transportation survival rate, ensure fish quality, and optimize transportation costs and efficiency, thereby meeting the market demand for high-quality fresh sea bass and providing technical support for the efficient operation of the industrial chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments or exemplary embodiments of the present invention, the drawings required for use in the embodiments or exemplary descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained according to the drawings without paying creative work.

[0015] Figure 1 A flow chart showing a method for intelligently regulating the transport environment for long-distance transport of Lateolabrax; Figure 2A flowchart of constructing an anesthetic dosage recommendation model to predict anesthetic dosage is shown; Figure 3 A flow chart showing the dynamic regulation of the transport water environment in an embodiment is shown; Figure 4 A block diagram of an intelligent regulation system for the transport environment for long-distance transshipment of brown sea bass is shown. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0017] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0018] Figure 1 A flow chart of the intelligent regulation method of the transport environment for long-distance transport of brown sea bass is shown.

[0019] like Figure 1 As shown, in the first embodiment of the present invention, a method for intelligently adjusting the transportation environment for long-distance transport of Lateolabrax japonicus is provided, comprising: S102, obtaining destination information of the japonica seabass transshipment, estimating the transshipment time based on the destination information, and constructing japonica seabass transshipment characteristics according to the estimated transshipment time, the average size of japonica seabass, the number of japonica seabass, and the water temperature; S104, constructing an anesthetic dosage recommendation model, using historical live fish transportation examples to train the model, importing the Lateolabrax transport characteristics into the trained anesthetic dosage recommendation model, and obtaining the recommended anesthetic dosage for Lateolabrax transport; S106, anesthetizing the striped seabass to be transported according to the recommended usage of the anesthetic, collecting the temperature, water quality and oxygen concentration of the transport water during transportation, evaluating the activity of the striped seabass, and generating an adjustment gradient based on the activity to dynamically adjust the transport water environment; S108, setting up an emergency event and emergency event plan library, generating an emergency warning when an emergency event is detected, and using water environment adjustment equipment to ensure the stability of the transportation water environment.

[0020] It should be noted that during the hot season, rising water temperatures cause the level of dissolved oxygen in the water to drop rapidly, and the striped seabass is prone to stress reactions due to lack of oxygen, which can lead to illness or directly cause death. In addition, high temperatures may also accelerate the decomposition of organic matter in the water and produce metabolites that are harmful to the fish, all of which increase the risk of transportation. Under long-term transportation conditions, traditional oxygen supplementation and temperature control technologies are often difficult to evenly and effectively maintain ideal water quality conditions, exacerbating transportation losses. Long-distance transportation often takes several hours or even longer, and deficiencies in water quality management and fish health monitoring in transport containers can easily lead to difficulties in timely adjustments once problems arise, resulting in losses. In addition, bumps and frequent environmental changes during transportation may cause stress reactions in the striped seabass, affecting its survival rate and meat quality.

[0021] Improve the overall health and stress resistance of the striped seabass in the preparation stage before transporting it, and ensure the safety and optimal health of the striped seabass during transportation. One week before salting, perform "liver, gallbladder and intestine" health care work, and enhance the liver, gallbladder and intestinal health of the striped seabass by adding multidimensional nutrition, bile acid and Clostridium butyricum to the feed of the striped seabass. The overall health level of the striped seabass has been significantly improved in the preparation stage for transporting the striped seabass, and it has been fully prepared for its rapid salting and entry into the sea. Retrieve a large number of historical live fish transportation examples, and use multidimensional nutrition, bile acid and Clostridium butyricum as search keywords in a large number of historical live fish transportation examples to obtain instances that meet the search criteria and mark them; obtain the average size and quantity information of the striped seabass to be transported, perform similarity comparison in the marked instances based on the average size and quantity information, screen instances that are greater than the preset similarity threshold, determine the addition ratio of multidimensional nutrition, bile acid and Clostridium butyricum based on the screened instances, and mix the feed for feeding based on the addition ratio.

[0022] To prevent and control pests and diseases, copper sulfate and ferrous sulfate in a ratio of 5:2 are used to disinfect parasites in transported seabass, and sampling and testing of viruses and bacteria are carried out as well as targeted prevention and control to reduce the risk of pathogen infection during transportation. Feeding is stopped 2 to 3 days before transportation to reduce the impact of excrement on water quality, thereby reducing the risk of water quality deterioration during transportation. At the same time, anti-stress drugs such as vitamin C are added daily, combined with pond bottom improvement and water purification measures, in order to reduce stress reactions caused by environmental changes and reduce mortality. Through the above-mentioned refined management measures, the seabass is ensured to be in the best health before transportation.

[0023] Figure 2 A flowchart for constructing an anesthetic dosage recommendation model to predict anesthetic dosage is shown.

[0024] According to an embodiment of the present invention, an anesthetic dosage recommendation model is constructed, and historical live fish transportation examples are used for model training. The transport characteristics of the striped sea bass are imported into the trained anesthetic dosage recommendation model to obtain the recommended anesthetic dosage for the transport of the striped sea bass, specifically: S202, initializing an anesthetic dosage recommendation model based on the LSTM network, optimizing the initial number of hidden layer nodes and learning rate of the LSTM network using an improved sparrow algorithm, and taking the initial number of hidden layer nodes and learning rate as optimization targets; S204, initializing the population and algorithm parameters of the sparrow algorithm, initializing the original population, calculating the fitness of the sparrow individuals, selecting a corresponding number of sparrow individuals as discoverers based on the fitness sorting and the proportion of discoverers, and the remaining sparrows as joiners, and updating the positions; S206, randomly selecting alerters from the individual sparrows according to the alerter ratio, and updating the position, calculating and updating the fitness of each individual sparrow, introducing the golden sine algorithm in the position update to guide the individual sparrow to update to the new position, updating the optimal position of the sparrow through repeated iterations, and outputting the optimal parameters of the LSTM network; S208, extracting transportation characteristics according to the estimated transportation time, average fish size, number of live fish and water temperature in the historical live fish transportation examples, matching the transportation characteristics with the anesthetic dosage in the examples to generate data samples, and dividing the data samples into a training set and a validation set; S210, configuring an anesthetic dosage recommendation model using the optimal parameters of the LSTM network, and using the training set to train the model, introducing a validation set to validate the predicted anesthetic dosage in the iteration process, and outputting the trained anesthetic dosage recommendation model when the performance standard is met; S212, importing the transport characteristics of the striped seabass to be transported into the trained anesthetic dosage recommendation model, predicting and outputting the recommended anesthetic dosage for the transport of the striped seabass, and using the recommended anesthetic dosage to completely anesthetize the striped seabass to be transported, thereby reducing the risk of physical stress and injury.

[0025] It should be noted that the LSTM network is specifically used to process and predict sequence data with long-term dependencies. In the LSTM network, each LSTM unit contains three gate structures: forget gate, input gate and output gate. The learned weights and activation functions determine whether to pass, discard or update information. The sparrow algorithm is used to search and optimize the optimal solution of the LSTM network parameters. The sparrow algorithm simulates the strategies of sparrows in foraging and anti-predation behaviors, and has global search capabilities and good stability and convergence accuracy. The sparrow algorithm simulates the behavioral strategies of sparrows in the process of finding food and escaping predators. It includes two parts: the foraging stage and the anti-predation stage. In the foraging stage, sparrows discover potential food sources by observing the surrounding environment and exchanging information with other sparrows, and choose appropriate paths for exploration. Each sparrow searches for the optimal solution by updating its position according to its individual position and speed. In the anti-predation stage, when sparrows encounter the threat of predators, they need to protect themselves through a fast escape strategy. Sparrows update their own positions according to their current positions and speeds to avoid predators and avoid falling into local optimal solutions. The golden sine algorithm is introduced into the sparrow algorithm to improve the global search capability and guide the individual sparrows to update their positions. The position update calculation process is: , in, , Indicates The sparrow individual is in sequence The iteration The position on the dimension, , Represents a random number, which determines the moving distance and direction of the individual sparrow. Indicates The global optimal position of the iteration is , Represents the position update parameter combined with the golden section coefficient, where the golden section coefficient is , by combining the position update parameters with the golden section coefficient, the search space is narrowed and the individual sparrows are guided to move to the optimal position.

[0026] During the process of catching the japonica seabass from the pond into the transport water truck and transferring them for stocking, they must be fully anesthetized to reduce the risk of physical stress and injury. The amount and time of anesthetics require that the transport characteristics of the japonica seabass to be transported be imported into the trained anesthetic dosage recommendation model to predict and output the recommended anesthetic dosage for japonica seabass transportation to ensure its safety and comfort throughout the operation.

[0027] It should be noted that in the actual transportation process, based on the real-time intelligent monitoring system, the multi-source transport water environment data of the transport water is obtained according to the temperature index, water quality index and oxygen concentration index. The monitoring system collects data in real time through the sensor network, and combines with the automatic water quality control equipment to realize the real-time monitoring and adjustment of key indicators such as water temperature, dissolved oxygen, pH value and ammonia nitrogen. The activity is characterized by the metabolic rate and oxygen consumption of the sea bass, and the mutual information between different indicators and the mutual information between different indicators and the metabolic rate and oxygen consumption of the sea bass are calculated; based on the mutual information, the mRMR algorithm is used to obtain the correlation of different indicators, and the correlation is normalized to generate the weight information of each indicator, and the multi-source transport water environment data is decomposed by wavelet packets, and the scatter entropy of the reconstructed data of different indicators is calculated; wavelet packets are suitable for processing non-stationary signals, and the scatter entropy can better extract nonlinear features. The two are combined to calculate the scatter entropy of the multi-source transport water environment data, and the scatter entropy is used as the indicator parameter of different indicators to characterize the non-stationary and nonlinear changes in the transport water environment of the transport water. Characteristics, introduce fuzzy comprehensive evaluation method, preset the comprehensive evaluation level of the activity of the striped sea bass; judge the membership of the indicator parameters of different indicators for each comprehensive evaluation level according to the membership function, and obtain the membership matrix. Commonly used membership functions include trapezoidal function, triangular function, etc. The membership of the indicator layer and the target layer is calculated by the membership and weight of the indicator of the next layer. For the activity levels of the striped sea bass: low activity, lower-middle activity, medium activity, upper-middle activity, and high activity, the memberships correspond to 60, 70, 80, 90, and 100 respectively. The membership of the evaluation indicator to the evaluation level is calculated, and the activity level of the striped sea bass is obtained according to the membership matrix and weight information.

[0028] Figure 3 A flow chart of dynamically adjusting the transport water environment according to an embodiment is shown.

[0029] According to an embodiment of the present invention, a regulation gradient is generated based on the activity to dynamically regulate the transport water environment, specifically: S302, obtaining the activity level sequence of the Lateolabrax body at each detection step during the Lateolabrax transportation process, extracting the activity level change cycle and change direction, determining the adjustment direction according to the change direction, presetting the activity level change cycle threshold interval, and setting different adjustment gradients for different threshold intervals; S304, obtaining the threshold interval into which the activity level change cycle in the current detection step falls and determining the corresponding adjustment gradient as the adjustment gradient of the water quality and oxygen concentration of the transport water body; S306, obtaining an influence coefficient of the external temperature on the transport water body according to the transport container for transporting the sea bass, compensating the adjustment gradient by the influence coefficient, and using the compensated adjustment gradient as the adjustment gradient of the transport water body temperature; S308, predicting the next activity level change cycle based on the activity level change cycle in the current detection step according to the adjustment gradient of the water quality, oxygen concentration and temperature of the transport water body; when the next activity level change cycle is less than the preset time threshold, dynamically adjusting the transport water body environment according to the adjustment gradient and adjustment direction.

[0030] It should be noted that the activity change cycle threshold interval is preset, and different adjustment gradients are set for different indicators in different threshold intervals, that is, the temperature index, water quality index and oxygen concentration index all correspond to different adjustment gradients. In the actual transportation process, in order to reduce the stress loss of the sea bass caused by temperature changes, a gradient cooling method is adopted, preferably cooling by about 2 degrees per hour to maintain the transportation water temperature at a low level, thereby reducing the metabolic rate and oxygen consumption of the fish body and reducing transportation losses. After arriving at the destination, the temperature difference between the transportation water body and the water body to be stocked is obtained, and based on the temperature difference, the water body to be stocked is gradually heated up to allow the sea bass to gradually adapt to the new water temperature conditions and reduce the stress response caused by the temperature difference.

[0031] In order to further improve the safety and efficiency of transportation, an emergency detection head is set according to the emergencies that may occur during transportation. The emergency detection head is used to obtain the emergencies of the transport water in real time. If the current multi-source transport water environment data meets the historical emergency data in the emergency plan library, an emergency warning is generated; the corresponding emergency plan is obtained according to the emergency category, and the corresponding water environment adjustment equipment in the emergency plan is extracted to optimize the water environment. For example, for possible oxygen shortage, spare oxygen cylinders and oxygenation equipment are equipped; for unexpected temperature changes, adjustable portable cooling or heating devices are prepared. Early warning monitoring is carried out within a preset time period to obtain the change sequence of water environment parameters corresponding to the transport water, and the deviation from the preset standard is judged according to the change sequence of water environment parameters. When the deviation gradually decreases and meets the preset standard, the emergency warning is cancelled, otherwise, a higher level emergency warning is generated. In addition, transportation personnel need to undergo professional training and master the biological characteristics of sea bass and stress response treatment measures to ensure that they can respond promptly and accurately when an emergency warning occurs.

[0032] After the striped seabass reaches the transshipment destination, the mortality rate of the striped seabass is statistically obtained. When the mortality rate is less than the preset mortality rate threshold, the striped seabass transshipment characteristics of this striped seabass transshipment and the dynamic adjustment data stream of the transport water environment are obtained and stored in a preset database; the preset database is used to configure the water environment adjustment plan for subsequent striped seabass transshipment tasks, and the striped seabass transshipment characteristics of the striped seabass transshipment tasks are screened by similarity calculation in the preset database, and the dynamic adjustment data stream that meets the similarity standard is screened; the deviation between the striped seabass transshipment task and the transport water temperature, water quality and oxygen concentration in the dynamic adjustment data stream is collected, and the recommended amount of anesthetics and the water environment adjustment gradient in the dynamic adjustment data stream are adjusted according to the deviation, and the initial configuration of the striped seabass transshipment task is performed.

[0033] Through a series of optimization measures, not only the survival rate of striped seabass during transportation is improved, the efficiency and safety of long-distance striped seabass transportation are significantly improved, and a solid foundation is provided for its subsequent growth and adaptation. The application of the present invention not only provides a scientific basis for breeding enterprises to reduce transportation costs and losses, but also provides strong support for the sustainable development of aquaculture. By living in harmony with the environment, the healthy growth of striped seabass and the stability of market supply are ensured, thereby further promoting the high-quality development of aquaculture.

[0034] Figure 4 A block diagram of the intelligent regulation system for the transport environment of sea bass for long-distance transport according to the present invention is shown.

[0035] In the second embodiment of the present invention, a transport environment intelligent regulation system 4 for long-distance transport of striped sea bass is provided, the system comprising a transport preparation module 401, a transport anesthetic dosage recommendation module 402, a striped sea bass body activity assessment module 403, a transport water body regulation module 404, and an emergency warning module 405; The transport preparation module obtains the estimated transport time, average size, number and water temperature of the transport water of the sea bass to be transported to construct the transport characteristics of the sea bass, and improves the overall health and stress resistance of the sea bass in the preparation stage before the transport of the sea bass; The transport anesthetic dosage recommendation module constructs an anesthetic dosage recommendation model, uses historical live fish transportation examples to train the model, imports the transport characteristics of the striped sea bass into the trained anesthetic dosage recommendation model, obtains the recommended anesthetic dosage for the transport of the striped sea bass, and anesthetizes the transported striped sea bass; The striped sea bass body activity evaluation module collects the temperature, water quality and oxygen concentration of the transport water during transportation, and introduces a fuzzy comprehensive evaluation method to evaluate the activity of the striped sea bass body; The transport water body regulation module generates a regulation gradient based on the activity level of the sea bass to dynamically regulate the transport water body environment; The emergency warning module is provided with an emergency and emergency plan library, and generates an emergency warning when an emergency is detected, and utilizes water environment adjustment equipment to ensure the stability of the transport water environment.

[0036] In the several embodiments provided in the present application, it should be understood that the disclosed method can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as: multiple modules or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or module can be electrical, mechanical or other forms. In addition, the functional modules in the various embodiments of the present invention can be all integrated into one processing module, or each module can be a separate module, or two or more modules can be integrated into one module; the above-mentioned integrated modules can be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0037] If the above-mentioned integrated module of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0038] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for intelligently regulating the transportation environment for long-distance transport of brown perch, characterized in that: The following steps are involved: Obtain destination information for the transshipment of striped sea bass, estimate the transshipment time based on the destination information, and construct transshipment characteristics of striped sea bass according to the estimated transshipment time, the average size of striped sea bass, the number of striped sea bass, and the water temperature; Constructing an anesthetic dosage recommendation model, using historical live fish transportation examples to train the model, importing the striped seabass transportation characteristics into the trained anesthetic dosage recommendation model, and obtaining the recommended anesthetic dosage for striped seabass transportation; Anesthetize the striped seabass to be transported according to the recommended usage of the anesthetic, collect the temperature, water quality and oxygen concentration of the transport water during transportation, evaluate the activity of the striped seabass, and generate an adjustment gradient based on the activity to dynamically adjust the transport water environment; Set up emergency events and emergency plan database, generate emergency warning when emergency events are detected, and use water environment adjustment equipment to ensure the stability of the transportation water environment; A recommended anesthetic dosage model was constructed, and historical live fish transportation examples were used for model training. The transport characteristics of the striped sea bass were imported into the trained anesthetic dosage recommendation model to obtain the recommended anesthetic dosage for the transport of the striped sea bass, specifically: Initializing the anesthetic dosage recommendation model based on the LSTM network, using the improved sparrow algorithm to optimize the initial hidden layer node number and learning rate of the LSTM network, and taking the initial hidden layer node number and learning rate as optimization targets; Initialize the population and algorithm parameters of the sparrow algorithm, initialize the original population, calculate the fitness of individual sparrows, select the corresponding number of sparrow individuals as discoverers based on the fitness sorting and the proportion of discoverers, and the remaining sparrows as joiners to update their positions; Randomly select alerters from individual sparrows according to the alerter ratio, and update the position. Calculate and update the fitness of each individual sparrow. In the position update, introduce the golden sine algorithm to guide the individual sparrow to update to the new position. Update the optimal position of the sparrow through repeated iterations, and output the optimal parameters of the LSTM network. Extracting transportation characteristics based on the estimated transportation time, average fish size, number of live fish and water temperature in historical live fish transportation examples, matching the transportation characteristics with the anesthetic dosage in the examples to generate data samples, and dividing the data samples into a training set and a validation set; The anesthetic dosage recommendation model is configured using the optimal parameters of the LSTM network, and the training set is used to train the model, and a validation set is introduced to verify the predicted anesthetic dosage in the iteration process, and when the performance standard is met, the trained anesthetic dosage recommendation model is output; The transport characteristics of the striped seabass to be transported are imported into the trained anesthetic dosage recommendation model, the recommended anesthetic dosage for the transport of the striped seabass is predicted and output, and the recommended anesthetic dosage is used to completely anesthetize the striped seabass to be transported, thereby reducing the risk of physical stress and injury.

2. The method for intelligently adjusting the transportation environment for long-distance transport of Lateolabrax japonicus according to claim 1, characterized in that: Improve the overall health and stress resistance of the sea bass during the preparation stage before transportation, specifically: By adding multi-dimensional nutrition, bile acid and Clostridium butyricum to the feed of japonicus, the liver, gallbladder and intestinal health of japonicus are enhanced, and a large number of historical live fish transportation examples are retrieved and obtained. Multi-dimensional nutrition, bile acid and Clostridium butyricum are used as search keywords in the large number of historical live fish transportation examples to obtain examples that meet the search criteria and mark them; Obtaining average size and quantity information of the striped sea bass to be transported, performing similarity comparison in the marked instances according to the average size and quantity information, screening instances with a similarity greater than a preset threshold, determining the addition ratio of multidimensional nutrition, bile acid and Clostridium butyricum according to the screened instances, and performing feeding based on the addition ratio; In addition, the transported sea bass are disinfected for parasites, and virus and bacteria are sampled and tested and targeted for prevention and control to reduce the risk of pathogen infection during transportation and ensure the health of the sea bass before transportation.

3. The method for intelligently adjusting the transportation environment for long-distance transport of Lateolabrax japonicus according to claim 1 is characterized in that: During transportation, the water temperature, water quality and oxygen concentration were collected to assess the activity of the sea bass. Specifically: In the actual transportation process, the multi-source water environment data of the transport water was obtained according to the temperature index, water quality index and oxygen concentration index, the activity was characterized by the metabolic rate and oxygen consumption of the sea bass, and the mutual information between different indicators and the mutual information between different indicators and the metabolic rate and oxygen consumption of the sea bass was calculated; Based on the mutual information, the mRMR algorithm is used to obtain the correlation of different indicators, the correlation is normalized to generate weight information of each indicator, the multi-source transport water environment data is decomposed by wavelet packets, and the scatter entropy of the reconstructed data of different indicators is calculated; The dispersion entropy is used as an indicator parameter of different indicators to characterize the non-stationary and nonlinear environmental change characteristics of the transport water body, a fuzzy comprehensive evaluation method is introduced, and a comprehensive evaluation level of the activity of the sea bass is preset; The membership of the index parameters of different indicators to each comprehensive evaluation level is judged according to the membership function to obtain a membership matrix, and the activity level of the sea bass body is obtained according to the membership matrix and weight information.

4. The method for intelligently adjusting the transportation environment for long-distance transport of Lateolabrax japonicus according to claim 1 is characterized in that: Based on the activity, a regulation gradient is generated to dynamically regulate the transport water environment, specifically: Obtaining the activity level sequence of the Lateolabrax body at each detection step during the Lateolabrax transportation process, extracting the activity level change cycle and change direction, determining the adjustment direction according to the change direction, presetting the activity change cycle threshold interval, and setting different adjustment gradients for different threshold intervals; Obtain the threshold interval that the activity level change cycle in the current detection step falls into to determine the corresponding adjustment gradient as the adjustment gradient of the water quality and oxygen concentration of the transport water body; Obtaining the influence coefficient of the external temperature on the transport water body according to the transport container for transporting the sea bass, compensating the adjustment gradient by the influence coefficient, and using the compensated adjustment gradient as the adjustment gradient of the transport water body temperature; According to the adjustment gradient of the water quality, oxygen concentration and temperature of the transport water body, the next activity level change cycle is predicted based on the activity level change cycle in the current detection step. When the next activity level change cycle is less than the preset time threshold, the transport water body environment is dynamically adjusted according to the adjustment gradient and adjustment direction.

5. The method for intelligently adjusting the transportation environment for long-distance transport of Lateolabrax japonicus according to claim 1, characterized in that: An emergency detection head is set up, and the emergency detection head is used to obtain emergency events of the transport water body in real time. If the current multi-source transport water body environmental data is consistent with the emergency events and the historical emergency event data in the emergency plan library, an emergency warning is generated; According to the type of emergency, the corresponding emergency plan is obtained, and the corresponding water environment adjustment equipment in the emergency plan is extracted to optimize the water environment. Early warning monitoring is carried out within a preset time period to obtain the water environment parameter change sequence corresponding to the transport water body. The deviation from the preset standard is judged according to the water environment parameter change sequence. When the deviation gradually decreases and meets the preset standard, the emergency warning is cancelled. Otherwise, a higher level emergency warning is generated.

6. The method for intelligently adjusting the transportation environment for long-distance transport of Lateolabrax japonicus according to claim 1, characterized in that: After the striped perch arrives at the transshipment destination, the mortality rate of the striped perch is statistically obtained. When the mortality rate is less than a preset mortality rate threshold, the striped perch transshipment characteristics and the dynamic adjustment data stream of the transport water environment of the striped perch transshipment are obtained and stored in a preset database; The water environment regulation scheme for subsequent sea bass transportation tasks is configured using the preset database, and the sea bass transportation characteristics of the sea bass transportation tasks are screened by similarity calculation in the preset database to screen the dynamic regulation data streams that meet the similarity standards; The deviations between the seabass transport task and the transport water temperature, water quality and oxygen concentration in the dynamic adjustment data stream are collected, and the recommended dosage of anesthetics and the water environment adjustment gradient in the dynamic adjustment data stream are adjusted according to the deviations to perform the initial configuration of the seabass transport task.

7. An intelligent transport environment adjustment system for long-distance transport of Lateolabrax japonicus, characterized in that: Implementing the intelligent adjustment method of the transportation environment for long-distance sea bass transportation as described in any one of claims 1 to 6, the system includes a transportation preparation module, a transportation anesthetic dosage recommendation module, a sea bass body activity assessment module, a transportation water body adjustment module, and an emergency warning module; The transport preparation module obtains the estimated transport time, average size, number and water temperature of the transport water of the sea bass to be transported to construct the transport characteristics of the sea bass, and improves the overall health and stress resistance of the sea bass in the preparation stage before the transport of the sea bass; The transport anesthetic dosage recommendation module constructs an anesthetic dosage recommendation model, uses historical live fish transportation examples to train the model, imports the transport characteristics of the striped sea bass into the trained anesthetic dosage recommendation model, obtains the recommended anesthetic dosage for the transport of the striped sea bass, and anesthetizes the transported striped sea bass; The striped sea bass body activity evaluation module collects the temperature, water quality and oxygen concentration of the transport water during transportation, and introduces a fuzzy comprehensive evaluation method to evaluate the activity of the striped sea bass body; The transport water body regulation module generates a regulation gradient based on the activity level of the sea bass to dynamically regulate the transport water body environment; The emergency warning module is provided with an emergency and emergency plan library, and generates an emergency warning when an emergency is detected, and utilizes water environment adjustment equipment to ensure the stability of the transport water environment.

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