A life support system control method and transport ship

Abstract

The present invention discloses a life support system control method and a transport ship. The life support system control method includes: establishing an objective function of total benefit; establishing and initializing an optimization space, which includes a raccoon population and multiple preys. During initialization, the state information of the life support system and the optimal survival information of multiple fish species are obtained; in the exploration phase, the predation of individuals on prey is simulated to select the best individual in the optimization space; in the development phase, predators are randomly set in the optimization space; in the tracking phase, the best individual moves toward the prey at a certain speed while avoiding predators, iteratively updates the position of the individual until the optimal individual with the maximum total benefit is obtained, and the state information corresponding to the optimal individual is output as the optimal state information. The life support system is set in the transport ship, and the optimal state information is used as an indicator to adjust the life support system. The present invention has the characteristics of automation, low cost and easy operation.

Description

Technical Field

[0001] The invention relates to the field of live fish transportation, and in particular to a life support system control method and a transport ship. Background Art

[0002] As people's health awareness increases, the requirements for food safety and nutritional health are also getting higher and higher. During the long-distance transportation of fresh fish, it is easy to deteriorate due to improper preservation measures, which has a great impact on the nutrients, freshness, taste, etc. of the fish. Specifically, traditional live fish transportation usually involves transporting live fish in water tanks or water bags, but during transportation, live fish are easily squeezed, hit, and collided, resulting in damage to the fish body and increased mortality. At the same time, maintaining water quality and temperature is also a difficult problem. Most of them need to be achieved manually, which is not convenient for operation. It is difficult to keep the water in the water tank or water bag clean and stable. It is easily affected by factors such as temperature changes, insufficient oxygen supply, and water level fluctuations, resulting in water quality deterioration and affecting the survival of fish. In particular, deep-sea farmed fish usually come from deeper waters and have a strong adaptability to low-temperature environments. The water temperature is high in summer, exceeding the suitable survival range of fish, which can easily lead to physiological dysfunction of fish, slow growth, or even death, making the transportation of live fish more difficult. In addition, traditional live fish transportation requires specialized equipment and manpower, and is costly. The preparation of water tanks or water bags, maintenance of water quality, and the catching and processing of fish all require a lot of time and resources, increasing transportation costs. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to provide an automated, low-cost, easy-to-operate life support system control method and transport ship.

[0004] Technical solution: The life support system control method described in the present invention includes: establishing an objective function of total benefit; establishing and initializing an optimization space, wherein the optimization space includes a raccoon population and multiple prey, and the raccoon population includes multiple individuals; during initialization, obtaining the state information of the life support system and the best survival information of multiple fish, assigning multiple groups of the state information to individuals in turn, and assigning multiple best survival information to prey in turn; simulating the predation of individuals on prey to select the best individual in the exploration stage; randomly setting predators in the optimization space in the development stage; in the tracking stage, the best individual moves toward the prey at a certain speed while avoiding predators, iteratively updating the position of the individual until the best individual that maximizes the total benefit is obtained, and outputting the state information corresponding to the best individual as the optimal state information.

[0005] Furthermore, the status information includes water temperature, pH value, dissolved oxygen level, ammonia nitrogen concentration, average temperature, light intensity, and feed density in the breeding warehouse.

[0006] Furthermore, the optimal survival information includes optimal water temperature, optimal pH value, optimal dissolved oxygen level, optimal ammonia nitrogen concentration, optimal average temperature, optimal light intensity, and optimal feed density in the fish breeding warehouse.

[0007] Furthermore, the objective function formula of the total revenue is as follows:

[0008]

[0009] In the formula, S represents the total income of the breeding warehouse; T represents the total amount of fish in the breeding warehouse; C represents the survival rate of fish; P represents the seasonal selling price of fish; K1 to K n is the independent variable, K1 represents the water temperature in the breeding warehouse, K2 represents the pH value in the breeding warehouse, K3 represents the dissolved oxygen level, K4 represents the ammonia nitrogen concentration, K5 represents the average temperature in the breeding warehouse, K6 represents the light intensity, K7 represents the feed density, that is, the number of fish per unit volume, K8 represents the frequency of water quality testing in the breeding warehouse, ε represents the disturbance factor; β1 to β8 represent weight parameters.

[0010] Furthermore, the exploration phase includes the following process: in the optimization space, prey is scattered on the prey tree, and then randomly falls to the ground. When preying, some individuals climb up the tree to prey, and other individuals wait on the ground for the prey to fall before preying, and update the individual positions. When updating, the position with the maximum total benefit is retained, and the best individual is obtained after the update is completed;

[0011] The individuals climbing the tree update their positions as follows:

[0012]

[0013] In the formula, represents the position of the j-th dimension individual at time t+1; represents the position of the j-th dimension individual at time t; represents the position of the optimal individual; I represents a random integer;

[0014] Individuals on the ground update their positions using the following formula:

[0015]

[0016]

[0017] Where t is the current iteration number; lbi represents the lower bound of the j-th dimension variable; ub j represents the upper bound of the j-th dimension variable; fitness(·) calculates the fitness; r represents a random number between [0, 1]; I represents a random integer from the integer set {1, 2}; Indicates the new position of the prey after it hits the ground; Indicates the j-th dimension variable value of the i-th individual in the current iteration;

[0018] The best individual is determined by greedy selection using the following formula:

[0019]

[0020] In the formula, fitness represents the function for calculating fitness.

[0021] Furthermore, the development phase includes the following process: generating random positions near each best individual position as the position of the predator; randomly generating the position of the predator by the following formula:

[0022]

[0023]

[0024] In the formula, r represents a random number between [0, 1]; t represents the number of iterations, and T is the maximum number of iterations; It is the upper bound of the j-dimensional variable updated with the number of iterations; is the lower bound of the j-th dimension variable updated with the number of iterations; lb j Indicates the upper bound of the j-dimensional variable updated with the number of iterations; ub j Represents the lower bound of the j-th dimension variable updated with the number of iterations; represents the position of the j-th dimension individual at time t+1; Indicates; i represents the position of the j-th dimension individual at time t.

[0025] Furthermore, the tracking phase includes the following process: the best individual approaches the prey at a certain speed while avoiding the predator, and updates the position by the following formula:

[0026] v k，d (t) = v k，d (t-1)+r1·c1·[S best，d (t-1)-S k，d (t-1)]

[0027] In the formula, S b est，d (t-1) is the individual position with the maximum total benefit in the previous iteration; S k，d (t-1) is the individual position of the previous iteration; c1 is a constant; r1 is a random number between [0, 1]; v k，d (t) represents the speed at which the individual is tracking prey and avoiding predators at time t; v k，d (t-1) represents the speed of the individual chasing prey and avoiding predators at time t-1; S k，d(t-1) represents the individual position of the iterative return at the previous moment.

[0028] Furthermore, when the speed exceeds the maximum speed range, the best individual updates its position at the maximum speed using the following formula:

[0029] S k，d (t) = S k，d (t-1)+v k，d (t)

[0030] In the formula, S k，d (t) represents the individual position of the iterative benefit at time t; v k，d (t) represents the speed of the individual chasing and avoiding at time t.

[0031] The transport ship described in the present invention includes a monitoring system, a control system, a life support system, and a power system; the power system is used to provide energy for the transport ship; the life support system includes a breeding warehouse, a temperature control device, a bubble injection device, and a water purifier. Fish are placed in the breeding warehouse, the breeding warehouse is used to adjust the light intensity, the temperature control device is used to adjust the water temperature and the average air temperature, the bubble injection device is used to adjust the dissolved oxygen level, the water purifier is used to adjust the ammonia nitrogen concentration and the pH value, and the feeding device is used to adjust the feed density; the monitoring system includes a temperature sensor, a water quality detection sensor, a gas sensor, and a photon sensor, which are used to monitor the status information of the breeding warehouse in real time; in the control system, the status information is processed in real time based on the life support system control method to obtain the optimal status information, and the optimal status information is used as an indicator to adjust the life support system to maximize the total profit of the breeding warehouse.

[0032] Furthermore, the power system includes a photovoltaic power generation system and an energy storage and control system. The photovoltaic power generation system includes solar photovoltaic panels, inverters, and regulators; the energy storage and control system includes battery packs, converters, motors, and load controllers.

[0033] Beneficial effects: The present invention has the following significant effects: 1. The present invention improves the level of automation: The present invention improves the raccoon algorithm to form a raccoon optimization algorithm, and adjusts the life support system of live fish in real time based on the raccoon optimization algorithm, automatically adjusts the temperature, dissolved oxygen, feed, light intensity and water quality (including pH value and ammonia nitrogen concentration), and the transport ship for transporting live fish adopts fish breeding and transportation technology to accurately provide comfortable water quality environment, suitable transportation conditions and other living conditions, thereby reducing the stress and damage of live fish, improving the survival rate and quality of live fish, and helping to maintain the freshness and quality of fish; 2. Easy to operate: The present invention sets a breeding warehouse, temperature control equipment, bubble injection device, and water purifier in the life support system, and the fish are placed in the breeding warehouse. The breeding warehouse is used to adjust the light intensity, the temperature control equipment is used to adjust the water temperature and the average air temperature, the bubble injection device is used to adjust the dissolved oxygen level, the water purifier is used to adjust the ammonia nitrogen concentration and pH value, and the feeding device is used to adjust the feed density. The breeding is effectively controlled by designing the ventilation system The temperature, humidity and oxygen content in the warehouse are convenient for adjusting the health and survival status of the fish; and a monitoring system is set up, and each device in the monitoring system is convenient for detecting each indicator in the life support system, and the results are fed back in real time to obtain real-time optimal status information; in addition, since the present invention can basically be implemented through intelligent devices, remote monitoring and predictive maintenance can also be carried out. Through real-time sensor data and algorithm analysis, maintenance needs can be accurately predicted, potential problems can be dealt with in time, and suitable conditions for breeding warehouses can be created for different fish; 3. The cost of the present invention is low: the present invention establishes an objective function of total revenue, takes the maximum total revenue as the goal in the process of adjusting the life support system, combines the monitoring system and the life support system to improve the quality and economic value of the caught live fish, while reducing the economic cost in the transportation process, and improving the transportation efficiency and economic benefits of the transport ship; in addition, the present invention converts solar energy into electrical energy, reduces fuel costs, reduces environmental pollution, and reduces energy costs, thereby increasing the revenue of cargo ships. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A flow chart of the life support system control method proposed by the present invention;

[0035] Figure 2 This is a schematic diagram of the overall structure of the transport ship proposed by the present invention;

[0036] Figure 3 Schematic diagram of energy and data transmission of transport ship. DETAILED DESCRIPTION

[0037] The present invention is further explained below in conjunction with the accompanying drawings and specific implementation methods.

[0038] See also Figure 1As shown, the life support system control method described in the present invention includes: establishing an objective function of total benefit; establishing and initializing an optimization space, wherein the optimization space includes a raccoon population and multiple preys, and the raccoon population includes multiple individuals; simulating the predation of individuals on prey to select the best individual in the exploration phase; randomly setting predators in the optimization space in the development phase; in the tracking phase, the best individual moves toward the prey at a certain speed while avoiding predators, iteratively updating the position of the individual until the optimal individual with the maximum total benefit is obtained, and outputting the state information corresponding to the optimal individual as the optimal state information.

[0039] When initializing the optimization space, the state information of the life support system and the optimal survival information of various fish are obtained, and multiple groups of the state information are assigned to individuals in turn, and multiple optimal survival information are assigned to prey in turn. In this embodiment, the optimal survival information includes the optimal water temperature value, the optimal pH value, the optimal dissolved oxygen level, the optimal ammonia nitrogen concentration, the optimal average temperature, the optimal light intensity, and the optimal feed density in the fish breeding warehouse; the state information includes the water temperature value, pH value, dissolved oxygen level, ammonia nitrogen concentration, average temperature, light intensity, and feed density in the breeding warehouse.

[0040] Specifically, the objective function formula of total revenue is as follows:

[0041]

[0042] In the formula, S represents the total income of the breeding warehouse; T represents the total amount of fish in the breeding warehouse; C represents the survival rate of fish; P represents the seasonal selling price of fish; K1 to K n is the independent variable, K1 represents the water temperature in the breeding warehouse, K2 represents the pH value in the breeding warehouse, K3 represents the dissolved oxygen level, K4 represents the ammonia nitrogen concentration, K5 represents the average temperature in the breeding warehouse, K6 represents the light intensity, K7 represents the feed density, that is, the number of fish per unit volume, K8 represents the frequency of water quality testing in the breeding warehouse, ε represents the disturbance factor; β1 to β8 represent weight parameters.

[0043] During initialization, the following formula is used:

[0044] S i，j =lb j +r·(ub j -lb j ) (1)

[0045] In the formula, S i，j For individuals; lb j To find the optimal lower boundary, that is, the minimum return; ub j To find the upper boundary, that is, the highest return; r is a random number between [0, 1].

[0046] The exploration phase preliminarily calculates the control strategy with the greatest economic benefit. In the raccoon predation design, it is assumed that the position of the best member in the population is the position of the prey. The exploration phase includes the following processes: In the optimization space, the prey is scattered on the prey tree and then randomly falls to the ground. When preying, some individuals climb up the tree to prey, while others wait on the ground for the prey to fall before preying. The individual positions are updated, and the position with the greatest total benefit is retained during the update. After the update is completed, the best individual is obtained.

[0047] The individuals climbing the tree update their positions as follows:

[0048]

[0049] In the formula, represents the position of the j-th dimension individual at time t+1; represents the position of the j-th dimension individual at time t; represents the position of the optimal individual; I represents a random integer;

[0050] After the prey falls to the ground, it is placed at a random position in the search space. Based on this random position, the iguana (individual) on the ground moves in the search space, and the individual on the ground updates its position by the following formula:

[0051]

[0052]

[0053] Where t is the current iteration number; lb i represents the lower bound of the j-th dimension variable; ub j represents the upper bound of the j-th dimension variable; fitness(·) calculates the fitness; r represents a random number between [0, 1]; I represents a random integer from the integer set {1, 2}; Indicates the new position of the prey after it hits the ground; Indicates the j-th dimension variable value of the i-th individual in the current iteration.

[0054] The best individual is determined by greedy selection using the following formula:

[0055]

[0056] In the formula, fitness represents the function for calculating fitness.

[0057] The development phase is to select the optimal control strategy based on the environmental parameters: The second stage of the process of updating the raccoon's position in the search space is based on modeling the natural behavior of raccoons when encountering and escaping from predators. In order to simulate this behavior, random positions are generated near the location of each cargo ship's revenue. The development phase includes the following processes: Generate random positions near each optimal individual position as the predator's position; Randomly generate the predator's position through the following formula:

[0058]

[0059]

[0060] In the formula, r represents a random number between [0, 1]; t represents the number of iterations, and T is the maximum number of iterations; It is the upper bound of the j-dimensional variable updated with the number of iterations; is the lower bound of the j-th dimension variable updated with the number of iterations; lb j Indicates the upper bound of the j-dimensional variable updated with the number of iterations; ub j Represents the lower bound of the j-th dimension variable updated with the number of iterations; represents the position of the j-th dimension individual at time t+1; Represents the position of the j-th dimension individual at time t.

[0061] If the updated cargo ship revenue and survival rate are optimal, the current individual is updated, otherwise it remains the same, and the best individual is determined by greedy selection using the following formula:

[0062]

[0063] In the formula, fitness represents the function for calculating fitness.

[0064] The tracking phase is to find the control strategy with the greatest economic benefits under the changing environment: move according to the speed in each dimension, and update the speed of each dimension of the current iteration according to the following formula for each cargo ship revenue value and live fish survival rate value. The tracking phase includes the following process: the best individual approaches the prey at a certain speed while avoiding predators, and updates the position according to the following formula:

[0065] v k，d (t) = v k，d (t-1)+r1·c1·[S best，d (t-1)-S k，d (t-1)] (9)

[0066] In the formula, S best，d (t-1) is the individual position with the maximum total benefit in the previous iteration; S k，d(t-1) is the individual position of the previous iteration; c1 is a constant; r1 is a random number between [0, 1]; v k，d (t) represents the speed at which the individual is tracking prey and avoiding predators at time t; v k，d (t-1) represents the speed of the individual chasing prey and avoiding predators at time t-1; S k，d (t-1) represents the individual position of the iterative return at the previous moment.

[0067] Then determine whether the speed is within the maximum speed range. If it exceeds the boundary, take the boundary value. When the speed exceeds the maximum speed range, the best individual updates its position at the maximum speed using the following formula:

[0068] S k,d (t) = S k,d (t-1)+v k,d (t) (10)

[0069] In the formula, S k,d (t) represents the individual position of the iterative benefit at time t; v k,d (t) represents the speed of the individual chasing and avoiding at time t.

[0070] The above process is iterated until the optimal individual is obtained. The optimal individual position finally obtained is the best control strategy that can obtain the highest benefit under the premise of energy conservation and emission reduction. Under the state information constraint conditions corresponding to the optimal individual, the survival rate of live fish is the highest and the profit of the cargo ship reaches the maximum. After that, the control system adjusts the various devices of the life support system according to the optimal state information. For example, the breeding warehouse is adjusted to change the light intensity, the temperature control equipment is adjusted to change the water temperature and average air temperature, the bubble injection device is adjusted to change the dissolved oxygen level, the water purifier is adjusted to change the ammonia nitrogen concentration and pH value, and the feeding device is adjusted to change the feed density.

[0071] See also Figures 2 to 3 The transport ship of the present invention comprises a monitoring system, a control system, a life support system and a power system; the power system is used to provide energy for the transport ship; the life support system comprises a breeding warehouse, a temperature control device, a bubble injection device and a water purifier, the fish are placed in the breeding warehouse, the breeding warehouse is used to adjust the light intensity, the temperature control device is used to adjust the water temperature and the average air temperature, the bubble injection device is used to adjust the dissolved oxygen level, the water purifier is used to adjust the ammonia nitrogen concentration and the pH value, and the feeding device is used to adjust the feed density; the monitoring system comprises a temperature sensor, a water quality detection sensor, a gas sensor and a photon sensor, which are used to monitor the status information of the breeding warehouse in real time; in the control system, the status information is processed in real time based on the life support system control method to obtain the optimal status information, and the optimal status information is used as an indicator to adjust the life support system to maximize the total profit of the breeding warehouse.

[0072] Among them, see Figure 3 , solid arrows represent energy transmission, dotted arrows represent data transmission, and horizontal lines represent DC busbars. The power system includes a photovoltaic power generation system and an energy storage and control system. The photovoltaic power generation system includes a solar photovoltaic panel, an inverter, and a regulator; the energy storage and control system includes a battery pack, a converter, an electric motor, and a load controller. The photovoltaic power generation system converts solar energy into electrical energy, reduces environmental pollution, reduces energy costs, and thus increases the revenue of cargo ships. Specifically, solar photovoltaic panels are usually located at appropriate positions on the hull to collect solar energy and convert it into electrical energy, and transfer excess electrical energy to the energy storage and control system, providing a clean and renewable energy source for ships, helping to drive various equipment and systems on transport ships, especially for key systems that keep live fish alive. In the energy storage and control system, the battery pack is used to store electrical energy, the converter is used to realize the conversion and distribution of electrical energy, the motor is used to adjust the output power of the battery pack, and the load controller can effectively distribute and manage electrical energy according to the load conditions of the ship. The status information of the transport ship is obtained through real-time detection by the monitoring system. The monitoring system includes temperature sensors, water quality detection sensors, gas sensors, and photon sensors. The temperature sensor is used to monitor the water temperature and average air temperature in the breeding warehouse. The water quality sensor is used to monitor the pH value, ammonia nitrogen concentration, and feed density in the breeding water. The gas sensor is used to monitor the dissolved oxygen level in the breeding water. The photon sensor is used to detect the light intensity. Each sensor works independently and provides real-time feedback to the control system to ensure the health and safety of the fish. In addition, the water purifier can also be used to filter and remove suspended matter, impurities, and harmful substances in the water; the automated feeding device is used to provide accurate and timely feed supply to ensure that the nutritional needs of fish are met during transportation.

[0073] The ship combines the improved raccoon algorithm to improve the total revenue of the cargo ship, and searches for the optimal solution with the highest total revenue under the premise of energy saving and emission reduction. Here, raccoon represents the operating status information of the transport ship, and prey represents the optimal survival information of various fish. In the control system, the status information is processed in real time based on the life support system control method, and the optimal status information is obtained by combining the optimal survival information. The control system adjusts each device of the life support system accordingly based on the obtained optimal status information.

Claims

1. A life support system control method, characterized in that: The life support system control method comprises: Establish an objective function of total revenue; the objective function formula of total revenue is as follows: In the formula, S represents the total income of the breeding warehouse; T represents the total amount of fish in the breeding warehouse; C represents the survival rate of fish; P represents the seasonal selling price of fish; K1 to K n is the independent variable, K1 represents the water temperature in the breeding warehouse, K2 represents the pH value in the breeding warehouse, K3 represents the dissolved oxygen level, K4 represents the ammonia nitrogen concentration, K5 represents the average temperature in the breeding warehouse, K6 represents the light intensity, K7 represents the feed density, that is, the number of fish per unit volume, K8 represents the frequency of water quality testing in the breeding warehouse, ε represents the disturbance factor; β1 to β8 represent weight parameters; Establish and initialize an optimization space, wherein the optimization space includes a raccoon population and multiple prey, wherein the raccoon population includes multiple individuals; during initialization, obtain state information of a life support system and optimal survival information of multiple fish species, assign multiple groups of the state information to individuals in sequence, and assign multiple optimal survival information to prey species in sequence; wherein the state information includes water temperature, pH value, dissolved oxygen level, ammonia nitrogen concentration, average air temperature, light intensity, and feed density in a breeding warehouse; and the optimal survival information includes optimal water temperature, optimal pH value, optimal dissolved oxygen level, optimal ammonia nitrogen concentration, optimal average air temperature, optimal light intensity, and optimal feed density in a fish breeding warehouse; In the exploration phase, the best individual is selected by simulating the predation of the individual on the prey; in the development phase, the predator is randomly set in the optimization space; in the tracking phase, the best individual moves towards the prey at a certain speed while avoiding the predator, and the position of the individual is iteratively updated until the best individual that maximizes the total benefit is obtained, and the state information corresponding to the best individual is output as the optimal state information; The exploration phase includes the following process: in the optimization space, prey is scattered on the prey tree and then randomly falls to the ground. When preying, some individuals climb up the tree to prey, and other individuals wait on the ground for the prey to fall before preying, and update the individual positions. When updating, the position with the largest total benefit is retained, and the best individual is obtained after the update is completed; The individuals climbing the tree update their positions as follows: In the formula, represents the position of the j-th dimension individual at time t+1; represents the position of the j-th dimension individual at time t; represents the position of the optimal individual; I represents a random integer; Individuals on the ground update their positions using the following formula: Where t is the current iteration number; lb i represents the lower bound of the j-th dimension variable; ub j represents the upper bound of the j-th dimension variable; fitness(·) calculates the fitness; r represents a random number between [0,1]; I represents a random integer from the integer set {1,2}; Indicates the new position of the prey after it hits the ground; Indicates the j-th dimension variable value of the i-th individual in the current iteration; The best individual is determined by greedy selection using the following formula: In the formula, fitness represents the function for calculating fitness; The development phase includes the following process: generating random positions near each best individual position as the position of the predator; randomly generating the position of the predator by the following formula: In the formula, r represents a random number between [0,1]; t represents the number of iterations, and T is the maximum number of iterations; It is the upper bound of the j-dimensional variable updated with the number of iterations; is the lower bound of the j-th dimension variable updated with the number of iterations; lb j Indicates the upper bound of the j-dimensional variable updated with the number of iterations; ub j Represents the lower bound of the j-th dimension variable updated with the number of iterations; represents the position of the j-th dimension individual at time t+1; Indicates; i represents the position of the j-th dimension individual at time t.

2. The life support system control method according to claim 1, characterized in that: The tracking phase includes the following process: the best individual approaches the prey at a certain speed while avoiding the predator, and updates the position by the following formula: v k,d (t)=v k,d (t-1)+r1·c1·[S best,d (t-1)-S k,d (t-1)] In the formula, S best,d (t-1) is the individual position with the maximum total benefit in the previous iteration; S k,d (t-1) is the individual position of the previous iteration; c1 is a constant; r1 is a random number between [0,1]; v k,d (t) represents the speed at which the individual is tracking prey and avoiding predators at time t; v k,d (t-1) represents the speed of the individual chasing prey and avoiding predators at time t-1; S k,d (t-1) represents the individual position of the iterative return at the previous moment.

3. The life support system control method according to claim 2, characterized in that: When the speed exceeds the maximum speed range, the best individual updates its position at the maximum speed using the following formula: S k,d (t)=S k,d (t-1)+v k,d (t) In the formula, S k,d (t) represents the individual position of the iterative benefit at time t; v k,d (t) represents the speed of the individual chasing and avoiding at time t.

4. A transport ship using the life support system control method according to any one of claims 1 to 3, characterized in that: The transport ship includes a monitoring system, a control system, a life support system, and a power system; The power system is used to provide energy for the transport ship; the life support system includes a breeding warehouse, a temperature control device, a bubble injection device, and a water purifier. The fish are placed in the breeding warehouse, the breeding warehouse is used to adjust the light intensity, the temperature control device is used to adjust the water temperature and the average air temperature, the bubble injection device is used to adjust the dissolved oxygen level, the water purifier is used to adjust the ammonia nitrogen concentration and the pH value, and the feeding device is used to adjust the feed density; The monitoring system includes a temperature sensor, a water quality detection sensor, a gas sensor, and a photon sensor, which are used to monitor the status information of the breeding warehouse in real time; in the control system, the status information is processed in real time based on the life support system control method to obtain the optimal status information, and the optimal status information is used as an indicator to adjust the life support system to maximize the total profit of the breeding warehouse.

5. The transport ship according to claim 4, characterized in that: The power system includes a photovoltaic power generation system and an energy storage and control system. The photovoltaic power generation system includes a solar photovoltaic panel, an inverter, and a regulator; the energy storage and control system includes a battery pack, a converter, an electric motor, and a load controller.

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