Method and system for debugging man-machine interaction equipment for nuclear power simulation and storage medium

Abstract

The invention relates to a man-machine interaction equipment debugging method and system for nuclear power simulation and a storage medium, and the method comprises the steps: K1, connecting a nuclear power simulation system with man-machine interaction equipment, and collecting data information of man-machine interaction state parameters, data information of conversion parameters of the user instruction and data information of feedback parameters of the nuclear power simulation system are obtained in real time; and K2, on the basis of the data information of the conversion parameters of the user instruction and the data information of the feedback parameters of the nuclear power simulation system, representing the matching degree of the interaction parameters of the user and the nuclear power simulation system by adopting a man-machine interaction matching degree detection algorithm based on a kendall rank correlation coefficient, and obtaining data information of the matching degree of the interaction parameters of the user and the nuclear power simulation system. According to the method, the corresponding data can be quickly queried according to the conversion parameters of the instructions of the user, and the conversion parameters of the instructions of the user can be optimized, so that the query accuracy is improved, and the user can conveniently obtain the data.

Description

Technical Field

[0001] The present invention relates to the technical field of human-computer interaction devices, and in particular to a debugging method, system and storage medium for a human-computer interaction device for nuclear power simulation. Background Art

[0002] Nuclear power simulation is to establish a "virtual nuclear power plant" by simulation methods. During the simulation process, a large amount of data will flow, and content in different parts will be queried and retrieved. Or data anomalies occur during the simulation process. Facing the huge amount of data, if manual investigation is carried out, it will definitely take a lot of time and delay the progress of the project. Therefore, how to achieve fast human-computer interaction has become an urgent problem for us to solve. Summary of the Invention

[0003] In view of the above problems, the present invention provides a debugging method, system and storage medium for a human-computer interaction device for nuclear power simulation, which can not only quickly query corresponding data according to the conversion parameters of the user's instructions, but also optimize the conversion parameters of the user's instructions, thereby improving the query accuracy and facilitating the user to obtain data.

[0004] To achieve the above object and other related objects, the technical solution provided by the present invention is as follows: A debugging method for a human-computer interaction device for nuclear power simulation, the method includes:

[0005] K1. Connect the nuclear power simulation system with the human-computer interaction device, collect the data information of the state parameters of the human-computer interaction, and obtain in real time the data information of the conversion parameters of the user's instructions and the data information of the feedback parameters of the nuclear power simulation system;

[0006] K2. Based on the data information of the conversion parameters of the user's instructions and the data information of the feedback parameters of the nuclear power simulation system, use the human-computer interaction matching degree detection algorithm based on the kendall rank correlation coefficient to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, and obtain the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system;

[0007] K3. Based on the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system and the data information of the state parameters of the human-computer interaction, construct a human-computer interaction satisfaction function F, calculate the satisfaction of the human-computer interaction, and obtain the data information of the satisfaction of the human-computer interaction;

[0008] K4. Based on the data information of the satisfaction of the human-computer interaction, set a preset threshold. If the satisfaction of the human-computer interaction is greater than the preset threshold, the human-computer interaction device does not need to be debugged. If the satisfaction of the human-computer interaction is less than the preset threshold, use the improved salp swarm optimization algorithm based on dynamic learning to optimize the conversion parameters of the user's instructions, and obtain the data information of the optimized conversion parameters of the user's instructions.

[0009] Further, in step K2, the characterization of the matching degree of the interaction parameters between the user and the nuclear power simulation system by using the human-computer interaction matching degree detection algorithm based on the Kendall rank correlation coefficient includes:

[0010] K21. Based on the data information of the conversion parameters of the user instruction and the data information of the feedback parameters of the nuclear power simulation system, establish a Kendall rank correlation function Q of the user and the nuclear power simulation system,

[0011]

[0012] where x is the data information of the conversion parameters of the user instruction, y is the data information of the feedback parameters of the nuclear power simulation system, and β1, β2, and β3 are any constant coefficients between 0 and 1, which characterize the correlation between the conversion parameters of the user instruction and the feedback parameters of the nuclear power simulation system, and obtain the data information of the correlation between the conversion parameters of the user instruction and the feedback parameters of the nuclear power simulation system;

[0013] K22. Based on the data information of the correlation between the conversion parameters of the user instruction and the feedback parameters of the nuclear power simulation system, construct a human-computer interaction matching degree function W,

[0014]

[0015] where z is the data information of the correlation between the conversion parameters of the user instruction and the feedback parameters of the nuclear power simulation system, and α1, α2, and α3 are weight coefficients;

[0016] K23. Based on the human-computer interaction matching degree function W, characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, and obtain the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system.

[0017] Further, the constraint conditions for the weight coefficients α1, α2, and α3 are

[0018]

[0019] Further, the constraint function f for the constant coefficients β1, β2, and β3 is

[0020]

[0021] where the value range of the constraint function f is (1, 2).

[0022] Further, the human-computer interaction satisfaction function F is

[0023]

[0024] Among them, r1 is the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system, r2 is the data information of the state parameters of the human-computer interaction, and δ1, δ2, and δ3 are the difference factors of the human-computer interaction satisfaction degree.

[0025] Furthermore, the difference factors δ1, δ2, and δ3 of the human-computer interaction satisfaction degree are

[0026]

[0027] Among them, r1 is the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system, and r2 is the data information of the state parameters of the human-computer interaction.

[0028] Furthermore, in step K4, the optimization of the conversion parameters of the user instruction by using the improved salp swarm optimization algorithm based on dynamic learning includes:

[0029] K41. Based on the data information of the conversion parameters of the user instruction, initialize the salp population, determine the population parameters and the maximum number of iterations R, and obtain the data information of the initialized salp population;

[0030] K42. Based on the data information of the initialized salp population, establish the fitness function S of the population individuals

[0031]

[0032] Among them, h is the data information of the initialized salp population, and the fitness values of the population individuals are calculated to obtain the data information of the fitness values of the population individuals;

[0033] K43. Based on the data information of the fitness values of the population individuals, establish the objective function G based on the dynamic learning factor

[0034]

[0035] Among them, g is the data information of the fitness values of the population individuals, λ1, λ2, and λ3 are the dynamic learning factors, and the conversion parameters of the user instruction are optimized to obtain the data information of the optimized conversion parameters of the user instruction.

[0036] Furthermore, the dynamic learning factors λ1, λ2, and λ3 are

[0037]

[0038] Among them, g is the data information of the fitness values of the population individuals.

[0039] To achieve the above object and other related objects, the present invention also provides a debugging system for a human-computer interaction device for nuclear power simulation, including a computer device, which is programmed or configured to execute the steps of any one of the debugging methods for the human-computer interaction device for nuclear power simulation.

[0040] To achieve the above object and other related objects, the present invention also provides a computer-readable storage medium, on which a computer program is stored that is programmed or configured to execute the debugging method for the human-computer interaction device for nuclear power simulation described in any one of the above.

[0041] The present invention has the following positive effects:

[0042] 1. By adopting the human-computer interaction matching degree detection algorithm based on the Kendall rank correlation coefficient to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, and combining with the construction of the human-computer interaction satisfaction function F to calculate the satisfaction degree of the human-computer interaction, the present invention can not only accurately evaluate the satisfaction degree of the human-computer interaction according to the data information of the state parameters of the human-computer interaction, the data information of the conversion parameters of the user instructions, and the data information of the feedback parameters of the nuclear power simulation system, but also provide solid data support for the subsequent debugging of the artificial interaction device.

[0043] 2. By adopting the improved salp swarm optimization algorithm based on dynamic learning to optimize the conversion parameters of the user instructions, the present invention can not only quickly query the corresponding data according to the conversion parameters of the user instructions, but also optimize the conversion parameters of the user instructions, thereby improving the query accuracy and facilitating the user to obtain data. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a schematic flow chart of the method of the present invention;

[0045] Figure 2 is a schematic flow chart of the human-computer interaction matching degree detection algorithm based on the Kendall rank correlation coefficient of the present invention;

[0046] Figure 3 is a schematic flow chart of the improved salp swarm optimization algorithm based on dynamic learning of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0047] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to assist in understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted below.

[0048] Example 1: As Figure 1 shown, a debugging method for a human - machine interaction device for nuclear power simulation, the method includes:

[0049] K1. Connect the nuclear power simulation system to the human - machine interaction device, collect the data information of the state parameters of the human - machine interaction, and obtain in real - time the data information of the conversion parameters of the user instructions and the data information of the feedback parameters of the nuclear power simulation system;

[0050] K2. Based on the data information of the conversion parameters of the user instructions and the data information of the feedback parameters of the nuclear power simulation system, use the human - machine interaction matching degree detection algorithm based on the Kendall rank - correlation coefficient to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, and obtain the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system;

[0051] K3. Based on the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system and the data information of the state parameters of the human - machine interaction, construct a human - machine interaction satisfaction function F, calculate the satisfaction degree of the human - machine interaction, and obtain the data information of the satisfaction degree of the human - machine interaction;

[0052] K4. Based on the data information of the satisfaction degree of the human - machine interaction, set a preset threshold. If the satisfaction degree of the human - machine interaction is greater than the preset threshold, the human - machine interaction device does not need to be debugged. If the satisfaction degree of the human - machine interaction is less than the preset threshold, use the improved salp swarm optimization algorithm based on dynamic learning to optimize the conversion parameters of the user instructions, and obtain the data information of the optimized conversion parameters of the user instructions.

[0053] In this embodiment, as Figure 2 shown, in step K2, the use of the human - machine interaction matching degree detection algorithm based on the Kendall rank - correlation coefficient to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system includes:

[0054] K21. Based on the data information of the conversion parameters of the user instructions and the data information of the feedback parameters of the nuclear power simulation system, establish a Kendall rank - correlation function Q between the user and the nuclear power simulation system,

[0055]

[0056] where x is the data information of the conversion parameters of the user instructions, y is the data information of the feedback parameters of the nuclear power simulation system, and β1, β2, and β3 are respectively any constant coefficients between 0 and 1, to characterize the correlation between the conversion parameters of the user instructions and the feedback parameters of the nuclear power simulation system, and obtain the data information of the correlation between the conversion parameters of the user instructions and the feedback parameters of the nuclear power simulation system;

[0057] K22. Construct a human - machine interaction matching degree function \(W\) based on the data information of the correlation between the conversion parameters of the user instruction and the feedback parameters of the nuclear power simulation system.

[0058]

[0059] Where \(z\) is the data information of the correlation between the conversion parameters of the user instruction and the feedback parameters of the nuclear power simulation system, and \(\alpha_1\), \(\alpha_2\), and \(\alpha_3\) are weight coefficients.

[0060] K23. Characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system based on the human - machine interaction matching degree function \(W\), and obtain the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system.

[0061] In this embodiment, the constraint conditions for the weight coefficients \(\alpha_1\), \(\alpha_2\), and \(\alpha_3\) are

[0062]

[0063] In this embodiment, the constraint function \(f\) for the constant coefficients \(\beta_1\), \(\beta_2\), and \(\beta_3\) is

[0064]

[0065] Where the value range of the constraint function \(f\) is \((1, 2)\).

[0066] In this embodiment, the human - machine interaction satisfaction function \(F\) is

[0067]

[0068] Where \(r_1\) is the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system, \(r_2\) is the data information of the state parameters of the human - machine interaction, and \(\delta_1\), \(\delta_2\), and \(\delta_3\) are the differential factors of the human - machine interaction satisfaction.

[0069] In this embodiment, the differential factors \(\delta_1\), \(\delta_2\), and \(\delta_3\) of the human - machine interaction satisfaction are

[0070]

[0071] Where \(r_1\) is the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system, and \(r_2\) is the data information of the state parameters of the human - machine interaction.

[0072] In this embodiment, the Kendall rank correlation coefficient (R) refers to the coefficient for n statistical objects, each with two attributes. All statistical objects are arranged according to the values of attribute 1. Without loss of generality, assume that the arrangement of the values of attribute 2 is in a disordered order at this time. Let P be the number of pairs of statistical objects with consistent magnitude relationships in the arrangements of the two attribute values. The rank correlation coefficient, also known as the grade correlation coefficient, reflects the association between the directions and intensities of the changes of two random variables. It is a statistic obtained by arranging the sample values of the two random variables in the order of data magnitude and replacing the actual data with the ranks of the sample values of each element. It is a statistical analysis index reflecting the degree of rank correlation. Common rank correlation analysis methods include the Spearman correlation coefficient and the Kendall rank correlation coefficient, etc. It is mainly used for data analysis.

[0073] In this embodiment, by using a human-computer interaction matching degree detection algorithm based on the Kendall rank correlation coefficient to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, and combining the construction of the human-computer interaction satisfaction function F to calculate the satisfaction degree of human-computer interaction, it is not only possible to accurately evaluate the satisfaction degree of human-computer interaction based on the data information of the state parameters of human-computer interaction, the data information of the conversion parameters of user instructions, and the data information of the feedback parameters of the nuclear power simulation system, but also provide solid data support for the subsequent debugging of artificial interaction devices.

[0074] Embodiment 2: On the basis of a method for debugging a human-computer interaction device for nuclear power simulation in Embodiment 1, the present invention will be further described and explained below.

[0075] As Figure 1 shown, a method for debugging a human-computer interaction device for nuclear power simulation, the method includes:

[0076] K1. The nuclear power simulation system is connected to the human-computer interaction device, the data information of the state parameters of human-computer interaction is collected, and the data information of the conversion parameters of user instructions and the data information of the feedback parameters of the nuclear power simulation system are obtained in real time;

[0077] K2. Based on the data information of the conversion parameters of the user instructions and the data information of the feedback parameters of the nuclear power simulation system, a human-computer interaction matching degree detection algorithm based on the Kendall rank correlation coefficient is used to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, and the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system is obtained;

[0078] K3. Based on the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system and the data information of the state parameters of the human-computer interaction, construct a human-computer interaction satisfaction function F to calculate the satisfaction of the human-computer interaction and obtain the data information of the satisfaction of the human-computer interaction;

[0079] K4. Based on the data information of the satisfaction of the human-computer interaction, set a preset threshold. If the satisfaction of the human-computer interaction is greater than the preset threshold, the human-computer interaction device does not need to be debugged. If the satisfaction of the human-computer interaction is less than the preset threshold, use an improved salp swarm optimization algorithm based on dynamic learning to optimize the conversion parameters of the user instructions and obtain the data information of the optimized conversion parameters of the user instructions.

[0080] In this embodiment, as Figure 3 shown, in step K4, the use of an improved salp swarm optimization algorithm based on dynamic learning to optimize the conversion parameters of the user instructions includes:

[0081] K41. Based on the data information of the conversion parameters of the user instructions, initialize the salp population, determine the population parameters and the maximum number of iterations R, and obtain the data information of the initialized salp population;

[0082] K42. Based on the data information of the initialized salp population, establish a fitness function S for the population individuals,

[0083]

[0084] where h is the data information of the initialized salp population, calculate the fitness values of the population individuals, and obtain the data information of the fitness values of the population individuals;

[0085] K43. Based on the data information of the fitness values of the population individuals, establish an objective function G based on dynamic learning factors,

[0086]

[0087] where g is the data information of the fitness values of the population individuals, λ1, λ2, and λ3 are dynamic learning factors, optimize the conversion parameters of the user instructions, and obtain the data information of the optimized conversion parameters of the user instructions.

[0088] In this embodiment, the dynamic learning factors λ1, λ2, and λ3 are

[0089]

[0090]

[0091] where g is the data information of the fitness values of the population individuals.

[0092] In this embodiment, the present invention further provides a debugging system for a human-computer interaction device for nuclear power simulation, including a computer device, which is programmed or configured to execute the steps of the debugging method for a human-computer interaction device for nuclear power simulation described in any one of the above.

[0093] In this embodiment, the system includes:

[0094] A data acquisition module, configured to collect data information of the state parameters of human-computer interaction, and real-time obtain data information of the conversion parameters of user instructions and data information of the feedback parameters of the nuclear power simulation system;

[0095] A matching degree module for the interaction parameters between the user and the nuclear power simulation system, connected to the data acquisition module, and configured to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system by using a human-computer interaction matching degree detection algorithm based on the Kendall rank correlation coefficient, so as to obtain data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system;

[0096] A satisfaction evaluation module for human-computer interaction, connected to the matching degree module for the interaction parameters between the user and the nuclear power simulation system, and configured to construct a human-computer interaction satisfaction function F to calculate the satisfaction of human-computer interaction, so as to obtain data information of the satisfaction of human-computer interaction;

[0097] A debugging module for human-computer interaction, connected to the satisfaction evaluation module for human-computer interaction, and configured to set a preset threshold. If the satisfaction of human-computer interaction is greater than the preset threshold, the human-computer interaction device does not need to be debugged. If the satisfaction of human-computer interaction is less than the preset threshold, an improved salp swarm optimization algorithm based on dynamic learning is used to optimize the conversion parameters of user instructions, so as to obtain data information of the optimized conversion parameters of user instructions.

[0098] In this embodiment, the salp is a marine invertebrate with a barrel-shaped and almost completely transparent body. It feeds on phytoplankton in the water and moves in the water by inhaling and ejecting seawater. In the deep sea, salps move and forage in a chain-like group behavior, and this "peculiar" group behavior has attracted the interest of researchers. The chain-like group behavior of salps usually has individuals connected end to end to form a "chain" and move forward in sequence. In the salp chain, there are leaders and followers. The leaders move towards the food and guide the movement of the followers immediately behind them. The movement of the followers follows a strict "hierarchical" system and is only affected by the previous salp. Such a movement pattern enables the salp chain to have strong global exploration and local development capabilities.

[0099] In this embodiment, the present invention further provides a computer-readable storage medium, on which a computer program is stored that is programmed or configured to execute the nuclear power simulation human-computer interaction device debugging method described in any one of the above.

[0100] Any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0101] In summary, the present invention can not only quickly query the corresponding data according to the conversion parameters of the user's instruction, but also optimize the conversion parameters of the user's instruction, thereby improving the query accuracy and facilitating the user to obtain data.

[0102] The above specific embodiments do not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. A method for debugging a human-computer interaction device for nuclear power simulation, characterized in that: The method comprises: K1. The nuclear power simulation system is connected to the human-computer interaction device to collect data information of the state parameters of the human-computer interaction, and obtain data information of the conversion parameters of the user instructions and data information of the feedback parameters of the nuclear power simulation system in real time; K2. Based on the data information of the conversion parameters of the user instructions and the data information of the feedback parameters of the nuclear power simulation system, a human-computer interaction matching degree detection algorithm based on the kendall rank correlation coefficient is used to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, and obtain the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system; K3. Based on the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system and the data information of the state parameters of the human-computer interaction, a human-computer interaction satisfaction function F is constructed, and the satisfaction of the human-computer interaction is calculated to obtain data information of the satisfaction of the human-computer interaction; K4. Based on the data information of satisfaction with the human-computer interaction, a preset threshold is set. If the satisfaction with the human-computer interaction is greater than the preset threshold, the human-computer interaction device does not need to be debugged. If the satisfaction with the human-computer interaction is less than the preset threshold, an improved salp swarm optimization algorithm based on dynamic learning is used to optimize the conversion parameters of the user commands to obtain data information of the optimized conversion parameters of the user commands.

2. The method for debugging a human-computer interaction device for nuclear power simulation according to claim 1, characterized in that: In step K2, the human-computer interaction matching detection algorithm based on the kendall rank correlation coefficient is used to characterize the matching degree of the interaction parameters between the user and the nuclear power simulation system, including: K21. Based on the data information of the conversion parameters of the user instruction and the data information of the feedback parameters of the nuclear power simulation system, a kendall rank correlation function Q between the user and the nuclear power simulation system is established. Among them, x is the data information of the conversion parameter of the user instruction, y is the data information of the feedback parameter of the nuclear power simulation system, β1, β2 and β3 are any constant coefficients between 0 and 1, and the correlation between the conversion parameter of the user instruction and the feedback parameter of the nuclear power simulation system is characterized to obtain the data information of the correlation between the conversion parameter of the user instruction and the feedback parameter of the nuclear power simulation system; K22. Based on the data information of the correlation between the conversion parameters of the user instruction and the feedback parameters of the nuclear power simulation system, a human-computer interaction matching function W is constructed. Among them, z is the data information of the correlation between the conversion parameters of the user command and the feedback parameters of the nuclear power simulation system, and α1, α2 and α3 are weight coefficients; K23. Based on the human-computer interaction matching function W, the matching degree of the interaction parameters between the user and the nuclear power simulation system is characterized to obtain data information on the matching degree of the interaction parameters between the user and the nuclear power simulation system.

3. The method for debugging a human-computer interaction device for nuclear power simulation according to claim 2, characterized in that: The constraints of the weight coefficients α1, α2 and α3 are:

4. The method for debugging a human-computer interaction device for nuclear power simulation according to claim 2, characterized in that: The constraint function f of the constant coefficients β1, β2 and β3 is, The value range of the constraint function f is (1,2).

5. The method for debugging a human-computer interaction device for nuclear power simulation according to claim 1, characterized in that: The human-computer interaction satisfaction function F is: Among them, r1 is the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system, r2 is the data information of the state parameters of the human-computer interaction, and δ1, δ2 and δ3 are the differential factors of the satisfaction with the human-computer interaction.

6. The method for debugging a human-computer interaction device for nuclear power simulation according to claim 5, characterized in that: The difference factors δ1, δ2 and δ3 of the human-computer interaction satisfaction are: Among them, r1 is the data information of the matching degree of the interaction parameters between the user and the nuclear power simulation system, and r2 is the data information of the state parameters of the human-computer interaction.

7. The method for debugging a human-computer interaction device for nuclear power simulation according to claim 1, characterized in that: In step K4, the optimization of the conversion parameters of the user instructions by using the improved salp swarm optimization algorithm based on dynamic learning includes: K41. Based on the data information of the conversion parameters of the user instruction, the salp population is initialized, the population parameters and the maximum number of iterations R are determined, and the data information of the initialized salp population is obtained; K42. Based on the data information of the initialized Salp population, establish a fitness function S of the population individuals, Among them, h is the data information of the initialized salp population, and the fitness values ​​of the individuals in the population are calculated to obtain the data information of the fitness values ​​of the individuals in the population; K43. Based on the data information of the fitness values ​​of the individuals in the population, an objective function G based on a dynamic learning factor is established. Among them, g is the data information of the fitness value of the population individual, λ1, λ2 and λ3 are dynamic learning factors, and the conversion parameters of the user instructions are optimized to obtain the data information of the optimized conversion parameters of the user instructions.

8. The method for debugging a human-computer interaction device for nuclear power simulation according to claim 7, characterized in that: The dynamic learning factors λ1, λ2 and λ3 are, Among them, g is the data information of the fitness value of the individuals in the population.

9. A human-computer interaction device debugging system for nuclear power simulation, comprising a computer device, characterized in that: The computer device is programmed or configured to execute the steps of the method for debugging a human-computer interaction device for nuclear power simulation as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program programmed or configured to execute the method for debugging a human-computer interaction device for nuclear power simulation as described in any one of claims 1 to 8.

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