Data processing method and device for dynamically adjusting step length

Abstract

The invention discloses a data processing method and device for dynamically adjusting step length. The method comprises the following steps: acquiring simulation parameter information; analyzing and processing the simulation parameter information to obtain target simulation state value information; the target simulation state value information comprises target displacement state value information, target speed state value information and target acceleration state value information; and analyzing and judging the target simulation state value information to obtain target simulation result information. The data processing method for step length dynamic adjustment disclosed by the invention is beneficial to realizing step length dynamic adjustment with low calculation overhead and improving the overall performance of a simulation system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of simulation technology, and in particular to a data processing method and device for step length dynamic adjustment. BACKGROUND

[0002] In the field of simulation data processing, step length parameters (such as learning rate in machine learning, adaptive filter step length in signal processing, and iteration step length in numerical optimization) directly affect the convergence speed and stability of the algorithm. Traditional methods mostly use fixed step length or dynamic adjustment strategies based on simple rules (such as exponential decay, error threshold triggering, etc.), which have the problem of being difficult to balance convergence speed and stability, with too large step length leading to oscillation divergence and too small step length leading to slow convergence. Some adaptive algorithms require real-time calculation of second-order derivatives or matrix inverse operations, which are difficult to deploy on resource-constrained devices. SUMMARY

[0003] The technical problem to be solved by the present application is to provide a data processing method and device for step length dynamic adjustment, which can realize low-computational-overhead step length dynamic adjustment and improve the overall performance of the simulation system.

[0004] To solve the above technical problems, the first aspect of the present application discloses a data processing method for step length dynamic adjustment, the method comprising:

[0005] obtaining simulation parameter information; the simulation parameter information includes basic simulation parameter information obtained by interacting with a user, and simulation object parameter information; the simulation object parameter information includes first object displacement information, first object velocity information, and first object acceleration information;

[0006] analyzing and processing the simulation parameter information to obtain target simulation state value information; the target simulation state value information includes target displacement state value information, target velocity state value information, and target acceleration state value information;

[0007] analyzing and judging the target simulation state value information to obtain target simulation result information.

[0008] The second aspect of the present application discloses a data processing device for step length dynamic adjustment, the device comprising:

[0009] an obtaining module for obtaining simulation parameter information; the simulation parameter information includes basic simulation parameter information obtained by interacting with a user, and simulation object parameter information; the simulation object parameter information includes first object displacement information, first object velocity information, and first object acceleration information;

[0010] The first processing module is configured to analyze and process the simulation parameter information to obtain target simulation state value information, wherein the target simulation state value information comprises target displacement state value information, target speed state value information and target acceleration state value information.

[0011] The second processing module is configured to analyze and judge the target simulation state value information to obtain target simulation result information.

[0012] The third aspect of the present application discloses another data processing device for step length dynamic adjustment, which comprises:

[0013] A memory storing executable program codes;

[0014] A processor coupled with the memory;

[0015] The processor calls the executable program codes stored in the memory to execute part or all steps of the data processing method for step length dynamic adjustment disclosed in the first aspect of the present application.

[0016] The fourth aspect of the present application discloses a computer readable storage medium storing computer instructions, which are called to execute part or all steps of the data processing method for step length dynamic adjustment disclosed in the first aspect of the present application.

[0017] The present application has the following advantages:

[0018] The data processing method for step length dynamic adjustment disclosed in the present application is beneficial to realize low-computational-cost step length dynamic adjustment and improve the overall performance of the simulation system. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a scene schematic diagram of the data processing system for step length dynamic adjustment disclosed in the embodiments of the present application;

[0020] Figure 2 is a flow schematic diagram of the data processing method for step length dynamic adjustment disclosed in the embodiments of the present application;

[0021] Figure 3 is a structure schematic diagram of the data processing device for step length dynamic adjustment disclosed in the embodiments of the present application;

[0022] Figure 4 is a structure schematic diagram of another data processing device for step length dynamic adjustment disclosed in the embodiments of the present application. DETAILED DESCRIPTION

[0023] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application, so that those skilled in the art can better understand the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0024] The terms "first", "second", and the like in the description and claims of the present application and the above drawings are used to distinguish different objects, and are not used to describe a particular order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but can optionally include other steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or apparatus.

[0025] In this document, reference to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. Those skilled in the art will appreciate from the present description that embodiments described herein can be combined with other embodiments in various ways.

[0026] In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration." Any implementation described as exemplary is not necessarily to be construed as preferred or advantageous over other implementations. The following description is presented to enable any person skilled in the art to make and use the application. In the following description, for purposes of explanation, specific details are set forth. It is apparent to those skilled in the art that the present application can be practiced without using these specific details. In other instances, well-known structures and processes are not described in detail in order to avoid obscuring the description of the application. Thus, the present application is not intended to be limited by the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0027] It should be noted that the method of the present application is executed in a computer device, and the processing objects of each computer device exist in the form of data or information, such as time, which is essentially time information. It can be understood that if the size, quantity, position, etc. are mentioned in subsequent embodiments, they are corresponding data, so that the computer device can process them, and specific details are not described here.

[0028] It should be noted that the artificial intelligence related technologies involved in the present application are briefly described. Artificial intelligence (AI) is the use of digital computers or digital computer controlled machines to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology of computer science, which attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that machines have the functions of perception, reasoning and decision-making.

[0029] Artificial intelligence technology is a comprehensive discipline, involving a wide range of fields, both hardware and software technologies. Artificial intelligence basic technologies generally include technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction system, mechatronics, etc. Artificial intelligence software technology mainly includes computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning, etc.

[0030] Computer vision (CV) is a science that studies how to make machines "see". Further, it refers to using cameras and computers to replace human eyes to identify and measure targets, and further to do image processing, so that the computer processing becomes more suitable for human eye observation or image transmission to instrument detection. As a scientific discipline, computer vision researches related theories and technologies, trying to establish artificial intelligence systems that can obtain information from images or multidimensional data. Computer vision technology usually includes image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, three-dimensional object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping, etc. It also includes common face recognition, fingerprint recognition and other biometric identification technologies.

[0031] Single modal information is only one type of data, such as text, image, audio, video, electromagnetic signal, etc. Multi-modal information is data information including at least two single modal information. Further, multi-modal information is suitable for complex tasks that require the integration of multiple information sources, such as sentiment analysis, robot interaction, autonomous driving, etc. By integrating information from multiple modalities, higher performance and accuracy can usually be achieved in tasks.

[0032] A large model refers to an artificial neural network model with a very large number of parameters. In the field of artificial intelligence, a large model usually refers to a model with hundreds of millions to tens of billions of parameters. The model usually needs to be trained on a large-scale dataset and requires a large amount of computing resources for optimization and adjustment. Large models are usually used to solve complex natural language processing, computer vision, and speech recognition tasks. Generative AI is an AI that can create new content and ideas, including conversations, stories, images, videos, and music. In the embodiments of the present application, the large model can be a large language model such as ChatGPT, BERT, XLNet, Zhibu model, Claude, Moonshot AI model, ChatGLM model, Tongwen Qiyi model, MiniMax model, Xinghuo model, Llama model, 360GPT model, Qwen model, Baichuan model, Yunque model, vivoLM model, and Wenxin Yiyang, etc. The embodiments of the present application are not limited.

[0033] The embodiments of the present application provide a data processing method and device for step dynamic adjustment, computer equipment and computer readable storage medium, which are described in detail below.

[0034] Please refer to Figure 1 , Figure 1 The scene schematic diagram of the data processing system for step dynamic adjustment provided by the embodiments of the present application can include a computer equipment 100, and the computer equipment 100 is integrated with a data processing device for step dynamic adjustment, such as Figure 1 computer equipment in the embodiments of the present application.

[0035] The computer equipment 100 in the embodiments of the present application is mainly used for obtaining simulation parameter information; the simulation parameter information includes basic simulation parameter information obtained by interacting with a user, and simulation object parameter information; the simulation object parameter information includes first object displacement information, first object speed information, and first object acceleration information;

[0036] The simulation parameter information is analyzed and processed to obtain target simulation state value information; the target simulation state value information includes target displacement state value information, target speed state value information, and target acceleration state value information;

[0037] The target simulation state value information is analyzed and judged to obtain target simulation result information.

[0038] The data processing system for step dynamic adjustment can realize low-computing-overhead step dynamic adjustment and improve the overall performance of the simulation system.

[0039] In this embodiment, the computer device 100 can be a standalone server, a server network, or a server cluster. For example, the computer device 100 described in this embodiment includes, but is not limited to, a computer, a network host, a single network server, a set of multiple network servers, or a cloud server composed of multiple servers. The cloud server is composed of a large number of computers or network servers based on cloud computing.

[0040] It is understood that the computer device 100 used in the embodiments of this application can be a device that includes both receiving and transmitting hardware, that is, a device having receiving and transmitting hardware capable of performing bidirectional communication on a bidirectional communication link. Such a device may include: cellular or other communication devices having a single-line display, a multi-line display, or a cellular or other communication device without a multi-line display. Specifically, the computer device 100 may be a desktop terminal or a mobile terminal, and may also be one of a mobile phone, tablet computer, laptop computer, etc.

[0041] Those skilled in the art will understand that Figure 1 The application environment shown is merely one application scenario of the solution in this application and does not constitute a limitation on the application scenario of the solution in this application. Other application environments may include more than one application scenario. Figure 1 The number of computer devices shown is more or less, for example Figure 1 Only one computer device is shown in the diagram. It is understood that the data processing system for dynamic step size adjustment may also include one or more other services, which are not limited here.

[0042] In addition, such as Figure 1 As shown, the data processing system for dynamic step size adjustment may also include a memory 200 for storing data, such as image data, location information, etc.

[0043] It should be noted that, Figure 1 The schematic diagram of the data processing system for dynamic step size adjustment shown is merely an example. The data processing system and scenario for dynamic step size adjustment described in this application are for the purpose of more clearly illustrating the technical solutions of this application and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of the data processing system for dynamic step size adjustment and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0044] This invention discloses a data processing method and apparatus for dynamic step size adjustment, which facilitates low-computational-overhead dynamic step size adjustment and improves the overall performance of the simulation system. Detailed descriptions follow.

[0045] Example 1:

[0046] Please see Figure 2 , Figure 2 This is a flowchart illustrating a data processing method for dynamic step size adjustment disclosed in an embodiment of the present invention. Figure 2 The described data processing method for dynamic step size adjustment is applied in a management system, such as a local server or cloud server for management, and this embodiment of the invention is not limited thereto. Figure 2 As shown, the data processing method for dynamic step size adjustment may include the following operations:

[0047] 101. Obtain simulation parameter information.

[0048] In this embodiment of the invention, the simulation parameter information includes basic simulation parameter information obtained through interaction with the user, and simulation object parameter information; the simulation object parameter information includes first object displacement information, first object velocity information, and first object acceleration information.

[0049] 102. Analyze and process the simulation parameter information to obtain the target simulation state value information.

[0050] In this embodiment of the invention, the target simulation state value information includes target displacement state value information, target velocity state value information, and target acceleration state value information.

[0051] 103. Analyze and process the target simulation state value information to obtain the target simulation result information.

[0052] It should be noted that the basic simulation parameters mentioned above are obtained by the user through input on the system interface, and can be updated by the system through simulation data during the simulation process. This embodiment of the invention does not limit this.

[0053] It should be noted that the above-mentioned target simulation results represent the kinematic simulation results of the simulation object, and the embodiments of the present invention are not limited thereto.

[0054] It is evident that implementing the data processing method for dynamic step size adjustment described in the embodiments of the present invention is beneficial for achieving dynamic step size adjustment with low computational overhead and improving the overall performance of the simulation system.

[0055] In an optional embodiment, the above-described analysis and processing of simulation parameter information to obtain target simulation state value information includes:

[0056] The simulation parameter information is processed using the first simulation calculation model to obtain the first simulation state value information;

[0057] The first simulation calculation model is:

[0058]

[0059] In the above formula, ZT1, and characterize the first displacement state value information, the first speed state value information and the first acceleration state value information in the first simulation state value information; BC characterizes the simulation step length in the basic simulation parameter information; FZDX1, and characterize the first object displacement information, the first object speed information and the first object acceleration information in the simulation object parameter information; xs1 and xs2 respectively characterize the first simulation calculation coefficient and the second simulation calculation coefficient;

[0060] Based on the first simulation state value information, target simulation state value information is determined.

[0061] It should be noted that the first simulation calculation coefficient and the second simulation calculation coefficient can be set by a user, or can be obtained by analyzing historical coefficients by using a large model, and the embodiments of the present application are not limited. Further, the first simulation calculation coefficient and the second simulation calculation coefficient are values between 0 and 1, and can be one of 0.5, 0.6, 0.7 or 0.8, and the embodiments of the present application are not limited.

[0062] It should be noted that the simulation step length characterizes a time period of each simulation, such as 1 second, 2 seconds, etc., and the embodiments of the present application are not limited. Further, the initial simulation step length is set by a user or a default value given by a system, and is dynamically adjusted in a subsequent simulation process, and the embodiments of the present application are not limited.

[0063] It can be seen that the data processing method for step length dynamic adjustment described in the embodiments of the present application is beneficial to realize low-computing-overhead step length dynamic adjustment and improve the overall performance of a simulation system.

[0064] In another optional embodiment, based on the first simulation state value information, target simulation state value information is determined, including:

[0065] The simulation object parameter information and the first simulation state value information are calculated and processed by using a second simulation calculation model to obtain second acceleration state value information;

[0066] The second simulation calculation model is:

[0067]

[0068] In the above formula, characterize the second acceleration state value information; JCCS1, JCCS2, JCCS3 and JCCS4 respectively characterize the first base parameter, the second base parameter, the third base parameter and the fourth base parameter in the base simulation parameter information;

[0069] the first simulation state value information is calculated by using the third simulation calculation model, to obtain the second displacement state value information and the second speed state value information;

[0070] The third simulation calculation model is as follows:

[0071]

[0072] In the above formula, ZT2 and respectively characterize the second displacement state value information and the second speed state value information; xs3, xs4 and xs5 respectively characterize the third simulation calculation coefficient, the fourth simulation calculation coefficient and the fifth simulation calculation coefficient;

[0073] Based on the base simulation times, the first simulation state value information, the second acceleration state value information, the second displacement state value information and the second speed state value information, the target simulation state value information is determined.

[0074] It should be noted that the above first base parameter, second base parameter, third base parameter and fourth base parameter respectively characterize the mass matrix, the force matrix, the damping matrix and the stiffness matrix, and the embodiments of the present application are not limited. Further, the first base parameter, the second base parameter, the third base parameter and the fourth base parameter can be directly determined according to their physical properties when determining the simulation object, wherein the force matrix can be updated by the set simulation sensor at each simulation step in the simulation process, and the embodiments of the present application are not limited.

[0075] It should be noted that the above third simulation calculation coefficient, fourth simulation calculation coefficient and fifth simulation calculation coefficient are values between [0, 0.5], which can be 0.5, 0.25 and 0.1 respectively, and the embodiments of the present application are not limited.

[0076] It can be seen that the data processing method for step length dynamic adjustment described in the embodiments of the present application is beneficial to realize low-computing-overhead step length dynamic adjustment and improve the overall performance of the simulation system.

[0077] In another optional embodiment, based on the base simulation times, the first simulation state value information, the second acceleration state value information, the second displacement state value information and the second speed state value information, the target simulation state value information is determined, including:

[0078] determine whether the base simulation times is greater than the first number threshold to obtain a first number judgment result;

[0079] When the first number judgment result is yes, the simulation step is updated by step reduction, and the calculation of the simulation parameter information by the first simulation calculation model is triggered to obtain the first simulation state value information;

[0080] When the first number judgment result is no, the target simulation state value information is determined based on the first simulation state value information, the second acceleration state value information, the second displacement state value information and the second speed state value information.

[0081] It should be noted that the above basic simulation number represents the number of simulation, and the initial value is 1. The basic simulation number is increased when the displacement judgment result is no. The present embodiment is not limited.

[0082] It should be noted that the first number threshold is a value between 5 and 10, such as 5, 6, 7, 8, 9, and 10. The present embodiment is not limited.

[0083] It should be noted that the first number threshold represents the maximum number of simulation iterations (the maximum number of simulation iterations is used to control the simulation step, that is, a pre-set simulation step is used to simulate in the early stage to ensure simulation efficiency, and then the simulation step is reduced to improve simulation accuracy after a certain number of simulations), which is greater than the second number threshold. Further, the second number threshold represents the minimum number of simulation iterations (the minimum number of simulation iterations is used to ensure simulation efficiency, that is, the simulation step is increased, the frequent analysis and judgment is reduced, and the resource consumption is reduced), and the present embodiment is not limited. Further, the second number threshold can be 3 or 4, and the present embodiment is not limited.

[0084] It should be noted that the simulation step is updated by step reduction, that is, the step period is shortened and the numerical simulation accuracy is improved, and the present embodiment is not limited.

[0085] It can be seen that the data processing method for step dynamic adjustment described in the present embodiment is beneficial to realize low-computing-overhead step dynamic adjustment and improve the overall performance of the simulation system.

[0086] In another optional embodiment, the target simulation state value information is determined based on the first simulation state value information, the second acceleration state value information, the second displacement state value information and the second speed state value information, including:

[0087] The difference between the second displacement state value information and the first displacement state value information in the first simulation state value information is calculated to obtain a displacement difference;

[0088] It is judged whether the displacement difference is less than or equal to a displacement threshold to obtain a displacement judgment result;

[0089] When the displacement judgment result is no, the basic simulation number is increased and updated;

[0090] The first displacement state value information, the first speed state value information and the first acceleration state value information in the first simulation state value information are replaced and updated by using the first displacement state value information, the first speed state value information and the first acceleration state value information in the first simulation state value information;

[0091] The first displacement state value information, the first speed state value information and the first acceleration state value information in the first simulation state value information are replaced and updated by using the second displacement state value information, the second speed state value information and the second acceleration state value information;

[0092] And triggering the execution of the calculation and processing of the simulation object parameter information and the first simulation state value information by using the second simulation calculation model to obtain the second acceleration state value information;

[0093] When the displacement judgment result is yes, the second displacement state value information, the second speed state value information and the second acceleration state value information are respectively taken as the target displacement state value information, the target speed state value information and the target acceleration state value information in the target simulation state value information.

[0094] It should be noted that the displacement threshold value is a value between [0.1, 0.5], which can be 0.2, 0.3, etc., and the embodiment of the application is not limited.

[0095] It should be noted that the increase and update of the basic simulation number is to add 1 to the basic simulation number, and the embodiment of the application is not limited.

[0096] It should be noted that the difference between the second displacement state value information and the first displacement state value information in the first simulation state value information is first calculated by numerical difference, and then absolute value processing is performed, and the embodiment of the application is not limited.

[0097] It can be seen that the data processing method for step dynamic adjustment described in the embodiment of the application is beneficial to realize low-computing-overhead step dynamic adjustment and improve the overall performance of the simulation system.

[0098] In an optional embodiment, the analysis and judgment processing of the target simulation state value information to obtain the target simulation result information includes:

[0099] The simulation time is obtained;

[0100] The target simulation result information is determined based on the simulation time, the basic simulation number and the target simulation state value information.

[0101] It should be noted that the simulation time represents the absolute time of the current simulation advancement, and the embodiments of the present application are not limited.

[0102] It can be seen that the data processing method for step length dynamic adjustment described in the embodiments of the present application is beneficial to realize low-computational-overhead step length dynamic adjustment and improve the overall performance of the simulation system.

[0103] In another optional embodiment, the target simulation result information is determined based on the simulation time, the basic simulation times, and the target simulation state value information, and includes:

[0104] It is determined whether the simulation time is equal to the time threshold value, and a time determination result is obtained.

[0105] When the time determination result is yes, the target simulation state value information is taken as the target simulation result information.

[0106] When the time determination result is no, it is determined whether the basic simulation times are greater than or equal to the second number threshold value, and a second number determination result is obtained.

[0107] When the second number determination result is no, the simulation parameter information is analyzed and processed, and the target simulation state value information is obtained.

[0108] When the second number determination result is yes, the simulation step length is increased by one step, and the simulation parameter information is analyzed and processed, and the target simulation state value information is obtained.

[0109] It should be noted that the time threshold value is a value between 50 seconds and 5 minutes, counted in seconds, such as 60, 80, 100, etc., and the embodiments of the present application are not limited.

[0110] It should be noted that the simulation step length is increased by one step, mainly considering that the displacement error of the previous two iterations is within the range, and the simulation step length does not need to be too small. Small simulation step length itself does not significantly improve simulation accuracy. If a small simulation step length is continuously used, the simulation resource consumption is large. Therefore, in order to improve simulation efficiency and resource utilization, the simulation step length is gradually doubled, and the embodiments of the present application are not limited.

[0111] It can be seen that the data processing method for step length dynamic adjustment described in the embodiments of the present application is beneficial to realize low-computational-overhead step length dynamic adjustment and improve the overall performance of the simulation system.

[0112] Embodiment two:

[0113] Please refer to Figure 3 , Figure 3 is a structural schematic diagram of a data processing device for step length dynamic adjustment disclosed by the embodiments of the present application.Figure 3 The described device can be applied in a management system, such as a local server or a cloud server for management, and the embodiments of the present application are not limited. As shown in the figure, the device can include: Figure 3 The device can include:

[0114] The acquisition module 201 is configured to acquire simulation parameter information; the simulation parameter information includes basic simulation parameter information obtained by interacting with a user, and simulation object parameter information; the simulation object parameter information includes first object displacement information, first object speed information, and first object acceleration information;

[0115] The first processing module 202 is configured to analyze and process the simulation parameter information to obtain target simulation state value information; the target simulation state value information includes target displacement state value information, target speed state value information, and target acceleration state value information;

[0116] The second processing module 203 is configured to analyze and judge the target simulation state value information to obtain target simulation result information.

[0117] It can be seen that the embodiments Figure 3 The described data processing device for step length dynamic adjustment is beneficial to realize low-computing-overhead step length dynamic adjustment and improve the overall performance of the simulation system.

[0118] In another optional embodiment, as shown in the figure, the analysis and processing of the simulation parameter information to obtain the target simulation state value information includes: Figure 3

[0119] The first simulation calculation model is used to calculate and process the simulation parameter information to obtain first simulation state value information;

[0120] The first simulation calculation model is as follows:

[0121]

[0122] In the above formula, ZT1、 and represent the first displacement state value information, the first speed state value information, and the first acceleration state value information in the first simulation state value information; BC represents the simulation step length in the basic simulation parameter information; FZDX1、 and represent the first object displacement information, the first object speed information, and the first object acceleration information in the simulation object parameter information; xs1 and xs2 represent the first simulation calculation coefficient and the second simulation calculation coefficient, respectively;

[0123] The target simulation state value information is determined based on the first simulation state value information.

[0124] ​It can be seen that the embodiment Figure 3 The data processing apparatus for step dynamic adjustment described has the advantages of facilitating low-computational-overhead step dynamic adjustment and improving the overall performance of the simulation system.

[0125] In yet another optional embodiment, as shown in Figure 3 Based on the first simulation state value information, the target simulation state value information is determined, including:

[0126] The simulation object parameter information and the first simulation state value information are calculated and processed by using the second simulation calculation model to obtain second acceleration state value information;

[0127] The second simulation calculation model is:

[0128]

[0129] In the above formula, ZT2 and represent the second acceleration state value information; JCCS1, JCCS2, JCCS3, and JCCS4 represent the first basic parameter, the second basic parameter, the third basic parameter, and the fourth basic parameter in the basic simulation parameter information, respectively;

[0130] The first simulation state value information is calculated and processed by using the third simulation calculation model to obtain second displacement state value information and second speed state value information;

[0131] The third simulation calculation model is:

[0132]

[0133] In the above formula, ZT2 and represent the second displacement state value information and the second speed state value information, respectively; xs3, xs4, and xs5 represent the third simulation calculation coefficient, the fourth simulation calculation coefficient, and the fifth simulation calculation coefficient, respectively;

[0134] Based on the basic simulation times, the first simulation state value information, the second acceleration state value information, the second displacement state value information, and the second speed state value information, the target simulation state value information is determined.

[0135] It can be seen that the embodiment Figure 3 The data processing apparatus for step dynamic adjustment described has the advantages of facilitating low-computational-overhead step dynamic adjustment and improving the overall performance of the simulation system.

[0136] In yet another optional embodiment, as shown in Figure 3 Based on the basic simulation times, the first simulation state value information, the second acceleration state value information, the second displacement state value information, and the second speed state value information, the target simulation state value information is determined.

[0137] determining whether the basic simulation times is greater than a first times threshold, to obtain a first times determination result;

[0138] when the first times determination result is yes, performing step length reduction update on the simulation step length, and triggering execution of calculation and processing on the simulation parameter information by using the first simulation calculation model, to obtain first simulation state value information;

[0139] when the first times determination result is no, determining target simulation state value information based on the first simulation state value information, the second acceleration state value information, the second displacement state value information and the second speed state value information.

[0140] It can be seen that, by implementing the data processing apparatus for step length dynamic adjustment, Figure 3 The data processing apparatus for step length dynamic adjustment described herein is advantageous in realizing low-computational-overhead step length dynamic adjustment and improving the overall performance of the simulation system.

[0141] In yet another optional embodiment, as shown in Figure 3 determining the target simulation state value information based on the first simulation state value information, the second acceleration state value information, the second displacement state value information and the second speed state value information, includes:

[0142] calculating a difference between the second displacement state value information and the first displacement state value information in the first simulation state value information, to obtain a displacement difference;

[0143] determining whether the displacement difference is less than or equal to a displacement threshold, to obtain a displacement determination result;

[0144] when the displacement determination result is no, performing increase update on the basic simulation times;

[0145] replacing and updating the first object displacement information, the first object speed information and the first object acceleration information in the simulation object parameter information by using the first displacement state value information, the first speed state value information and the first acceleration state value information in the first simulation state value information;

[0146] replacing and updating the first displacement state value information, the first speed state value information and the first acceleration state value information in the first simulation state value information by using the second displacement state value information, the second speed state value information and the second acceleration state value information;

[0147] and triggering execution of calculation and processing on the simulation object parameter information and the first simulation state value information by using the second simulation calculation model, to obtain the second acceleration state value information;

[0148] When the displacement determination result is yes, the second displacement state value information, the second speed state value information and the second acceleration state value information are respectively taken as target displacement state value information, target speed state value information and target acceleration state value information in target simulation state value information.

[0149] It can be seen that, by implementing the data processing apparatus for dynamic adjustment of step length, Figure 3 The data processing apparatus for dynamic adjustment of step length described herein facilitates the dynamic adjustment of step length with low computational overhead, thereby improving the overall performance of the simulation system.

[0150] In yet another optional embodiment, as shown in Figure 3 The target simulation result information is obtained by analyzing and judging the target simulation state value information, including:

[0151] The simulation time is obtained.

[0152] The target simulation result information is determined based on the simulation time, the basic simulation times and the target simulation state value information.

[0153] It can be seen that, by implementing the data processing apparatus for dynamic adjustment of step length, Figure 3 The data processing apparatus for dynamic adjustment of step length described herein facilitates the dynamic adjustment of step length with low computational overhead, thereby improving the overall performance of the simulation system.

[0154] In yet another optional embodiment, as shown in Figure 4 The target simulation result information is determined based on the simulation time, the basic simulation times and the target simulation state value information, including:

[0155] It is determined whether the simulation time is equal to the time threshold value, and a time determination result is obtained.

[0156] When the time determination result is yes, the target simulation state value information is taken as the target simulation result information.

[0157] When the time determination result is no, it is determined whether the basic simulation times are greater than or equal to the second number threshold value, and a second number determination result is obtained.

[0158] When the second number determination result is no, the simulation parameter information is analyzed and processed to obtain the target simulation state value information.

[0159] When the second number determination result is yes, the simulation step length is increased and updated, and the simulation parameter information is analyzed and processed to obtain the target simulation state value information.

[0160] It can be seen that, by implementing the data processing apparatus for dynamic adjustment of step length, Figure 4 The data processing apparatus for dynamic adjustment of step length described herein facilitates the dynamic adjustment of step length with low computational overhead, thereby improving the overall performance of the simulation system.

[0161] Embodiment three:

[0162] Please refer to Figure 4 , Figure 4 is another structure diagram of the data processing device for step length dynamic adjustment disclosed by the embodiment of the application. Wherein, ​ The described device can be applied to a management system, such as a local server or a cloud server for management, and the embodiment of the application is not limited. As ​ The device can include:

[0163] The memory 301 stores executable program codes;

[0164] The processor 302 is coupled to the memory 301;

[0165] The processor 302 calls the executable program codes stored in the memory 301, and is used for executing the steps in the data processing method for step length dynamic adjustment described in embodiment one.

[0166] Embodiment four:

[0167] The embodiment of the application discloses a computer readable storage medium, which stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps in the data processing method for step length dynamic adjustment described in embodiment one.

[0168] Embodiment five:

[0169] The embodiment of the application discloses a computer program product, which includes a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the data processing method for step length dynamic adjustment described in embodiment one.

[0170] The device embodiments described above are only schematic, wherein the modules illustrated as separate components can or can not be physically separated, and the components illustrated as modules can or can not be physical modules, that is, they can be located in one place, or can be distributed on multiple network modules. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement it without creative labor.

[0171] Those skilled in the art can clearly understand the implementation of the various embodiments by means of software and necessary general hardware platforms through the above specific description of the embodiments, and of course, the embodiments can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be embodied in the form of a software product. The computer software product can be stored in a computer readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage, a magnetic tape storage, or any other computer readable medium that can be used to carry or store data.

[0172] Finally, it should be noted that: the data processing method and device for step length dynamic adjustment disclosed by the embodiments of the present application are only the preferred embodiments of the present application, and are used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A data processing method for dynamic step size adjustment, characterized in that, The method includes: Acquire simulation parameter information; the simulation parameter information includes basic simulation parameter information obtained through interaction with the user, and simulation object parameter information; the simulation object parameter information includes first object displacement information, first object velocity information, and first object acceleration information; The simulation parameter information is analyzed and processed to obtain the target simulation state value information; the target simulation state value information includes target displacement state value information, target velocity state value information, and target acceleration state value information. The target simulation state value information is analyzed, judged, and processed to obtain the target simulation result information.

2. The data processing method for dynamic step size adjustment according to claim 1, characterized in that, The simulation parameter information is analyzed and processed to obtain the target simulation state value information, including: The simulation parameter information is processed using the first simulation calculation model to obtain the first simulation state value information; The first simulation calculation model is: In the above formula, ZT1 represents the first displacement state value information in the first simulation state value information; The first velocity state value information in the first simulation state value information; The first acceleration state value information in the first simulation state value information is represented by BC; the simulation step size in the basic simulation parameter information is represented by BC; and the first object displacement information in the simulation object parameter information is represented by FZDX1. The velocity information of the first object in the parameter information of the simulated object; The first object acceleration information in the simulated object parameter information; xs1 represents the first simulation calculation coefficient; xs2 represents the second simulation calculation coefficient; Based on the first simulation state value information, the target simulation state value information is determined.

3. The data processing method for dynamic step size adjustment according to claim 2, characterized in that, Based on the first simulation state value information, the target simulation state value information is determined, including: The second simulation calculation model is used to calculate and process the parameter information of the simulation object and the first simulation state value information to obtain the second acceleration state value information; The second simulation calculation model is: In the above formula, JCCS1 represents the second acceleration state value information; JCCS2 represents the second basic parameter in the basic simulation parameter information; JCCS3 represents the third basic parameter in the basic simulation parameter information; JCCS4 represents the fourth basic parameter in the basic simulation parameter information. The third simulation calculation model is used to calculate and process the first simulation state value information to obtain the second displacement state value information and the second velocity state value information; The third simulation calculation model is: In the above formula, ZT2 represents the second displacement state value information; xs3 represents the second velocity state value information; xs4 represents the third simulation calculation coefficient; xs5 represents the fourth simulation calculation coefficient; Based on the number of basic simulations, the first simulation state value information, the second acceleration state value information, the second displacement state value information, and the second velocity state value information, the target simulation state value information is determined.

4. The data processing method for dynamic step size adjustment according to claim 3, characterized in that, Based on the basic simulation count, the first simulation state value information, the second acceleration state value information, the second displacement state value information, and the second velocity state value information, the target simulation state value information is determined, including: Determine whether the number of basic simulations exceeds the threshold of the first number, and obtain the result of the first number judgment. When the first numerical judgment result is yes, the simulation step size is updated by decreasing the step size, and the execution of the simulation parameter information is triggered by using the first simulation calculation model to obtain the first simulation state value information. When the first numerical judgment result is negative, the target simulation state value information is determined based on the first simulation state value information, the second acceleration state value information, the second displacement state value information, and the second velocity state value information.

5. The data processing method for dynamic step size adjustment according to claim 4, characterized in that, Based on the first simulation state value information, the second acceleration state value information, the second displacement state value information, and the second velocity state value information, the target simulation state value information is determined, including: Calculate the difference between the second displacement state value information and the first displacement state value information in the first simulation state value information to obtain the displacement difference; Determine whether the displacement difference is less than or equal to the displacement threshold to obtain the displacement judgment result; When the displacement judgment result is negative, the number of basic simulations is increased and updated. The first displacement state value, first velocity state value, and first acceleration state value in the first simulation state value information are used to replace and update the first object displacement information, first object velocity information, and first object acceleration information in the simulation object parameter information; The first displacement state value, first velocity state value, and first acceleration state value in the first simulation state value information are replaced and updated using the second displacement state value information, the second velocity state value information, and the second acceleration state value information. It also triggers the execution of calculations using the second simulation calculation model to process the simulation object parameter information and the first simulation state value information, thereby obtaining the second acceleration state value information; When the displacement judgment result is yes, the second displacement state value information, the second velocity state value information, and the second acceleration state value information are respectively used as the target displacement state value information, target velocity state value information, and target acceleration state value information in the target simulation state value information.

6. The data processing method for dynamic step size adjustment according to claim 1, characterized in that, The target simulation state value information is analyzed and processed to obtain the target simulation result information, including: Obtain the simulation time; Based on the simulation time, the number of basic simulations, and the target simulation state value information, the target simulation result information is determined.

7. The data processing method for dynamic step size adjustment according to claim 6, characterized in that, Based on simulation time, the number of basic simulations, and the target simulation state value information, the target simulation result information is determined, including: Determine whether the simulation time is equal to the time threshold to obtain the time determination result; When the time judgment result is yes, the target simulation state value information is used as the target simulation result information; If the time judgment result is negative, determine whether the number of basic simulations is greater than or equal to the threshold of the second number, and obtain the second number judgment result; When the result of the second numerical judgment is negative, the process of analyzing and processing the simulation parameter information is triggered to obtain the target simulation state value information. When the result of the second numerical judgment is yes, the simulation step size is increased and updated, and the simulation parameter information is analyzed and processed to obtain the target simulation state value information.

8. A data processing device for dynamic step size adjustment, characterized in that, The device includes: The acquisition module is used to acquire simulation parameter information. The simulation parameter information includes basic simulation parameter information obtained through interaction with the user, as well as simulation object parameter information. The simulation object parameter information includes the displacement information, velocity information, and acceleration information of the first object. The first processing module is used to analyze and process the simulation parameter information to obtain the target simulation state value information; the target simulation state value information includes the target displacement state value information, the target velocity state value information, and the target acceleration state value information. The second processing module is used to analyze and process the target simulation state value information to obtain the target simulation result information.

9. A data processing device for dynamic step size adjustment, characterized in that, The device includes: a memory storing executable program code; A processor coupled to memory; The processor calls executable program code stored in memory to execute the steps in the data processing method for dynamic step size adjustment as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, which, when invoked, are used to execute the steps in the data processing method for dynamic step size adjustment as described in any one of claims 1-7.

Images