基于计算机模拟应用的数学实验研究  

Research on Mathematical Experiments Based on Computer Simulation Applications

作　　者：张瑜 ZHANG Yu(Shanxi Jinzhong University of Technology,Jinzhong 030600,China)

机构地区：[1]山西晋中理工学院,山西晋中030600

出　　处：《数字通信世界》2024年第8期49-51,共3页Digital Communication World

摘　　要：该文聚焦基于计算机模拟应用的数学实验研究,通过深入探讨计算机模拟与数据驱动、数学模型与计算机模拟、数据同化技术以及数据生成模型的优化等关键领域,展现了计算机模拟与数学建模的相互交融。其中,数据同化技术在提高数学模型还原能力方面发挥了重要作用,通过将实测数据与模拟数据融合,优化模型参数,实现了对真实系统更精准的描述。另一方面,数据生成模型的优化则通过引入生成对抗网络等技术,提高了计算机模拟生成的合成数据的逼真度,为数学模型提供更具代表性的输入,推动了模型的性能提升。这一研究突显了计算机模拟在数学实验研究中的应用价值,为科学研究和工程应用提供了新的思路和方法。This article focuses on mathematical experimental research based on computer simulation applications.Through in-depth exploration of key areas such as computer simulation and data-driven,mathematical models and computer simulation,data assimilation technology,and optimization of data generation models,it demonstrates the integration of computer simulation and mathematical modeling.Among them,data assimilation technology has played an important role in improving the restoration ability of mathematical models.By integrating measured data with simulated data,optimizing model parameters,and achieving more accurate descriptions of real systems.On the other hand,the optimization of data generation models improves the realism of synthesized data generated by computer simulation by introducing techniques such as generative adversarial networks,providing more representative inputs for mathematical models,and promoting the performance improvement of the models.This study highlights the application value of computer simulation in mathematical experimental research,providing new ideas and methods for scientific research and engineering applications.

关 键 词：计算机模拟 数学模型 数据同化技术 生成对抗网络 实验研究 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]