International Journal of Science, Engineering and TechnologyAuthors: Manish Kumar Jain, Dharmendra Singh Sengar, Abhendra Pratap Singh, Yash Kumar, Tarun Kumar Mishra, Nandini Sharma
Abstract: AI is growing much faster in every field including engineering and linear algebra has provided a strong base for it. Linear Algebra is a core branch of mathematics which is used in mostly all engineering fields. This review paper carries out its applications on five major fields of engineering, i.e., civil engineering, electrical engineering, mechanical engineering, computer science engineering, and chemical engineering. Vectors, matrices, system of linear equations, linear transformation, and eigenvalues have been discussed here. Linear algebra can be seen in civil engineering through structural analysis with the help of finite element methods and hydraulic modeling. In electrical engineering, it has a big part in circuit analysis, signal processing, control systems as well as communication; while in mechanical engineering it is applied for vibration studies robotics and fluid dynamics. In chemical engineering modeling processes thermodynamics and transport phenomena take place with the help of linear algebra. In computer science linear algebra helps machine learning data analysis computer graphics and cryptography to advance further. This paper illustrates the critical role that linear algebra plays as an underlying structure supporting AI and ML systems by their use of vector and matrix-based data representation as well as model computation. It reveals how different techniques such as neural networks dimensionality reduction optimization are based on fundamental principles from linear algebra to handle large datasets in modern engineering fields. Hence Linear algebra is important for new ideas and tech progress in engineering.
DOI: http://doi.org/10.5281/zenodo.21768308
