Neural Networks: A Novel Approach for Optimization and Efficiency of Structures

This paper explores the use of neural networks in optimizing structures. Employing these networks as one of the leading methods in the field of structural engineering, with its own advantages and specific challenges, enables the enhancement of efficiency and cost reduction. Among the advantages of using neural networks are high accuracy in load predictions, precise detection of risks and structural weaknesses, and increasing the efficiency and productivity of structures. However, computational complexity and the need for large volumes of data for training models are among the most significant challenges of employing these methods.In conclusion, the paper emphasizes the importance of practical applications of neural networks in the analysis and optimal design of structures and offers suggestions for future work in this area. With the capabilities and features they provide; these methods can help improve the performance and efficiency of structures and be used in various industrial and scientific projects.This paper demonstrates that the use of neural networks as a responsive and powerful tool in the analysis and optimization of structures will attract more attention and research from specialists in this field in the future.

Keywords:

The utilization of neural networks contributes to the optimization of structures , structural engineering , data modeling , and accurate prediction , thereby enhancing the cost-effectiveness of structures.