A novel evolutionary algorithm for identifying multiple structure detects by artificial intelligent model updating


EOI: 10.11242/viva-tech.01.05.103

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Citation

Ms. Akshay Mistry, Ms. Pratibha Patil, Ms. , , "A novel evolutionary algorithm for identifying multiple structure detects by artificial intelligent model updating", VIVA-IJRI Volume 1, Issue 5, Article 103, pp. 1-3, 2022. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Artificial intelligence (AI) is proving to be an efficient alternative approach to classical modeling techniques. AI refers to the branch of computer science that develops machines and software with human-like intelligence. Many problems in civil and structural engineering are affected by uncertainties that cannot be solved with traditional methods. AI aids to solve such complex problems. In addition, AI-based solutions are good alternatives to determine engineering design parameters when testing is not possible, thus resulting in significant savings in terms of human time and effort spent in experiments AI is also able to make the process of decision making faster, decrease error rates, and increase computational efficiency. Among the different AI techniques, machine learning (ML), pattern recognition (PR), and deep learning (DL) have acquired considerable attention and are establishing themselves as a new class of intelligent methods for use in structural engineering. The objective of this review paper is to summarize recently developed techniques with regards to the applications of the noted AI methods in structural engineering over the last decade. First, a general introduction to AI is presented and the importance of AI in the field is described. Thereafter, a review of recent applications of ML, PR, and DL in structural engineering is provided, and the capability of such methods to address the restrictions of conventional models are discussed. Further, the advantages of employing such intelligent methods are discussed in detail. Finally, potential research avenues and emerging trends for employing ML, PR, and DL are presented.

Keywords

structural engineering, artificial intelligence, machine learning, pattern recognition, deep learning, soft computing

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