Litcius/Paper detail

ANNA: advanced neural network algorithm for optimisation of structures

Nima Khodadadi, Siamak Talatahari, Amir H. Gandomi

2023Proceedings of the Institution of Civil Engineers - Structures and Buildings23 citationsDOI

Abstract

The purpose of this study is to develop an advanced neural network algorithm as a new optimisation for the optimal design of truss structures. The central concept of the algorithm is based on biological nerve structures and artificial neural networks. The performance of the proposed method is explored in engineering design problems. Two efficient methods for improving the standard neural network algorithm are considered here. The first is an enhanced initialisation mechanism based on opposite-based learning. The second relies on using a few tunable parameters to provide proper exploration and exploitation abilities for the algorithm, enabling better solutions to be found while the required structural analyses are reduced. The new algorithm's performance is investigated by using five well-known restricted benchmarks to assess its efficiency in relation to the latest optimisation techniques. The outcome of the examples demonstrates that the upgraded version of the algorithm has increased efficacy and robustness in comparison with the original version of the algorithm and some other methods.

Topics & Concepts

Artificial neural networkComputer scienceRobustness (evolution)AlgorithmTrussRelation (database)Artificial intelligenceEngineeringData miningGeneStructural engineeringBiochemistryChemistryMetaheuristic Optimization Algorithms ResearchStructural Health Monitoring TechniquesTopology Optimization in Engineering