Artificial Neural Networks and Optimization Technique: A theoretical study

Abstract

Artificial Neural Networks (ANNs) have become a pivotal tool in modern artificial intelligence (AI), significantly impacting various fields such as image processing, natural language processing, and autonomous systems. The training process of ANNs requires find-ing optimal parameters (weights and biases) that minimize a loss function, which can be computationally intensive and challenging. To achieve better performance, it is crucial to employ efficient optimization techniques that guide the network toward optimal solutions effectively. This paper provides an overview of ANNs, including their structure, types, applications, advantages, challenges, and future directions. This review also provides optimization techniques that are used to enhance their performance during training.