A survey on evolutionary neural architecture search
Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …
architectures of DNNs play a crucial role in their performance, which is usually manually …
Advanced metaheuristic optimization techniques in applications of deep neural networks: a review
Deep neural networks (DNNs) have evolved as a beneficial machine learning method that
has been successfully used in various applications. Currently, DNN is a superior technique …
has been successfully used in various applications. Currently, DNN is a superior technique …
Coronavirus optimization algorithm: a bioinspired metaheuristic based on the COVID-19 propagation model
This study proposes a novel bioinspired metaheuristic simulating how the coronavirus
spreads and infects healthy people. From a primary infected individual (patient zero), the …
spreads and infects healthy people. From a primary infected individual (patient zero), the …
A survey of swarm and evolutionary computing approaches for deep learning
Deep learning (DL) has become an important machine learning approach that has been
widely successful in many applications. Currently, DL is one of the best methods of …
widely successful in many applications. Currently, DL is one of the best methods of …
The orb-weaving spider algorithm for training of recurrent neural networks
AS Mikhalev, VS Tynchenko, VA Nelyub, NM Lugovaya… - Symmetry, 2022 - mdpi.com
The quality of operation of neural networks in solving application problems is determined by
the success of the stage of their training. The task of learning neural networks is a complex …
the success of the stage of their training. The task of learning neural networks is a complex …
Automatic design of machine learning via evolutionary computation: A survey
Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …
knowledge from data, has been widely applied to practical applications, such as …
Driver identification using optimized deep learning model in smart transportation
The Intelligent Transportation System (ITS) is said to revolutionize the travel experience by
making it safe, secure, and comfortable for the people. Although vehicles have been …
making it safe, secure, and comfortable for the people. Although vehicles have been …
Optimizing deep learning model parameters using socially implemented IoMT systems for diabetic retinopathy classification problem
Diabetic retinopathy (DR) is on the increase nowadays due to the high sugar level in the
blood, and it is the reason for blindness that mainly occurs in middle-aged people …
blood, and it is the reason for blindness that mainly occurs in middle-aged people …
Deepswarm: Optimising convolutional neural networks using swarm intelligence
E Byla, W Pang - … Intelligence Systems: Contributions Presented at the …, 2020 - Springer
In this paper we propose DeepSwarm, a novel neural architecture search (NAS) method
based on Swarm Intelligence principles. At its core DeepSwarm uses Ant Colony …
based on Swarm Intelligence principles. At its core DeepSwarm uses Ant Colony …
Lights and shadows in evolutionary deep learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges
Much has been said about the fusion of bio-inspired optimization algorithms and Deep
Learning models for several purposes: from the discovery of network topologies and …
Learning models for several purposes: from the discovery of network topologies and …