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 …
Crow search algorithm: theory, recent advances, and applications
In this article, a comprehensive overview of the Crow Search Algorithm (CSA) is introduced
with detailed discussions, which is intended to keep researchers interested in swarm …
with detailed discussions, which is intended to keep researchers interested in swarm …
Multilevel threshold image segmentation for COVID-19 chest radiography: A framework using horizontal and vertical multiverse optimization
H Su, D Zhao, H Elmannai, AA Heidari… - Computers in Biology …, 2022 - Elsevier
COVID-19 is currently raging worldwide, with more patients being diagnosed every day. It
usually is diagnosed by examining pathological photographs of the patient's lungs. There is …
usually is diagnosed by examining pathological photographs of the patient's lungs. There is …
EGNN: Graph structure learning based on evolutionary computation helps more in graph neural networks
Z Liu, D Yang, Y Wang, M Lu, R Li - Applied Soft Computing, 2023 - Elsevier
In recent years, graph neural networks (GNNs) have been successfully applied in many
fields due to their characteristics of neighborhood aggregation and have achieved state-of …
fields due to their characteristics of neighborhood aggregation and have achieved state-of …
Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection
This research's genesis is in two aspects: first, a guaranteed solution for mitigating the grey
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …
Evolutionary deep learning: A survey
As an advanced artificial intelligence technique for solving learning problems, deep learning
(DL) has achieved great success in many real-world applications and attracted increasing …
(DL) has achieved great success in many real-world applications and attracted increasing …
Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis
Y Zhang, R Liu, AA Heidari, X Wang, Y Chen, M Wang… - Neurocomputing, 2021 - Elsevier
Bankruptcy prediction is a crucial application in financial fields to aid in accurate decision
making for business enterprises. Many models may stagnate to low-accuracy results due to …
making for business enterprises. Many models may stagnate to low-accuracy results due to …
Evolutionary transfer optimization-a new frontier in evolutionary computation research
The evolutionary algorithm (EA) is a nature-inspired population-based search method that
works on Darwinian principles of natural selection. Due to its strong search capability and …
works on Darwinian principles of natural selection. Due to its strong search capability and …
Neural architecture search: Insights from 1000 papers
In the past decade, advances in deep learning have resulted in breakthroughs in a variety of
areas, including computer vision, natural language understanding, speech recognition, and …
areas, including computer vision, natural language understanding, speech recognition, and …
Automatically designing CNN architectures using the genetic algorithm for image classification
Convolutional neural networks (CNNs) have gained remarkable success on many image
classification tasks in recent years. However, the performance of CNNs highly relies upon …
classification tasks in recent years. However, the performance of CNNs highly relies upon …