COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach
Miodrag Zivkovic,Nebojsa Bacanin,K. Venkatachalam,Anand Nayyar,Aleksandar Djordjevic,Ivana Strumberger,Fadi Al-Turjman +6 more
TLDR
Wang et al. as mentioned in this paper proposed a hybrid approach between machine learning, adaptive neuro-fuzzy inference system and enhanced beetle antennae search swarm intelligence metaheuristics to predict the number of the COVID-19 cases.About:
This article is published in Sustainable Cities and Society.The article was published on 2021-03-01 and is currently open access. It has received 167 citations till now. The article focuses on the topics: Adaptive neuro fuzzy inference system & Search algorithm.read more
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Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions
TL;DR: A survey of AI methods being used in various applications in the fight against the COVID-19 outbreak is presented and the crucial roles of AI research in this unprecedented battle are outlined.
Journal ArticleDOI
Improved manta ray foraging optimization for multi-level thresholding using COVID-19 CT images.
TL;DR: In this paper, an efficient version of the recent manta ray foraging optimization (MRFO) algorithm is proposed based on the opposition-based learning called the MRFO-OBL algorithm.
Journal ArticleDOI
Performance of a Novel Chaotic Firefly Algorithm with Enhanced Exploration for Tackling Global Optimization Problems: Application for Dropout Regularization
Nebojsa Bacanin,Ruxandra Stoean,Miodrag Zivkovic,Aleksandar Petrović,Tarik A. Rashid,Timea Bezdan +5 more
TL;DR: In this paper, the authors proposed an enhanced version of the firefly algorithm that corrects the acknowledged drawbacks of the original method by an explicit exploration mechanism and a chaotic local search strategy, theoretically tested on two sets of bound-constrained benchmark functions from the CEC suites and practically validated for automatically selecting the optimal dropout rate for the regularization of deep neural networks.
Proceedings ArticleDOI
Optimizing Convolutional Neural Network by Hybridized Elephant Herding Optimization Algorithm for Magnetic Resonance Image Classification of Glioma Brain Tumor Grade
Timea Bezdan,Stefan Milosevic,K. Venkatachalam,Miodrag Zivkovic,Nebojsa Bacanin,Ivana Strumberger +5 more
TL;DR: In this paper, a metaheuristic method has been proposed to automatically search and target the near-optimal values of convolutional neural network hyperparameters based on hybridized version of elephant herding optimization swarm intelligence metaheuristics.
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Modified firefly algorithm for workflow scheduling in cloud-edge environment
TL;DR: In this paper , the authors proposed an enhanced firefly algorithm adapted for tackling workflow scheduling challenges in a cloud-edge environment, which overcomes observed deficiencies of original firefly metaheuristic by incorporating genetic operators and quasi-reflection-based learning procedure.
References
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