Adam Slowik
Cytowane przez
Cytowane przez
Firefly algorithm
XS Yang, A Slowik
Swarm intelligence algorithms, 163-174, 2020
Evolutionary algorithms and their applications to engineering problems
A Slowik, H Kwasnicka
Neural Computing and Applications 32, 12363-12379, 2020
Nature inspired methods and their industry applications—Swarm intelligence algorithms
A Slowik, H Kwasnicka
IEEE Transactions on Industrial Informatics 14 (3), 1004-1015, 2017
MOSOA: A new multi-objective seagull optimization algorithm
G Dhiman, KK Singh, M Soni, A Nagar, M Dehghani, A Slowik, A Kaur, ...
Expert Systems with Applications 167, 114150, 2021
Training of artificial neural networks using differential evolution algorithm
A Slowik, M Bialko
2008 conference on human system interactions, 60-65, 2008
Adaptive crossover operator based multi-objective binary genetic algorithm for feature selection in classification
Y Xue, H Zhu, J Liang, A Słowik
Knowledge-Based Systems 227, 107218, 2021
EMoSOA: a new evolutionary multi-objective seagull optimization algorithm for global optimization
G Dhiman, KK Singh, A Slowik, V Chang, AR Yildiz, A Kaur, M Garg
International Journal of Machine Learning and Cybernetics 12, 571-596, 2021
A self-adaptive mutation neural architecture search algorithm based on blocks
Y Xue, Y Wang, J Liang, A Slowik
IEEE Computational Intelligence Magazine 16 (3), 67-78, 2021
Artificial intelligence technique for gene expression by tumor RNA-Seq data: a novel optimized deep learning approach
NEM Khalifa, MHN Taha, DE Ali, A Slowik, AE Hassanien
IEEE Access 8, 22874-22883, 2020
Application of an adaptive differential evolution algorithm with multiple trial vectors to artificial neural network training
A Slowik
IEEE Transactions on Industrial Electronics 58 (8), 3160-3167, 2010
Metaheuristic Optimization Through Deep Learning Classification of COVID-19 in Chest X-Ray Images.
NA Samee, ESM El-Kenawy, G Atteia, MM Jamjoom, A Ibrahim, ...
Computers, Materials & Continua 73 (2), 2022
Multi-objective hybrid genetic algorithm for task scheduling problem in cloud computing
P Pirozmand, AAR Hosseinabadi, M Farrokhzad, M Sadeghilalimi, ...
Neural computing and applications 33, 13075-13088, 2021
A novel hybrid hypervolume indicator and reference vector adaptation strategies based evolutionary algorithm for many-objective optimization
G Dhiman, M Soni, HM Pandey, A Slowik, H Kaur
Engineering with Computers 37, 3017-3035, 2021
Swarm intelligence algorithms (two volume set)
A Slowik
CRC press, 2021
Multi-objective orthogonal opposition-based crow search algorithm for large-scale multi-objective optimization
RM Rizk-Allah, AE Hassanien, A Slowik
Neural Computing and Applications 32 (17), 13715-13746, 2020
Modified african buffalo optimization for strategic integration of battery energy storage in distribution networks
P Singh, NK Meena, A Slowik, SK Bishnoi
IEEE Access 8, 14289-14301, 2020
Use of machine learning methods for predicting amount of bioethanol obtained from lignocellulosic biomass with the use of ionic liquids for pretreatment
M Smuga-Kogut, T Kogut, R Markiewicz, A Słowik
Energies 14 (1), 243, 2021
Multi-objective optimization of surface grinding process with the use of evolutionary algorithm with remembered Pareto set
A Slowik, J Slowik
The International Journal of Advanced Manufacturing Technology 37, 657-669, 2008
Energy consumption prediction of appliances using machine learning and multi-objective binary grey wolf optimization for feature selection
D Moldovan, A Slowik
Applied Soft Computing 111, 107745, 2021
An improved bat optimization algorithm to solve the tasks scheduling problem in open shop
MB Shareh, SH Bargh, AAR Hosseinabadi, A Slowik
Neural Computing and Applications 33, 1559-1573, 2021
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