[156] Yao Lv, Peng Liu, Juan Wang, Yao Zhang, Adam Slowik, Jianhui Lv, „GA-based Feature Selection Method for Oversized Data Analysis in Digital Economy”, Expert Systems, Volume 41, Issue 1, Article ID: e13477, January 2024, doi: 10.1111/exsy.13477, Impact Factor in 2022: 3.3

[157] Chenyi Zhang, Yu Xue, Ferrante Neri, Xu Cai, Adam Slowik, „Multi-objective Self-adaptive Particle Swarm Optimization for Large-scale Feature Selection in Classification”, International Journal of Neural Systems, Volume 34, Number 3, Article ID: 2450014, 2024, doi: 10.1142/S012906572450014X, Impact Factor in 2022: 8.0

[158] Amir Javadpour, Hadi Zavieh, Forough Jafari, Arun Kumar Sangaiah, Adam Slowik, „Enhanced Efficiency in Fog Computing: A Fuzzy Data-driven Machine Selection Strategy”, International Journal of Fuzzy Systems, Volume 26, pp. 368-389, 2024, doi: 10.1007/s40815-023-01605-y, Impact Factor in 2022: 4.3

[159] Xiaoping Zhao, Liwen Jiang, Adam Slowik, Zhenman Zhang, Yu Xue, „Evolving blocks by segmentation for neural architecture search”, Electronic Research Archive, Volume 32, Issue 3, pp. 2016-2032, 2024, doi: 10.3934/era.2024092, Impact Factor in 2022: 0.8

[160] Wen Xing, Adam Slowik, Dinesh Peter, „Edge-Cloud Computing Oriented Large-Scale Online Secure Music Education Mechanism Driven by Neural Networks”, Journal of Cloud Computing, Volume 13, Article number 55, 2024, doi: 10.1186/s13677-023-00555-y, Impact Factor in 2022: 4.0

 [161] Zhendong Song, Huiming Wu, Wei Chen, Adam Slowik, „Improving automatic segmentation of liver tumor images using a deep learning model”, Heliyon, Volume 10, Issue 7, Article ID: e28538, 2024, doi: 10.1016/j.heliyon.2024.e28538, Impact Factor in 2022: 4.0

[162] Adam Slowik, Krzysztof Cpalka, Yu Xue, Aneta Hapka, „An efficient approach to parameter extraction of photovoltaic cell models using a new population-based algorithm”, Applied Energy, Volume 364, Article ID: 123208, 2024, doi: 10.1016/j.apenergy.2024.123208, Impact Factor in 2022: 11.2

[163] Jianhui Lv, Bo Yi, Adam Slowik, Peichen Li, Jiahao Chen, „VNF Constituted Consumer Application Preference for High Quality Service Provision in IoT”, IEEE Transactions on Consumer Electronics, Volume 70, Number 1, pp. 1071-1079, 2024, doi: 10.1109/TCE.2023.3319328, Impact Factor in 2022: 4.3

[164] Adam Slowik, Dorin Moldovan, „Multi-Objective Plum Tree Algorithm and Machine Learning for Heating and Cooling Load Prediction”, Energies, Volume 17, Issue 12, Article ID: 3054, 2024, doi: 10.3390/en17123054, Impact Factor in 2022: 3.2

[165] Walaa H. El-Ashmawi, Adam Slowik, Ahmed F. Ali, „An effective fitness dependent optimizer algorithm for edge server allocation in mobile computing”, Soft Computing, Volume 28, pp. 6855-6877, 2024, doi: 10.1007/s00500-023-09582-y, Impact Factor in 2023: 3.1

[166] Benxue Lu, Kaizhou Gao, Yaxian Ren, Dachao Li, Adam Slowik, „Combining meta-heuristics and Q-learning for scheduling lot-streaming hybrid flow shops with consistent sublots”, Swarm and Evolutionary Computation, Volume 91, Article ID: 101731, December 2024, doi: 10.1016/j.swevo.2024.101731, Impact Factor 2023: 8.2

[167] Fenglei Wang, Adam Slowik, „AI-Empowered Consumer Behavior Analysis for Trustworthy Track Recommendation over Musical Dance Electronic Products”, Heliyon, Volume 10, Issue 18, Article ID: e37633, September 30, 2024, doi: 10.1016/j.heliyon.2024.e37633, Impact Factor in 2023: 3.4

[168] Qianyao Zhu, Kaizhou Gao, Wuze Huang, Zhenfang Ma, Adam Slowik, „Q-Learning-Assisted Meta-heuristics for Scheduling Distributed Hybrid Flow Shop Problems”, CMC-Computers, Materials & Continua, Volume 80, Number 3, pp. 3573-3589, 2024, doi: 10.32604/cmc.2024.055244, Impact Factor in 2023: 2.0

[169] Jianhui Lv, Byung-Gyu Kim, Adam Slowik, B.D. Parameshachari, Saru Kumari, Chien-Ming Chen, Keqin Li, „ERLNEIL-MDP: Evolutionary Reinforcement Learning with Novelty-Driven Exploration for Medical Data Processing”, Swarm and Evolutionary Computation, Volume 91, Article ID: 101769, 2024, doi: 10.1016/j.swevo.2024.101769, Impact Factor in 2023: 8.2

[170] Xin Wang, Jianhui Lv, Adam Slowik, Byung-Gyu Kim, B. D. Parameshachari, Keqin Li, Gang Feng, „Augmented Intelligence of Things for Priority-Aware Task Offloading in Vehicular Edge Computing”, IEEE Internet of Things Journal, Volume 11, Number 22, pp. 36002-36013, 2024, doi: 10.1109/JIOT.2024.3408157, Impact Factor in 2023: 8.2

[171] Ahmed M. Ali, Adam Słowik, Ibrahim M. Hezam, Mohamed Abdel-Basset, „Sustainable smart system for vegetables plant disease detection: Four vegetable case studies”, Computers and Electronics in Agriculture, Volume 227, Part 2, Article ID: 109672, 2024, doi: 10.1016/j.compag.2024.109672, Impact Factor in 2023: 7.7

[172] Hongxin Zhao, Byung-Gyu Kim, Adam Slowik, Daohua Pan, „Temporal–spatial correlation and graph attention-guided network for micro-expression recognition in English learning livestreams”, Discover Computing, Volume 27, Article number 47, 2024, doi: 10.1007/s10791-024-09477-y

[173] Xin Wang, Jianhui Lv, Byung-Gyu Kim, Carsten Maple, B. D. Parameshachari, Adam Slowik, Keqin Li, „Generative Adversarial Privacy for Multimedia Analytics Across the IoT-Edge Continuum”, IEEE Transactions on Cloud Computing, Volume 12, Issue 4, pp. 1260-1272, 2024, doi: 10.1109/TCC.2024.3459789, Impact Factor in 2023: 5.3

[174] Ruixue Zhang, Hui Yu, Adam Slowik, Kaizhou Gao, „Q-learning Based Meta-Heuristics for Scheduling Bi-Objective Surgery Problems with Setup Time„, Complex System Modeling and Simulation, Volume 4, Number 4, pp. 321-338, 2024, doi:  10.23919/CSMS.2024.0021

[175] Xin Wang, Jianhui Lv, Adam Slowik, B. D. Parameshachari, Keqin Li, Chien-Ming Chen, Saru Kumari, „DLLF-2EN: Energy-Efficient Next Generation Mobile Network with Deep Learning-Based Load Forecasting”, IEEE Transactions on Network and Service Management, Volume 21, Issue 6, pp. 6515-6526, 2024, doi: 10.1109/TNSM.2024.3445369, Impact Factor in 2023: 4.7