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A Competitive Parkinson-Based Binary Volleyball Premier League Metaheuristic Algorithm for Feature Selection

   | 30 nov 2023
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Naka, E., V. Guliashki. B-VPL: A Binary Volleyball Premier League Optimization Algorithm for Feature Selection. – In: Proc. of 29th International Conference on Systems, Signals and Image Processing (IWSSIP’22) – IEEE Xplore, 2022, pp. 1-4. Search in Google Scholar

Pudjihartono, N, T. Fadason, A. W. Kempa-Liehr, J. M. O’Sullivan. A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction. – Frontiers in Bioinformatics, Vol. 2, 2022, pp. 1-17. Search in Google Scholar

Venkatesh, B., J. Anuradha. A Review of Feature Selection and Its Methods – Cybernetics and Information Technologies, Vol. 19, 2019, No 1, pp. 3-26. Search in Google Scholar

Remeseiro, B., V. Bolon-Canedo. A Review of Feature Selection Methods in Medical Applications. – Computers in Biology and Medicine, Vol. 112, 2019, pp. 1-35. Search in Google Scholar

Liu, W., J. Wang. A Brief Survey on Nature-Inspired Metaheuristics for Feature Selection in Classification in This Decade. – In: Proc. of 16th IEEE International Conference on Networking, Sensing and Control (ICNSC’19) – IEEE Xplore, 2019, pp. 424-429. Search in Google Scholar

Sharma, M., P. Kaur. A Comprehensive Analysis of Nature-Inspired Meta-Heuristic Techniques for Feature Selection Problem. – Archives of Computational Methods in Engineering, Vol. 28, 2021, pp. 1103-1127. Search in Google Scholar

Agrawal, P., H. F. Abutarboush, T. Ganesh, A. W. Mohamed. Metaheuristic Algorithms on Feature Selection: A Survey of One Decade of Research (2009-2019) – IEEE Access, Vol. 9, 2021, pp. 26766-26791. Search in Google Scholar

Dokeroglu, T., A. Deniz, H. E. Kiziloz. A Comprehensive Survey on Recent Metaheuristics for Feature Selection. – Neurocomputing, Vol. 494, 2022, pp. 269-296. Search in Google Scholar

Sörensen, K., F. W. Glover. Metaheuristics. – In: S. I. Gass, M. C. Fu, Eds. Encyclopedia of Operations Research and Management Science. Boston, MA, Springer, 2013, pp. 960-970. Search in Google Scholar

Rajwar, K., K. Deep, S. Das. An Exhaustive Review of the Metaheuristic Algorithms for Search and Optimization: Taxonomy, Applications, and Open Challenges. – Artificial Intelligence Review, 2023, pp. 1-71. Search in Google Scholar

Crawford, B., R. Soto, G. Astorga, J. García, C. Castro, F. Paredes. Putting Continuous Metaheuristics to Work in Binary Search Spaces. – Complexity, Vol. 2017, 2017, pp. 1-19. Search in Google Scholar

Mirjalili, S., A. Lewis. S-Shaped vs. V-Shaped Transfer Functions for Binary Particle Swarm Optimization. – Swarm and Evolutionary Computation, Vol. 9, 2013, pp. 1-14. Search in Google Scholar

Beheshti, Z. A Novel x-Shaped Binary Particle Swarm Optimization. – Soft Computing, Vol. 25, 2021, pp. 3013-3042. Search in Google Scholar

Mirjalili, S., H. Zhang, S. Mirjalili, S. Chalup, N. Noman. A Novel U-Shaped Transfer Function for Binary Particle Swarm Optimisation. – In: A. Nagar, K. Deep, J. Bansal, K. Das, Eds. Soft Computing for Problem Solving 2019. – Advances in Intelligent Systems and Computing, Springer, Singapore, Vol. 1138, 2020, pp. 241-259. Search in Google Scholar

Wang, L., X. Wang, J. Fu, L. Zhen. A Novel Probability Binary Particle Swarm Optimization Algorithm and Its Application. – Journal of Software, Vol. 3, 2008, No 9, pp. 28-35. Search in Google Scholar

Too, J., A. R. Abdullah, N. MohdSaad. A New Quadratic Binary Harris Hawk Optimization for Feature Selection. – Electronics, Vol. 8, 2019, pp. 1-27. Search in Google Scholar

Nadimi-Shahraki, M. H., M. Banaie-Dezfouli, H. Zamani, S. Taghian, S. Mirjalili. B-MFO: A Binary Moth-Flame Optimization for Feature Selection from Medical Datasets. – Computers, Vol. 10, 2021, pp. 1-18. Search in Google Scholar

Kumar, V., D. Kumar, M. Kaur, D. Singh, S. A. Idris, H. Alshazly. A Novel Binary Seagull Optimizer and Its Application to Feature Selection Problem. – IEEE Access, Vol. 9, 2021, pp. 103481-103496. Search in Google Scholar

Jiang, Y., Q. Luo, Y. Wei, L. Abualigah, Y. Zhou. An Efficient Binary Gradient-Based Optimizer for Feature Selection. – Mathematical Biosciences and Engineering, Vol. 18, 2021, No 4, pp. 3813-3854. Search in Google Scholar

Emary, E., H. M. Zawbaa, A. E. Hassanien. Binary Ant Lion Approaches for Feature Selection. – Neurocomputing, Vol. 213, 2016, pp. 54-65. Search in Google Scholar

Turkoglu, B., S. A. Uymaz, E. Kaya. Binary Artificial Algae Algorithm for Feature Selection. – Applied Soft Computing, Vol. 120, 2022, pp. 1-19. Search in Google Scholar

Too, J., A. R. Abdullah. Binary Atom Search Optimisation Approaches for Feature Selection. – Connection Science, Vol. 32, 2020, No 4, pp. 406-430. Search in Google Scholar

Pan, J.-S., L. Yue, S.-C. Chu, P. Hu, B. Yan, H. Yang. Binary Bamboo Forest Growth Optimization Algorithm for Feature Selection. – Entropy, Vol. 25, 2013, pp. 1-25 Search in Google Scholar

Nssibi, M., G. Manita, O. Korbaa. Binary Giza Pyramids Construction for Feature Selection. – Procedia Computer Science, Vol. 192, 2021, pp. 676-687. Search in Google Scholar

Eluri, R. K., N. Devarakonda. Binary Golden Eagle Optimizer with Time-Varying Flight Length for Feature Selection. – Knowledge-Based Systems, Vol. 247, 2022, pp. 1-28. Search in Google Scholar

Agrawal, P., T. Ganesh, D. Oliva, A. W. Mohamed. S-Shaped and V-Shaped Gaining-Sharing Knowledge-Based Algorithm for Feature Selection. – Applied Intelligence, Vol. 52, 2022, pp. 81-112. Search in Google Scholar

Ghosh, K. K., R. Guha, S. K. Bera, N. Kumar, R. Sarkar. S-Shaped vs. V-Shaped Transfer Functions for Binary Manta Ray Foraging Optimization in Feature Selection Problem. – Neural Computing & Application, Vol. 33, 2021, pp. 11027-11041. Search in Google Scholar

Awadallah, M. A., A. I. Hammouri, M. A. Al-Beta, M. S. Braik, M. A. Elaziz. Binary Horse Herd Optimization Algorithm with Crossover Operators for Feature Selection. – Computers in Biology and Medicine, Vol. 141, 2022, pp. 105152. Search in Google Scholar

Moghdani, R., K. Salimifard. Volleyball Premier League Algorithm. – Applied Soft Computing, Vol. 64, 2018, pp. 161-185. Search in Google Scholar

Tizhoosh, H. R. Opposition-Based Learning: A New Scheme for Machine Intelligence. – In: Proc. of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, Vienna, Austria, 2005, pp. 695-701. Search in Google Scholar

Naka, E. K. Review of Metaheuristic Algorithms in Feature Selection Based on Parkinson Disease. – In: Proc. of 24th International Conference on Control Systems and Computer Science (CSCS’23) – IEEE Xplore, 2023, pp. 221-228. Search in Google Scholar

UCI Machine Learning Repository (Accessed in August 2022). https://archive.ics.uci.edu/datasets?search=parkinson Search in Google Scholar

HandPD Dataset, New HandPD Dataset (Accessed in 4 August 2022). https://wwwp.fc.unesp.br/~papa/pub/datasets/Handpd/ Search in Google Scholar

Parkinson’s Progression Markers Initiative (Accessed in 1 August 2022). https://www.ppmi-info.org Search in Google Scholar

Too, J. Ant Colony Optimization for Feature Selection. 2021 (Retrieved at 26/05/2022). https://www.mathworks.com/matlabcentral/fileexchange/80278-ant-colony-optimization-for-feature-selection?s_tid=srchtitle Search in Google Scholar

Heris, M. K. Artificial Bee Colony. 2015. https://yarpiz.com/297/ypea114-artificial-bee-colony Search in Google Scholar

Too, J., A. R. Abdullah. Binary Atom Search Optimisation Approaches for Feature Selection. – Connection Science, Vol. 32, 2020, No 4, pp. 406-430. Search in Google Scholar

Mirjalili, S., S. M. Mirjalili, X.-S. Y a n g. Binary Bat Algorithm. – Neural Computing & Applications, Vol. 25, 2014, pp. 663-681. Search in Google Scholar

Too, J., A. R. Abdullah, N. MohdSaad. Hybrid Binary Particle Swarm Optimization Differential Evolution-Based Feature Selection for EMG Signals Classification. – Axioms, Vol. 8, 2019, No 3, pp. 1-17. Search in Google Scholar

Too, J., S. Mirjalili. A Hyper Learning Binary Dragonfly Algorithm for Feature Selection: A COVID-19 Case Study. – Knowledge-Based Systems, Vol. 212, 2020, pp. 1-16. Search in Google Scholar

Heris, M. K. Firefly Algorithm (FA) in MATLAB. 2015. https://yarpiz.com/259/ypea112, retrieved in August 2022 Search in Google Scholar

Too, J., A. R. Abdullah, N. MohdSaad, N. M. Ali, W. Tee. A New Competitive Binary Grey Wolf Optimizer to Solve the Feature Selection Problem in EMG Signals Classification. – Computers, Vol. 7, 2018, No 4, pp. 1-18. Search in Google Scholar

Mirjalili, S. Moth-Flame Optimization Algorithm: A Novel Nature-Inspired Heuristic Paradigm. – Knowledge-Based Systems, Vol. 89, 2015, pp. 228-249. Search in Google Scholar

Too, J. Particle Swarm Optimization for Feature Selection, 2021, https://www.mathworks.com/matlabcentral/fileexchange/78802-particle-swarm-optimization-for-feature-selection?s_tid=prof_contriblnk Search in Google Scholar

Too, J. Salp Swarm Algorithm for Feature Selection. 2021. https://www.mathworks.com/matlabcentral/fileexchange/78913-salp-swarm-algorithm-for-feature-selection?s_tid=prof_contriblnk Search in Google Scholar

Too, J., A. R. Abdullah, N. M. Saad, N. M. Ali. Feature Selection Based on Binary Tree Growth Algorithm for the Classification of Myoelectric Signals. – Machines, Vol. 6, 2018, No 4, pp. 1-19. Search in Google Scholar

Mirjalili, S., A. Lewis. The Whale Optimization Algorithm. – Advances in Engineering Software, Vol. 95, 2016, pp. 51-67. DOI: 10.1016/j.advengsoft.2016.0. https://www.mathworks.com/matlabcentral/fileexchange/55667-the-whale-optimization-algorithm Search in Google Scholar

Too, J., S. Mirjalili. General Learning Equilibrium Optimizer: A New Feature Selection Method for Biological Data Classification. – Applied Artificial Intelligence, Vol. 35, 2021, No 3, pp. 247-263. Search in Google Scholar

Too, J., A. R. Abdullah. A New and Fast Rival Genetic Algorithm for Feature Selection. – The Journal of Supercomputing, Vol. 77, 2021, pp. 2844-2874. Search in Google Scholar

Too, J. Sine Cosine Algorithm for Feature Selection. 2021. https://www.mathworks.com/matlabcentral/fileexchange/80671-sine-cosine-algorithm-for-feature-selection?s_tid=prof_contriblnk, retrieved at 09/08/2022 Search in Google Scholar

Heris, M. K. Teaching-Learning-Based Optimization in MATLAB. 2015. https://yarpiz.com/83/ypea111-teaching-learning-based-optimization. Search in Google Scholar

Saremi, S., S. Mirjalili, A. Lewis. Grasshopper Optimization Algorithm: Theory and Application. – Advances in Engineering Software, Vol. 105, 2017, pp. 30-47. Search in Google Scholar

eISSN:
1314-4081
Lingua:
Inglese
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4 volte all'anno
Argomenti della rivista:
Computer Sciences, Information Technology