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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Bio-inspired computation: Where we stand and what's next
Javier Del Ser, Eneko Osaba, Daniel Molina, et al.
Swarm and Evolutionary Computation (2019) Vol. 48, pp. 220-250
Open Access | Times Cited: 526

Showing 1-25 of 526 citing articles:

An improved grey wolf optimizer for solving engineering problems
Mohammad H. Nadimi-Shahraki, Shokooh Taghian, Seyedali Mirjalili
Expert Systems with Applications (2020) Vol. 166, pp. 113917-113917
Closed Access | Times Cited: 800
A survey on new generation metaheuristic algorithms
Tansel Dökeroğlu, Ender Sevinç, Tayfun Küçükyılmaz, et al.
Computers & Industrial Engineering (2019) Vol. 137, pp. 106040-106040
Closed Access | Times Cited: 694
Beluga whale optimization: A novel nature-inspired metaheuristic algorithm
Changting Zhong, Gang Li, Zeng Meng
Knowledge-Based Systems (2022) Vol. 251, pp. 109215-109215
Closed Access | Times Cited: 476
Particle Swarm Optimization
Xin‐She Yang
Elsevier eBooks (2021), pp. 111-121
Closed Access | Times Cited: 367
Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application
Essam H. Houssein, Ahmed G. Gad, Kashif Hussain, et al.
Swarm and Evolutionary Computation (2021) Vol. 63, pp. 100868-100868
Closed Access | Times Cited: 321
Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey
Khan Muhammad, Salman Khan, Javier Del Ser, et al.
IEEE Transactions on Neural Networks and Learning Systems (2020) Vol. 32, Iss. 2, pp. 507-522
Closed Access | Times Cited: 308
A better balance in metaheuristic algorithms: Does it exist?
Bernardo Morales-Castañeda, Daniel Zaldívar, Erik Cuevas, et al.
Swarm and Evolutionary Computation (2020) Vol. 54, pp. 100671-100671
Closed Access | Times Cited: 280
Task Scheduling in Cloud Computing based on Meta-heuristics: Review, Taxonomy, Open Challenges, and Future Trends
Essam H. Houssein, Ahmed G. Gad, Yaser M. Wazery, et al.
Swarm and Evolutionary Computation (2021) Vol. 62, pp. 100841-100841
Closed Access | Times Cited: 260
Population size in Particle Swarm Optimization
A. Piotrowski, Jarosław J. Napiórkowski, Agnieszka E. Piotrowska
Swarm and Evolutionary Computation (2020) Vol. 58, pp. 100718-100718
Open Access | Times Cited: 259
A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems
Eneko Osaba, Esther Villar-Rodríguez, Javier Del Ser, et al.
Swarm and Evolutionary Computation (2021) Vol. 64, pp. 100888-100888
Closed Access | Times Cited: 253
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
J. M. Górriz, Javier Ramı́rez, Andrés Ortíz, et al.
Neurocomputing (2020) Vol. 410, pp. 237-270
Open Access | Times Cited: 235
An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges
Kanchan Rajwar, Kusum Deep, Swagatam Das
Artificial Intelligence Review (2023) Vol. 56, Iss. 11, pp. 13187-13257
Open Access | Times Cited: 220
Spiking Neural Networks and online learning: An overview and perspectives
Jesús L. Lobo, Javier Del Ser, Albert Bifet, et al.
Neural Networks (2019) Vol. 121, pp. 88-100
Open Access | Times Cited: 217
An optimized model based on convolutional neural networks and orthogonal learning particle swarm optimization algorithm for plant diseases diagnosis
Ashraf Darwish, Dalia Ezzat, Aboul Ella Hassanien
Swarm and Evolutionary Computation (2019) Vol. 52, pp. 100616-100616
Closed Access | Times Cited: 216
A survey on data‐efficient algorithms in big data era
Amina Adadi
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 215
MTDE: An effective multi-trial vector-based differential evolution algorithm and its applications for engineering design problems
Mohammad H. Nadimi-Shahraki, Shokooh Taghian, Seyedali Mirjalili, et al.
Applied Soft Computing (2020) Vol. 97, pp. 106761-106761
Closed Access | Times Cited: 198
Multiobjective Evolution of Fuzzy Rough Neural Network via Distributed Parallelism for Stock Prediction
Bin Cao, Jianwei Zhao, Zhihan Lv, et al.
IEEE Transactions on Fuzzy Systems (2020) Vol. 28, Iss. 5, pp. 939-952
Closed Access | Times Cited: 193
Boosted mutation-based Harris hawks optimizer for parameters identification of single-diode solar cell models
Hussein Mohammed Ridha, Ali Asghar Heidari, Mingjing Wang, et al.
Energy Conversion and Management (2020) Vol. 209, pp. 112660-112660
Closed Access | Times Cited: 190
A review on computational intelligence for identification of nonlinear dynamical systems
Giuseppe Quaranta, Walter Lacarbonara, Sami F. Masri
Nonlinear Dynamics (2020) Vol. 99, Iss. 2, pp. 1709-1761
Closed Access | Times Cited: 167
An efficient hybrid sine-cosine Harris hawks optimization for low and high-dimensional feature selection
Kashif Hussain, Nabil Neggaz, William Zhu, et al.
Expert Systems with Applications (2021) Vol. 176, pp. 114778-114778
Closed Access | Times Cited: 157
A survey of swarm and evolutionary computing approaches for deep learning
Ashraf Darwish, Aboul Ella Hassanien, Swagatam Das
Artificial Intelligence Review (2019) Vol. 53, Iss. 3, pp. 1767-1812
Closed Access | Times Cited: 152
RFID Reader Anticollision Based on Distributed Parallel Particle Swarm Optimization
Bin Cao, Yu Gu, Zhihan Lv, et al.
IEEE Internet of Things Journal (2020) Vol. 8, Iss. 5, pp. 3099-3107
Closed Access | Times Cited: 137
Hybrid slime mould algorithm with adaptive guided differential evolution algorithm for combinatorial and global optimization problems
Essam H. Houssein, Mohamed A. Mahdy, Maude Josée Blondin, et al.
Expert Systems with Applications (2021) Vol. 174, pp. 114689-114689
Closed Access | Times Cited: 133
A prescription of methodological guidelines for comparing bio-inspired optimization algorithms
Antonio LaTorre, Daniel Molina, Eneko Osaba, et al.
Swarm and Evolutionary Computation (2021) Vol. 67, pp. 100973-100973
Open Access | Times Cited: 127
An Effective Feature Selection Model Using Hybrid Metaheuristic Algorithms for IoT Intrusion Detection
Saif S. Kareem, Reham R. Mostafa, Fatma A. Hashim, et al.
Sensors (2022) Vol. 22, Iss. 4, pp. 1396-1396
Open Access | Times Cited: 124
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