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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:

Computational Intelligence: An Introduction
Arya Yaghoubzadeh-Bavandpour, Omid Bozorg‐Haddad, Babak Zolghadr‐Asli, et al.
Studies in computational intelligence (2022), pp. 411-427
Closed Access | Times Cited: 113

Showing 1-25 of 113 citing articles:

Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art
Carlos A. Coello Coello, Margarita Reyes-Sierra
International Journal of Computational Intelligence Research (2006) Vol. 2, Iss. 3
Open Access | Times Cited: 1318
Granular computing: an introduction
Witold Pedrycz
(2002) Vol. 3, pp. 1349-1354
Open Access | Times Cited: 375
Self-adaptive Differential Evolution
Mahamed G. H. Omran, Ayed Salman, Andries P. Engelbrecht
Lecture notes in computer science (2005), pp. 192-199
Closed Access | Times Cited: 262
Efficient Population Utilization Strategy for Particle Swarm Optimizer
Sheng-Ta Hsieh, Tsung-Ying Sun, Chan-Cheng Liu, et al.
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (2008) Vol. 39, Iss. 2, pp. 444-456
Closed Access | Times Cited: 168
Tabu search for attribute reduction in rough set theory
Abdel-Rahman Hedar, Jue Wang, Masao Fukushima
Soft Computing (2007) Vol. 12, Iss. 9, pp. 909-918
Closed Access | Times Cited: 154
Granular clustering: a granular signature of data
Witold Pedrycz, A Bargiela
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (2002) Vol. 32, Iss. 2, pp. 212-224
Open Access | Times Cited: 161
An alternative differential evolution algorithm for global optimization
Ali Wagdy Mohamed, Hegazy Zaher Sabry, Motaz Khorshid
Journal of Advanced Research (2011) Vol. 3, Iss. 2, pp. 149-165
Open Access | Times Cited: 96
It really does matter how you normalize the branch distance in search‐based software testing
Andrea Arcuri
Software Testing Verification and Reliability (2011) Vol. 23, Iss. 2, pp. 119-147
Closed Access | Times Cited: 86
The comparison of multi-objective particle swarm optimization and NSGA II algorithm: applications in centrifugal pumps
Ahmad Nourbakhsh, Hamed Safikhani, Shahram Derakhshan
Engineering Optimization (2011) Vol. 43, Iss. 10, pp. 1095-1113
Closed Access | Times Cited: 83
Linguistic models and linguistic modeling
W. Pedryez, Athanasios V. Vasilakos
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (1999) Vol. 29, Iss. 6, pp. 745-757
Closed Access | Times Cited: 122
FORECASTING GOLD PRICE CHANGES BY USING ADAPTIVE NETWORK FUZZY INFERENCE SYSTEM
Abdolreza Yazdani–Chamzini, Siamak Haji Yakhchali, Diana Volungevičienė, et al.
Journal of Business Economics and Management (2012) Vol. 13, Iss. 5, pp. 994-1010
Open Access | Times Cited: 59
Multi-Objective Feature Subset Selection using Non-dominated Sorting Genetic Algorithm
Ayesha Khan, Abdul Rauf Baig
Journal of Applied Research and Technology (2015) Vol. 13, Iss. 1, pp. 145-159
Open Access | Times Cited: 59
Evolutionary fuzzy modeling
Witold Pedrycz, Marek Reformat
IEEE Transactions on Fuzzy Systems (2003) Vol. 11, Iss. 5, pp. 652-665
Closed Access | Times Cited: 83
Visualizing the computational intelligence field [Application Notes]
Nees Jan van Eck, Ludo Waltman, Jan van den Berg, et al.
IEEE Computational Intelligence Magazine (2006) Vol. 1, Iss. 4, pp. 6-10
Open Access | Times Cited: 68
Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?
Dimitar A. Dobchev, Mati Karelson
Expert Opinion on Drug Discovery (2016) Vol. 11, Iss. 7, pp. 627-639
Closed Access | Times Cited: 31
Comparing PSO structures to learn the game of checkers from zero knowledge
N. Franken, Andries P. Engelbrecht
(2004), pp. 234-241
Closed Access | Times Cited: 47
Cosmological parameter estimation using particle swarm optimization
J. Prasad, Tarun Souradeep
Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology (2012) Vol. 85, Iss. 12
Open Access | Times Cited: 31
Design of very thin wide band absorbers using modified local best particle swarm optimization
Somayyeh Chamaani, Seyed Abdullah Mirtaheri, Mahdi Aliyari Shoorehdeli
AEU - International Journal of Electronics and Communications (2007) Vol. 62, Iss. 7, pp. 549-556
Closed Access | Times Cited: 28
Flocking based approach for data clustering
Abbas Ahmadi, Fakhri Karray, Mohamed S. Kamel
Natural Computing (2009) Vol. 9, Iss. 3, pp. 767-791
Closed Access | Times Cited: 27
Measuring flow as concept for detecting game fun in the Pac-Man game
Nicola Beume, Holger Danielsiek, Christian Eichhorn, et al.
(2008), pp. 3448-3455
Closed Access | Times Cited: 27
Scatter Search for Rough Set Attribute Reduction
Jue Wang, Abdel-Rahman Hedar, Guihuan Zheng, et al.
(2009), pp. 531-535
Closed Access | Times Cited: 24
Pareto optimum control of a 2-DOF inverted pendulum using approximate feedback linearization and sliding mode control
Morteza Andalib Sahnehsaraei, M. J. Mahmoodabadi, Ahmad Bagheri
Transactions of the Institute of Measurement and Control (2013) Vol. 36, Iss. 4, pp. 496-505
Closed Access | Times Cited: 21
A hybrid water cycle-particle swarm optimization for solving the fuzzy underground water confined steady flow
Elsayed Badr, Horia Elgendy
Indonesian Journal of Electrical Engineering and Computer Science (2020) Vol. 19, Iss. 1, pp. 492-492
Open Access | Times Cited: 17
Fuzzy explicit marking for congestion control in differentiated services networks
Chrysostomos Chrysostomou, Andreas Pitsillides, G. Hadjipollas, et al.
(2004), pp. 312-319
Closed Access | Times Cited: 30
Use of aggregation pheromone density for image segmentation
Susmita Ghosh, Megha Kothari, Anindya Halder, et al.
Pattern Recognition Letters (2009) Vol. 30, Iss. 10, pp. 939-949
Closed Access | Times Cited: 21
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