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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:

Improved Salp Swarm Algorithm with Space Transformation Search for Training Neural Network
Nibedan Panda, Santosh Kumar Majhi
Arabian Journal for Science and Engineering (2019) Vol. 45, Iss. 4, pp. 2743-2761
Closed Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Improved Salp Swarm Algorithm Based on Levy Flight and Sine Cosine Operator
Jianhua Zhang, Jie-Sheng Wang
IEEE Access (2020) Vol. 8, pp. 99740-99771
Open Access | Times Cited: 79
Large scale salp-based grey wolf optimization for feature selection and global optimization
Mohammed Qaraad, Souad Amjad, Nazar K. Hussein, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 11, pp. 8989-9014
Closed Access | Times Cited: 45
Review of Approaches to Minimise the Cost of Simulation-Based Optimisation for Liquid Composite Moulding Processes
Boon Xian Chai, Boris Eisenbart, Mostafa Nikzad, et al.
Materials (2023) Vol. 16, Iss. 24, pp. 7580-7580
Open Access | Times Cited: 39
Improved salp swarm algorithm based on Newton interpolation and cosine opposition-based learning for feature selection
Hongbo Zhang, Xiwen Qin, Xueliang Gao, et al.
Mathematics and Computers in Simulation (2024) Vol. 219, pp. 544-558
Closed Access | Times Cited: 13
Weight Optimization in Artificial Neural Network Training by Improved Monarch Butterfly Algorithm
Nebojša Bačanin, Timea Bezdan, Miodrag Živković, et al.
Lecture notes on data engineering and communications technologies (2021), pp. 397-409
Closed Access | Times Cited: 54
Adaptive Barebones Salp Swarm Algorithm with Quasi-oppositional Learning for Medical Diagnosis Systems: A Comprehensive Analysis
Jianfu Xia, Hongliang Zhang, Rizeng Li, et al.
Journal of Bionic Engineering (2022) Vol. 19, Iss. 1, pp. 240-256
Closed Access | Times Cited: 30
Simulation-based optimisation for injection configuration design of liquid composite moulding processes: A review
Boon Xian Chai, Boris Eisenbart, Mostafa Nikzad, et al.
Composites Part A Applied Science and Manufacturing (2021) Vol. 149, pp. 106540-106540
Closed Access | Times Cited: 34
Wireless Sensor Networks Localization by Improved Whale Optimization Algorithm
Nebojša Bačanin, Miloš Antonijević, Timea Bezdan, et al.
Algorithms for intelligent systems (2022), pp. 769-783
Closed Access | Times Cited: 26
An innovative quadratic interpolation salp swarm-based local escape operator for large-scale global optimization problems and feature selection
Mohammed Qaraad, Souad Amjad, Nazar K. Hussein, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 20, pp. 17663-17721
Closed Access | Times Cited: 25
An efficient salp swarm algorithm based on scale-free informed followers with self-adaption weight
Chao Wang, Ren-qian Xu, Lei Ma, et al.
Applied Intelligence (2022) Vol. 53, Iss. 2, pp. 1759-1791
Closed Access | Times Cited: 23
Predicting Hydropower Production Using Deep Learning CNN-ANN Hybridized with Gaussian Process Regression and Salp Algorithm
Mohammad Ehtearm, Hossein Ghayoumi Zadeh, Akram Seifi, et al.
Water Resources Management (2023) Vol. 37, Iss. 9, pp. 3671-3697
Closed Access | Times Cited: 13
Improved spotted hyena optimizer with space transformational search for training pi‐sigma higher order neural network
Nibedan Panda, Santosh Kumar Majhi
Computational Intelligence (2020) Vol. 36, Iss. 1, pp. 320-350
Closed Access | Times Cited: 38
Solving traveling salesman problem using hybridization of rider optimization and spotted hyena optimization algorithm
M. Murali Krishna, Nibedan Panda, Santosh Kumar Majhi
Expert Systems with Applications (2021) Vol. 183, pp. 115353-115353
Closed Access | Times Cited: 31
Quantum-inspired binary chaotic salp swarm algorithm (QBCSSA)-based dynamic task scheduling for multiprocessor cloud computing systems
Kaushik Mishra, Rosy Pradhan, Santosh Kumar Majhi
The Journal of Supercomputing (2021) Vol. 77, Iss. 9, pp. 10377-10423
Closed Access | Times Cited: 28
A Hybrid Approach of Spotted Hyena Optimization Integrated with Quadratic Approximation for Training Wavelet Neural Network
Nibedan Panda, Santosh Kumar Majhi, Rosy Pradhan
Arabian Journal for Science and Engineering (2022) Vol. 47, Iss. 8, pp. 10347-10363
Open Access | Times Cited: 19
Solar radiation prediction using improved soft computing models for semi-arid, slightly-arid and humid climates
Hailong Huang, Shahab S. Band, Hojat Karami, et al.
Alexandria Engineering Journal (2022) Vol. 61, Iss. 12, pp. 10631-10657
Open Access | Times Cited: 19
Multiprocessor Task Scheduling Optimization for Cyber-Physical System Using an Improved Salp Swarm Optimization Algorithm
Biswaranjan Acharya, Sucheta Panda, Niranjan Kumar Ray
SN Computer Science (2024) Vol. 5, Iss. 1
Closed Access | Times Cited: 4
A Novel SSA Tuned PI-TDF Control Scheme for Mitigation of Frequency Excursions in Hybrid Power System
Shilpam Malik, Sathans Suhag
Smart Science (2020) Vol. 8, Iss. 4, pp. 202-218
Closed Access | Times Cited: 29
Oppositional salp swarm algorithm with mutation operator for global optimization and application in training higher order neural networks
Nibedan Panda, Santosh Kumar Majhi
Multimedia Tools and Applications (2021) Vol. 80, Iss. 28-29, pp. 35415-35439
Closed Access | Times Cited: 25
Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy
Mohammad Ehteram, Fatemeh Barzegari Banadkooki, Chow Ming Fai, et al.
Energy Reports (2021) Vol. 7, pp. 3703-3725
Open Access | Times Cited: 24
Large-Scale Competitive Learning-Based Salp Swarm for Global Optimization and Solving Constrained Mechanical and Engineering Design Problems
Mohammed Qaraad, Abdussalam Aljadania, Mostafa A. Elhosseini
Mathematics (2023) Vol. 11, Iss. 6, pp. 1362-1362
Open Access | Times Cited: 9
Improved Salp Swarm Algorithm with Simulated Annealing for Solving Engineering Optimization Problems
Qing Duan, Lu Wang, Hongwei Kang, et al.
Symmetry (2021) Vol. 13, Iss. 6, pp. 1092-1092
Open Access | Times Cited: 20
Addressing constrained engineering problems and feature selection with a time-based leadership salp-based algorithm with competitive learning
Mohammed Qaraad, Souad Amjad, Nazar K. Hussein, et al.
Journal of Computational Design and Engineering (2022) Vol. 9, Iss. 6, pp. 2235-2270
Closed Access | Times Cited: 14
Improved Salp Swarm Optimization Algorithm: Application in Feature Weighting for Blind Modulation Identification
Sarra Ben Chaabane, Akram Belazi, Sofiane Kharbech, et al.
Electronics (2021) Vol. 10, Iss. 16, pp. 2002-2002
Open Access | Times Cited: 16
Comparing SSALEO as a Scalable Large Scale Global Optimization Algorithm to High-Performance Algorithms for Real-World Constrained Optimization Benchmark
Mohammed Qaraad, Souad Amjad, Nazar K. Hussein, et al.
IEEE Access (2022) Vol. 10, pp. 95658-95700
Open Access | Times Cited: 12
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