Most cited papers in Advanced Algorithms and Applications
What are the most cited papers in Advanced Algorithms and Applications?
The most cited paper in Advanced Algorithms and Applications is "Particle swarm optimization" (Riccardo Poli, James C. Kennedy, Tim Blackwell, 2007), with 21,401 citations. Next come "Dynamic programming algorithm optimization for spoken word recognition" (6,722) and "Particle swarm optimization: developments, applications and resources" (4,324).
Showing 50 of 99 papers. Every paper with more than 291 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Particle swarm optimization Riccardo Poli, James C. Kennedy, Tim Blackwell · Swarm Intelligence | 31 Jul 2007 | 21,401 |
| 2 | Dynamic programming algorithm optimization for spoken word recognition Hiroaki Sakoe, Seibi Chiba · IEEE Transactions on Acoustics Speech and Signal Processing | Feb 1978 | 6,722 |
| 3 | Particle swarm optimization: developments, applications and resources Eberhart, Yuhui Shi | 2001 | 4,324 |
| 4 | Parameter selection in particle swarm optimization Yuhui Shi, Russell C. Eberhart · Lecture notes in computer science | 1998 | 3,541 |
| 5 | Particle swarm optimization algorithm: an overview Dongshu Wang, Dapei Tan, Lei Liu · Soft Computing | 17 Jan 2017 | 3,333 |
| 6 | Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients Asanga Ratnaweera, Saman Kumara Halgamuge, Heather C. Watson · IEEE Transactions on Evolutionary Computation | Jun 2004 | 3,042 |
| 7 | Fuzzy basis functions, universal approximation, and orthogonal least-squares learning L.-X. Wang, Jerry M. Mendel · IEEE Transactions on Neural Networks | 1992 | 2,802 |
| 8 | Support vector machine in machine condition monitoring and fault diagnosis Achmad Widodo, Bo‐Suk Yang · Mechanical Systems and Signal Processing | 16 Jan 2007 | 1,645 |
| 9 | Particle Swarm Optimization: A Comprehensive Survey Tareq M. Shami, Ayman A. El‐Saleh, Mohammed Alswaitti et al. · IEEE Access | 2022 | 1,420 |
| 10 | Working Set Selection Using Second Order Information for Training Support Vector Machines Rong-En Fan, Pai-Hsuen Chen, Chih‐Jen Lin · Journal of Machine Learning Research | Dec 2005 | 1,412 |
| 11 | Application of support vector machines in financial time series forecasting Francis E. H. Tay, Lijuan Cao · Omega | Aug 2001 | 1,270 |
| 12 | An introductory survey of fuzzy control Michio Sugeno · Information Sciences | Jul 1985 | 1,184 |
| 13 | A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications Yudong Zhang, Shuihua Wang, Genlin Ji · Mathematical Problems in Engineering | 2015 | 1,167 |
| 14 | An introduction to Γ-convergence Gianni Dal Maso · CERN Document Server (European Organization for Nuclear Research) | 1993 | 1,152 |
| 15 | Forecasting stock market movement direction with support vector machine Wei Huang, Yoshiteru Nakamori, Shouyang Wang · Computers & Operations Research | 30 May 2004 | 1,128 |
| 16 | On the usage of differential evolution for function optimization Rainer Storn | 23 Dec 2002 | 1,102 |
| 17 | Fuzzy adaptive particle swarm optimization Yuhui Shi, R.C. Eberhart | 13 Nov 2002 | 1,077 |
| 18 | Cuckoo search: recent advances and applications Xin‐She Yang, Suash Deb · Neural Computing and Applications | 7 Mar 2013 | 1,071 |
| 19 | Support vector machine with adaptive parameters in financial time series forecasting Leilei Cao, Francis E. H. Tay · IEEE Transactions on Neural Networks | Nov 2003 | 1,017 |
| 20 | A Review on Representative Swarm Intelligence Algorithms for Solving Optimization Problems: Applications and Trends Jun Tang, Gang Liu, Qingtao Pan · IEEE/CAA Journal of Automatica Sinica | 27 Jul 2021 | 994 |
| 21 | Improved particle swarm optimization combined with chaos Bo Liu, Ling Wang, Yihui Jin et al. · Chaos Solitons & Fractals | 21 Feb 2005 | 950 |
| 22 | Particle swarm optimization for parameter determination and feature selection of support vector machines Shih-Wei Lin, Kuo‐Ching Ying, Shih‐Chieh Chen et al. · Expert Systems with Applications | 2 Oct 2007 | 910 |
| 23 | Self-learning fuzzy controllers based on temporal backpropagation Jyh‐Shing Roger Jang · IEEE Transactions on Neural Networks | 1992 | 907 |
| 24 | An optimizing BP neural network algorithm based on genetic algorithm Shifei Ding, Chunyang Su, Junzhao Yu · Artificial Intelligence Review | 17 Feb 2011 | 809 |
| 25 | Development and Application of Artificial Neural Network Yuchen Wu, Junwen Feng · Wireless Personal Communications | 30 Dec 2017 | 802 |
| 26 | Principal Component Analysis Based on L1-Norm Maximization Nojun Kwak · IEEE Transactions on Pattern Analysis and Machine Intelligence | 24 Jul 2008 | 795 |
| 27 | Analysis of Particle Swarm Optimization Algorithm Bai Qing-hai · Computer and Information Science | 15 Jan 2010 | 732 |
| 28 | An Overview of Variants and Advancements of PSO Algorithm Meetu Jain, Vibha Saihjpal, Narinder Pal Singh et al. · Applied Sciences | 23 Aug 2022 | 722 |
| 29 | Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey Derviş Karaboğa, Ebubekir Kaya · Artificial Intelligence Review | 3 Jan 2018 | 720 |
| 30 | A global search strategy of quantum-behaved particle swarm optimization Jun Jie Sun, Wenbo Xu, Feng Bin | 6 Jul 2005 | 716 |
| 31 | Brief Introduction of Back Propagation (BP) Neural Network Algorithm and Its Improvement Jing Li, Jihang Cheng, Jingyuan Shi et al. · Advances in intelligent and soft computing | 2012 | 699 |
| 32 | Face recognition with radial basis function (RBF) neural networks Meng Joo Er, Shiqian Wu, Juwei Lu et al. · IEEE Transactions on Neural Networks | May 2002 | 670 |
| 33 | Artificial intelligence for the modeling and control of combustion processes: a review Soteris A. Kalogirou · Progress in Energy and Combustion Science | 2003 | 645 |
| 34 | Least squares twin support vector machines for pattern classification Manoj Kumar, Mahesh Gopal · Expert Systems with Applications | 2 Oct 2008 | 643 |
| 35 | A new hybrid PSOGSA algorithm for function optimization Seyedali Mirjalili, Siti Zaiton Mohd Hashim | Dec 2010 | 641 |
| 36 | Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE Xiaofeng Yuan, Biao Huang, Yalin Wang et al. · IEEE Transactions on Industrial Informatics | 26 Feb 2018 | 639 |
| 37 | Nonlinear principal component analysis—Based on principal curves and neural networks Diya Dong, Thomas J. McAvoy · Computers & Chemical Engineering | 1996 | 631 |
| 38 | A modified artificial bee colony algorithm Weifeng Gao, Sanyang Liu · Computers & Operations Research | 26 Jun 2011 | 611 |
| 39 | A New Bio-inspired Algorithm: Chicken Swarm Optimization Xian-Bing Meng, Yu Liu, Xiao‐Zhi Gao et al. · Lecture notes in computer science | 2014 | 594 |
| 40 | Improvements on Twin Support Vector Machines Yuan‐Hai Shao, Chunhua Zhang, Xiaobo Wang et al. · IEEE Transactions on Neural Networks | 9 May 2011 | 581 |
| 41 | Inertia Weight strategies in Particle Swarm Optimization Jagdish Chand Bansal, Poonam Singh, Mukesh Saraswat et al. | Oct 2011 | 577 |
| 42 | Application of genetic algorithm-PLS for feature selection in spectral data sets Riccardo Leardi · Journal of Chemometrics | 2000 | 563 |
| 43 | Universal Approximation Capability of Broad Learning System and Its Structural Variations C. L. Philip Chen, Zhulin Liu, Shuang Feng · IEEE Transactions on Neural Networks and Learning Systems | 21 Sep 2018 | 558 |
| 44 | A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network Feng Yu, Xu Xiaozhong · Applied Energy | 23 Aug 2014 | 539 |
| 45 | Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation Nandar Lynn, Ponnuthurai Nagaratnam Suganthan · Swarm and Evolutionary Computation | 23 Jun 2015 | 519 |
| 46 | Comparisons Among Clustering Techniques for Electricity Customer Classification Gianfranco Chicco, Roberto Napoli, Federico Piglione · IEEE Transactions on Power Systems | May 2006 | 514 |
| 47 | Adaptive neural control of MIMO nonlinear state time-varying delay systems with unknown dead-zones and gain signs T.P. Zhang, Shuzhi Sam Ge · Automatica | 30 Apr 2007 | 511 |
| 48 | Training v-Support Vector Classifiers: Theory and Algorithms Chih-Chung Chang, Chih‐Jen Lin · Neural Computation | Sep 2001 | 504 |
| 49 | Binary Optimization Using Hybrid Grey Wolf Optimization for Feature Selection Qasem Al-Tashi, Said Jadid Abdulkadir, Helmi Md Rais et al. · IEEE Access | 2019 | 490 |
| 50 | Forecasting stock indices with back propagation neural network Jianzhou Wang, Jujie Wang, Zhe George Zhang et al. · Expert Systems with Applications | 12 May 2011 | 489 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.