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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:

A combined robust fuzzy time series method for prediction of time series
Özge Cağcağ Yolcu, Hak‐Keung Lam
Neurocomputing (2017) Vol. 247, pp. 87-101
Open Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions
Nusrat Rouf, Majid Bashir Malik, Tasleem Arif, et al.
Electronics (2021) Vol. 10, Iss. 21, pp. 2717-2717
Open Access | Times Cited: 163
Stock Market Forecasting Using Computational Intelligence: A Survey
Gourav Kumar, Sanjeev Jain, Uday Pratap Singh
Archives of Computational Methods in Engineering (2020) Vol. 28, Iss. 3, pp. 1069-1101
Closed Access | Times Cited: 143
Application of a novel early warning system based on fuzzy time series in urban air quality forecasting in China
Jianzhou Wang, Hongmin Li, Haiyan Lu
Applied Soft Computing (2018) Vol. 71, pp. 783-799
Open Access | Times Cited: 120
Designing fuzzy time series forecasting models: A survey
Mahua Bose, Kalyani Mali
International Journal of Approximate Reasoning (2019) Vol. 111, pp. 78-99
Open Access | Times Cited: 106
FQTSFM: A fuzzy-quantum time series forecasting model
Pritpal Singh
Information Sciences (2021) Vol. 566, pp. 57-79
Closed Access | Times Cited: 59
A novel high order hesitant fuzzy time series forecasting by using mean aggregated membership value with support vector machine
Radha Mohan Pattanayak, H. S. Behera, Sibarama Panigrahi
Information Sciences (2023) Vol. 626, pp. 494-523
Closed Access | Times Cited: 26
A study on leading machine learning techniques for high order fuzzy time series forecasting
Sibarama Panigrahi, H. S. Behera
Engineering Applications of Artificial Intelligence (2019) Vol. 87, pp. 103245-103245
Closed Access | Times Cited: 67
A novel probabilistic intuitionistic fuzzy set based model for high order fuzzy time series forecasting
Radha Mohan Pattanayak, H. S. Behera, Sibarama Panigrahi
Engineering Applications of Artificial Intelligence (2020) Vol. 99, pp. 104136-104136
Closed Access | Times Cited: 62
A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting
Miguel Ángel Castán-Lascorz, P. Jiménez-Herrera, Alicia Troncoso, et al.
Information Sciences (2021) Vol. 586, pp. 611-627
Open Access | Times Cited: 52
Designing emergency flood evacuation plans using robust optimization and artificial intelligence
Soheyl Khalilpourazari, Seyed Hamid Reza Pasandideh
Journal of Combinatorial Optimization (2021) Vol. 41, Iss. 3, pp. 640-677
Closed Access | Times Cited: 41
Performance ratio prediction of photovoltaic pumping system based on grey clustering and second curvelet neural network
Bin Zhao, Yi Ren, Diankui Gao, et al.
Energy (2019) Vol. 171, pp. 360-371
Closed Access | Times Cited: 50
DERN: Deep Ensemble Learning Model for Short- and Long-Term Prediction of Baltic Dry Index
Imam Mustafa Kamal, Hyerim Bae, Sunghyun Sim, et al.
Applied Sciences (2020) Vol. 10, Iss. 4, pp. 1504-1504
Open Access | Times Cited: 45
Hierarchical temporal memory and recurrent neural networks for time series prediction: An empirical validation and reduction to multilayer perceptrons
Jakob Struye, Steven Latré
Neurocomputing (2019) Vol. 396, pp. 291-301
Closed Access | Times Cited: 43
A Hybrid Jaya-Pi-Sigma Model Using Length-Based Discretization Approach for Time Series Forecasting
Radha Mohan Pattanayak, M. V. Sangameswar, T. Pradhan, et al.
Lecture notes in networks and systems (2025), pp. 239-248
Closed Access
Developing a forecasting model for time series based on clustering and deep learning algorithms
Luan Nguyen-Huynh, Tai Vovan
Applied Soft Computing (2025), pp. 112977-112977
Closed Access
A New Approach for Time Series Prediction: Fuzzy Regression Network Functions
Mehmet Raci Aktoprak, Özge Cağcağ Yolcu
International Journal of Advances in Engineering and Pure Sciences (2025) Vol. 37, Iss. 1, pp. 36-52
Closed Access
High-Order Fuzzy Time Series Forecasting by Using Membership Values Along with Data and Support Vector Machine
Radha Mohan Pattanayak, Sibarama Panigrahi, H. S. Behera
Arabian Journal for Science and Engineering (2020) Vol. 45, Iss. 12, pp. 10311-10325
Closed Access | Times Cited: 37
A novel intuitionistic fuzzy time series prediction model with cascaded structure for financial time series
Özge Cağcağ Yolcu, Ufuk Yolcu
Expert Systems with Applications (2022) Vol. 215, pp. 119336-119336
Open Access | Times Cited: 21
Fuzzy time series model based on weighted association rule for financial market forecasting
Ching‐Hsue Cheng, Chung‐Hsi Chen
Expert Systems (2018) Vol. 35, Iss. 4
Closed Access | Times Cited: 33
A survey of time series forecasting from stochastic method to soft computing
Putriaji Hendikawati, Subanar Subanar, Abdurakhman Abdurakhman, et al.
Journal of Physics Conference Series (2020) Vol. 1613, Iss. 1, pp. 012019-012019
Open Access | Times Cited: 29
A new fuzzy time series forecasting model based on clustering technique and normal fuzzy function
Luan Nguyen-Huynh, Tai Vovan
Knowledge and Information Systems (2023) Vol. 65, Iss. 8, pp. 3489-3509
Closed Access | Times Cited: 8
Stock index forecasting: A new fuzzy time series forecasting method
Hao Wu, Haiming Long, Yue Wang, et al.
Journal of Forecasting (2020) Vol. 40, Iss. 4, pp. 653-666
Closed Access | Times Cited: 21
A novel two-stage combination model for tourism demand forecasting
Mingming Hu, Haifeng Yang, Doris Chenguang Wu, et al.
Tourism Economics (2024) Vol. 30, Iss. 8, pp. 1925-1950
Closed Access | Times Cited: 2
A Tutorial on Fuzzy Time Series Forecasting Models: Recent Advances and Challenges
Patrícia de Oliveira e Lucas, Omid Orang, Petrônio Cândido de Lima e Silva, et al.
Learning and Nonlinear Models (2022) Vol. 19, Iss. 2, pp. 29-50
Open Access | Times Cited: 11
A Non-Probabilistic Neutrosophic Entropy-Based Method For High-Order Fuzzy Time-Series Forecasting
Radha Mohan Pattanayak, H. S. Behera, Sibarama Panigrahi
Arabian Journal for Science and Engineering (2021) Vol. 47, Iss. 2, pp. 1399-1421
Closed Access | Times Cited: 13
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