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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 hybrid fuzzy time series model based on granular computing for stock price forecasting
Mu‐Yen Chen, Bo-Tsuen Chen
Information Sciences (2014) Vol. 294, pp. 227-241
Closed Access | Times Cited: 218

Showing 1-25 of 218 citing articles:

Machine learning techniques and data for stock market forecasting: A literature review
Mahinda Mailagaha Kumbure, Christoph Lohrmann, Pasi Luukka, et al.
Expert Systems with Applications (2022) Vol. 197, pp. 116659-116659
Open Access | Times Cited: 301
Systematic analysis and review of stock market prediction techniques
Dattatray P. Gandhmal, Kumar Kannan
Computer Science Review (2019) Vol. 34, pp. 100190-100190
Closed Access | Times Cited: 243
Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model
Antonio Rafael Sabino Parmezan, Vinícius M. A. Souza, Gustavo E. A. P. A. Batista
Information Sciences (2019) Vol. 484, pp. 302-337
Closed Access | Times Cited: 241
A novel graph convolutional feature based convolutional neural network for stock trend prediction
Wei Chen, Manrui Jiang, Wei-Guo Zhang, et al.
Information Sciences (2020) Vol. 556, pp. 67-94
Closed Access | Times Cited: 218
Big Data Driven Marine Environment Information Forecasting: A Time Series Prediction Network
Jiabao Wen, Jiachen Yang, Bin Jiang, et al.
IEEE Transactions on Fuzzy Systems (2020) Vol. 29, Iss. 1, pp. 4-18
Closed Access | Times Cited: 154
Fine-tuned support vector regression model for stock predictions
Ranjan Kumar Dash, Tu N. Nguyen, Korhan Cengiz, et al.
Neural Computing and Applications (2021) Vol. 35, Iss. 32, pp. 23295-23309
Closed Access | Times Cited: 122
A new fuzzy time series forecasting model combined with ant colony optimization and auto-regression
Qisen Cai, Defu Zhang, Wei Zheng, et al.
Knowledge-Based Systems (2014) Vol. 74, pp. 61-68
Closed Access | Times Cited: 164
Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis
Ranjeeta Bisoi, P.K. Dash, Ajaya Kumar Parida
Applied Soft Computing (2018) Vol. 74, pp. 652-678
Closed Access | Times Cited: 139
A hybrid fuzzy time series forecasting model based on granular computing and bio-inspired optimization approaches
Pritpal Singh, Gaurav Dhiman
Journal of Computational Science (2018) Vol. 27, pp. 370-385
Closed Access | Times Cited: 130
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
Fuzzy time series forecasting method based on hesitant fuzzy sets
Kamlesh Bisht, Sanjay Kumar
Expert Systems with Applications (2016) Vol. 64, pp. 557-568
Closed Access | Times Cited: 114
A novel forecasting method based on multi-order fuzzy time series and technical analysis
Furong Ye, Liming Zhang, Defu Zhang, et al.
Information Sciences (2016) Vol. 367-368, pp. 41-57
Closed Access | Times Cited: 109
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
An Experimental Review on Deep Learning Architectures for Time Series Forecasting
Pedro Lara-Benítez, Manuel Carranza-García, José C. Riquelme
International Journal of Neural Systems (2020) Vol. 31, Iss. 03, pp. 2130001-2130001
Open Access | Times Cited: 99
Online ensemble learning with abstaining classifiers for drifting and noisy data streams
Bartosz Krawczyk, Alberto Cano
Applied Soft Computing (2017) Vol. 68, pp. 677-692
Closed Access | Times Cited: 93
An intelligent pattern recognition model for supporting investment decisions in stock market
Tai-Liang Chen, Fengyu Chen
Information Sciences (2016) Vol. 346-347, pp. 261-274
Closed Access | Times Cited: 91
Long-term forecasting of time series based on linear fuzzy information granules and fuzzy inference system
Xiyang Yang, Fusheng Yu, Witold Pedrycz
International Journal of Approximate Reasoning (2016) Vol. 81, pp. 1-27
Open Access | Times Cited: 89
A new procedure in stock market forecasting based on fuzzy random auto-regression time series model
Riswan Efendi, Nureize Arbaiy, Mustafa Mat Deris
Information Sciences (2018) Vol. 441, pp. 113-132
Open Access | Times Cited: 86
Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting
Yaoli Wang, Lipo Wang, Fangjun Yang, et al.
Information Sciences (2020) Vol. 547, pp. 1066-1079
Closed Access | Times Cited: 84
Generalized exponential autoregressive models for nonlinear time series: Stationarity, estimation and applications
Guangyong Chen, Min Gan, Guolong Chen
Information Sciences (2018) Vol. 438, pp. 46-57
Closed Access | Times Cited: 83
Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia
Naizhuo Zhao, Katia Charland, Mabel Carabalí, et al.
PLoS neglected tropical diseases (2020) Vol. 14, Iss. 9, pp. e0008056-e0008056
Open Access | Times Cited: 76
FQTSFM: A fuzzy-quantum time series forecasting model
Pritpal Singh
Information Sciences (2021) Vol. 566, pp. 57-79
Closed Access | Times Cited: 59
A Comparative Study of Forecasting Electricity Consumption Using Machine Learning Models
Madeline Pe, Yee Ser, Ganeshsree Selvachandran, et al.
Mathematics (2022) Vol. 10, Iss. 8, pp. 1329-1329
Open Access | Times Cited: 37
Stock index forecasting based on multivariate empirical mode decomposition and temporal convolutional networks
Yuan Yao, Zhaoyang Zhang, Yang Zhao
Applied Soft Computing (2023) Vol. 142, pp. 110356-110356
Closed Access | Times Cited: 29
Improved v -Support vector regression model based on variable selection and brain storm optimization for stock price forecasting
Jianzhou Wang, Ru Hou, Chen Wang, et al.
Applied Soft Computing (2016) Vol. 49, pp. 164-178
Closed Access | Times Cited: 84
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