IDEAS home Printed from https://ideas.repec.org/r/arx/papers/1401.1916.html
   My bibliography  Save this item

Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Mojtaba Sedighi & Hossein Jahangirnia & Mohsen Gharakhani & Saeed Farahani Fard, 2019. "A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine," Data, MDPI, vol. 4(2), pages 1-28, May.
  2. Feng Gao & Jie Song & Xueyan Shao, 2025. "Short-term interval-valued load forecasting with a combined strategy of iHW and multioutput machine learning," Annals of Operations Research, Springer, vol. 346(3), pages 2009-2033, March.
  3. Hu, Zhongyi & Bao, Yukun & Chiong, Raymond & Xiong, Tao, 2015. "Mid-term interval load forecasting using multi-output support vector regression with a memetic algorithm for feature selection," Energy, Elsevier, vol. 84(C), pages 419-431.
  4. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
  5. Kamil Kashif & Robert 'Slepaczuk, 2024. "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers 2406.18206, arXiv.org.
  6. Zhu, Mengrui & Xu, Hua & Wang, Minggang & Tian, Lixin, 2024. "Carbon price interval prediction method based on probability density recurrence network and interval multi-layer perceptron," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
  7. Tao XIONG & LI Chongguang & Yukun BAO, 2017. "An improved EEMD-based hybrid approach for the short-term forecasting of hog price in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(3), pages 136-148.
  8. Ma, Xuejiao & Wang, Yong & Wang, Chen, 2017. "Low-carbon development of China's thermal power industry based on an international comparison: Review, analysis and forecast," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 942-970.
  9. Fu, Hao & Lam, William H.K. & Shao, Hu & Kattan, Lina & Salari, Mostafa, 2022. "Optimization of multi-type traffic sensor locations for estimation of multi-period origin-destination demands with covariance effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
  10. Zaji, Amir Hossein & Bonakdari, Hossein & Khodashenas, Saeed Reza & Shamshirband, Shahaboddin, 2016. "Firefly optimization algorithm effect on support vector regression prediction improvement of a modified labyrinth side weir's discharge coefficient," Applied Mathematics and Computation, Elsevier, vol. 274(C), pages 14-19.
  11. Ha, Youngmin & Zhang, Hai, 2019. "Fast multi-output relevance vector regression," Economic Modelling, Elsevier, vol. 81(C), pages 217-230.
  12. Wang, Zicheng & Gao, Ruobin & Wang, Piao & Chen, Huayou, 2023. "A new perspective on air quality index time series forecasting: A ternary interval decomposition ensemble learning paradigm," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
  13. Huiyuan Wang & Ruiyuan Cao, 2025. "Deep Learning Quantile Regression for Interval‐Valued Data Prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(5), pages 1806-1825, August.
  14. Yang, Dongchuan & Guo, Ju-e & Sun, Shaolong & Han, Jing & Wang, Shouyang, 2022. "An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting," Applied Energy, Elsevier, vol. 306(PA).
  15. Avijit Duary & Md Sadikur Rahman & Amalesh Kumar Manna & Ali Akbar Shaikh, 2025. "Optimal policy of an interval production problem with variable demand and warranty policy via $$0\_1$$ 0 _ 1 parametrized optimization technique," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(9), pages 2967-2982, September.
  16. Gao, Tian & Niu, Dongxiao & Ji, Zhengsen & Sun, Lijie, 2022. "Mid-term electricity demand forecasting using improved variational mode decomposition and extreme learning machine optimized by sparrow search algorithm," Energy, Elsevier, vol. 261(PB).
  17. Xiong, Tao & Li, Chongguang & Bao, Yukun, 2017. "Interval-valued time series forecasting using a novel hybrid HoltI and MSVR model," Economic Modelling, Elsevier, vol. 60(C), pages 11-23.
  18. Mingyu Xu & Xin Lai & Yuying Zhang & Zongjun Li & Bohan Ouyang & Jingmiao Shen & Shiming Deng, 2024. "An Integrated Hog Supply Forecasting Framework Incorporating the Time-Lagged Piglet Feature: Sustainable Insights from the Hog Industry in China," Sustainability, MDPI, vol. 16(19), pages 1-24, September.
  19. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
  20. M. A. Ghorbani & R. Khatibi & V. Karimi & Zaher Mundher Yaseen & M. Zounemat-Kermani, 2018. "Learning from Multiple Models Using Artificial Intelligence to Improve Model Prediction Accuracies: Application to River Flows," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4201-4215, October.
  21. Hao, Peng & Guo, Junpeng, 2017. "Constrained center and range joint model for interval-valued symbolic data regression," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 106-138.
  22. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
  23. Kaike Sa Teles Rocha Alves & Rosangela Ballini & Eduardo Pestana de Aguiar, 2025. "Financial Series Forecasting: A New Fuzzy Inference System for Crisp Values and Interval-Valued Predictions," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3673-3721, June.
  24. Lanmei Wang & Yao Wang & Guibao Wang & Jianke Jia, 2020. "Near-field sound source localization using principal component analysis–multi-output support vector regression," International Journal of Distributed Sensor Networks, , vol. 16(4), pages 15501477209, April.
  25. Deo, Ravinesh C. & Ghorbani, Mohammad Ali & Samadianfard, Saeed & Maraseni, Tek & Bilgili, Mehmet & Biazar, Mustafa, 2018. "Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference station data," Renewable Energy, Elsevier, vol. 116(PA), pages 309-323.
  26. Süleyman Bilgin Kılıç & Semin Paksoy & Tolga Genç, 2014. "Forecasting the Direction of BIST 100 Returns with Artificial Neural Network Models," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 4(3), pages 759-759.
  27. Sun, Shaolong & Sun, Yuying & Wang, Shouyang & Wei, Yunjie, 2018. "Interval decomposition ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 76(C), pages 274-287.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.