The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Predicting stock market index using fusion of machine learning techniques
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Citations
Cites
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Cited by
Chong, E., Han, C., & Park, F. C. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.04.030 · Cited by 834
A systematic review of fundamental and technical analysis of stock market predictions
Nti, I. K., Adekoya, A. F., & Weyori, B. A. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09754-z · Cited by 547
Stock Market Analysis: A Review and Taxonomy of Prediction Techniques
Shah, D., Isah, H., & Zulkernine, F. (2019) · International Journal of Financial Studies · doi:10.3390/ijfs7020026 · Cited by 465
Deep learning and time series-to-image encoding for financial forecasting
Barra, S., Carta, S. M., Corriga, A., Podda, A. S., & Recupero, D. R. (2020) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2020.1003132 · Cited by 267
Stock Price prediction using LSTM and SVR
Bathla, G. (2020) · 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC) · doi:10.1109/pdgc50313.2020.9315800 · Cited by 139
Metadata
- Authors
- Patel, J., Shah, S., Thakkar, P., & Kotecha, K.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 42
- Issue
- 4
- Pages
- 2162-2172
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2007358469
- Cited by
- 608
- References
- 26
- FWCI
- 16.02
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock market index using fusion of machine learning techniques. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2014.10.031
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
