The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Time series forecasting using a deep belief network with restricted Boltzmann machines
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336
Greedy layer-wise training of deep networks
Bengio, Y., Lamblin, P., Popovici, D., & Larochelle, H. (2007) · Advances in Neural Information Processing Systems 19 · doi:10.7551/mitpress/7503.003.0024 · Cited by 4,841
A learning algorithm for Boltzmann machines
Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. (1985) · Cognitive Science · doi:10.1207/s15516709cog0901_7 · Cited by 3,402
Cited by
Feature dimensionality reduction: a review
Jia, W., Sun, M., Lian, J., & Hou, S. (2022) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00637-x · Cited by 797
Temporal data classification and forecasting using a memristor-based reservoir computing system
Moon, J., Ma, W., Shin, J. H., Cai, F., Du, C., Lee, S. H., & Lu, W. D. (2019) · Nature Electronics · doi:10.1038/s41928-019-0313-3 · Cited by 645
Ball, J. E., Anderson, D. T., & Chan, C. S. (2017) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.11.042609 · Cited by 746
Sagheer, A., & Kotb, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-55320-6 · Cited by 351
Shapley additive explanations for NO2 forecasting
Vega García, M., & Aznarte, J. L. (2020) · Ecological Informatics · doi:10.1016/j.ecoinf.2019.101039 · Cited by 346
A survey of swarm and evolutionary computing approaches for deep learning
Darwish, A., Hassanien, A. E., & Das, S. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09719-2 · Cited by 200
Lekha, S., & M, S. (2021) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2020.2993591 · Cited by 105
Metadata
- Authors
- Kuremoto, T., Kimura, S., Kobayashi, K., & Obayashi, M.
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2014-08
- Volume
- 137
- Pages
- 47-56
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W2083022762
- Cited by
- 527
- References
- 4
- FWCI
- 31.03
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.
