The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Forecasting daily urban electric load profiles using artificial neural networks
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Cites
Kohonen, T. (2001) · Springer Series in Information Sciences · doi:10.1007/978-3-642-56927-2 · Cited by 16,019
Davies, D. L., & Bouldin, D. W. (1979) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1979.4766909 · Cited by 9,145
Hagan, M., Demuth, H. B., Beale, M. H., & Jes?s, O. D. (2016) · Institutional Repository of the National University Open and Distance UNAD (Universidad Nacional Abierta y a Distancia) · Cited by 5,133
Pattern Recognition Principles
(2009) · Classification Methods for Remotely Sensed Data, Second Edition · doi:10.1201/9781420090741.ch2 · Cited by 3,188
Gray, R. M. (1990) · Readings in Speech Recognition · doi:10.1016/b978-0-08-051584-7.50011-5 · Cited by 2,845
Parallel & distributed processing
Slusallek, P., Shirley, P., Mark, W., Stoll, G., & Wald, I. (2005) · ACM SIGGRAPH 2005 Courses on - SIGGRAPH '05 · doi:10.1145/1198555.1198750 · Cited by 2,568
Electric load forecasting using an artificial neural network
Park, D.-C., El-Sharkawi, M. A., Marks, R. J., Atlas, L., & Damborg, M. J. (1991) · IEEE Transactions on Power Systems · doi:10.1109/59.76685 · Cited by 1,440
SOM-based data visualization methods
Vesanto, J. (1999) · Intelligent Data Analysis · doi:10.3233/ida-1999-3203 · Cited by 851
Short-term load forecasting using an artificial neural network
Lee, K. Y., Cha, Y. T., & Park, J. H. (1992) · IEEE Transactions on Power Systems · doi:10.1109/59.141695 · Cited by 602
Kohonen's Self Organizing Feature Maps for Exploratory Data Analysis
Ultsch, A. (1990) · Medical Entomology and Zoology · Cited by 560
Cited by
Electric load forecasting methods: Tools for decision making
Hahn, H., Meyer-Nieberg, S., & Pickl, S. (2009) · European Journal of Operational Research · doi:10.1016/j.ejor.2009.01.062 · Cited by 549
Load forecasting, dynamic pricing and DSM in smart grid: A review
Khan, A. R., Mahmood, A., Safdar, A., Khan, Z. A., & Khan, N. A. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.10.117 · Cited by 469
Paradigm shift in urban energy systems through distributed generation: Methods and models
Manfren, M., Caputo, P., & Costa, G. (2011) · Applied Energy · doi:10.1016/j.apenergy.2010.10.018 · Cited by 437
Efendigil, T., Önüt, S., & Kahraman, C. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.08.058 · Cited by 263
Marvuglia, A., Kanevski, M., & Benetto, E. (2015) · Environment International · doi:10.1016/j.envint.2015.05.011 · Cited by 41
Self-citation
Metadata
- Authors
- Beccali, M., Cellura, M., Lo Brano, V., & Marvuglia, A.
- Venue
- Energy Conversion and Management
- Publisher
- Elsevier BV
- Published
- 2004-11
- Volume
- 45
- Issue
- 18-19
- Pages
- 2879-2900
- ISSN
- 0196-8904 (ISSN-L)
- OpenAlex
- W1968806673
- Cited by
- 253
- References
- 25
- FWCI
- 7.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Beccali, M., Cellura, M., Lo Brano, V., & Marvuglia, A. (2004). Forecasting daily urban electric load profiles using artificial neural networks. Energy Conversion and Management. https://doi.org/10.1016/j.enconman.2004.01.006
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.
