The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Empirical prediction models for adaptive resource provisioning in the cloud
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Cites
Modern Applied Statistics with S
Venables, W. N., & Ripley, B. D. (2002) · Statistics and Computing · doi:10.1007/978-0-387-21706-2 · Cited by 24,305
A survey of cross-validation procedures for model selectionPreprint
Arlot, S., & Célisse, A. (2010) · Cited by 3,625
A survey of cross-validation procedures for model selection
Arlot, S., & Celisse, A. (2010) · Statistics Surveys · doi:10.1214/09-ss054 · Cited by 3,522
A leisurely look at the bootstrap, the jackknife, and cross-validation
Efron, B., & Gong, G. (1983) · The American Statistician · doi:10.1080/00031305.1983.10483087 · Cited by 3,229
Modern Applied Statistics with S-Plus.
Venables, W. N., & Ripley, B. D. (1996) · Biometrics · doi:10.2307/2532871 · Cited by 2,994
Beckman, R. J. (1987) · Technometrics · doi:10.1080/00401706.1987.10488195 · Cited by 2,835
Encyclopedia of research design
(2011) · Choice Reviews Online · doi:10.5860/choice.48-2447 · Cited by 1,910
Parallel Networks that Learn to Pronounce English Text
B, T. J. S. A. (1987) · Cited by 1,514
Predicting the secondary structure of globular proteins using neural network models
Qian, N., & Sejnowski, T. J. (1988) · Journal of Molecular Biology · doi:10.1016/0022-2836(88)90564-5 · Cited by 1,227
CloudCmp: comparing public cloud providers
Li, A., Yang, X., Kandula, S., & Zhang, M. (2010) · Proceedings of the 10th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1879141.1879143 · Cited by 882
Machine Learning for Sequential Data: A Review
Dietterich, T. G. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-70659-3_2 · Cited by 666
Pattern Recognition, Fourth Edition
Theodoridis, S., & Koutroumbas, K. (2008) · Academic Press eBooks · Cited by 548
Malik, M. B. (2005) · Technometrics · doi:10.1198/tech.2005.s286 · Cited by 305
Experience with the accuracy of software maintenance task effort prediction models
Jorgensen, M. (1995) · IEEE Transactions on Software Engineering · doi:10.1109/32.403791 · Cited by 288
Technical Analysis from A to Z
Achelis, S. B. (2005) · Medical Entomology and Zoology · Cited by 228
Towards autonomic workload provisioning for enterprise Grids and clouds
Quiroz, A., Kim, H., Parashar, M., Gnanasambandam, N., & Sharma, N. (2009) · 2009 10th IEEE/ACM International Conference on Grid Computing · doi:10.1109/grid.2009.5353066 · Cited by 190
Forecasting for Grid and Cloud Computing On-Demand Resources Based on Pattern Matching
Caron, E., Desprez, F., & Muresan, A. (2010) · IEEE International Conference on Cloud Computing Technology and Science · doi:10.1109/cloudcom.2010.65 · Cited by 152
Structural, Syntactic, and Statistical Pattern Recognition
(2002) · Springer eBooks · doi:10.1007/b83642 · Cited by 18
Cited by
Data Center Energy Consumption Modeling: A Survey
Dayarathna, M., Wen, Y., & Fan, R. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2481183 · Cited by 1,165
Elasticity in Cloud Computing: State of the Art and Research Challenges
Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., & Merle, P. (2018) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2017.2711009 · Cited by 409
Autopilot: workload autoscaling at Google
Rzadca, K., Findeisen, P., Swiderski, J., Zych, P., Broniek, P., Kusmierek, J., Nowak, P., Strack, B., Witusowski, P., Hand, S., et al. (2020) · Proceedings of the Fifteenth European Conference on Computer Systems · doi:10.1145/3342195.3387524 · Cited by 303
Aslanpour, M. S., Gill, S. S., & Toosi, A. N. (2020) · Internet of Things · doi:10.1016/j.iot.2020.100273 · Cited by 289
A load prediction model for cloud computing using PSO-based weighted wavelet support vector machine
Zhong, W., Zhuang, Y., Sun, J., & Gu, J. (2018) · Applied Intelligence · doi:10.1007/s10489-018-1194-2 · Cited by 83
Metadata
- Authors
- Islam, S., Keung, J., Lee, K., & Liu, A.
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 28
- Issue
- 1
- Pages
- 155-162
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W2119438912
- Cited by
- 631
- References
- 18
- FWCI
- 80.46
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
