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Cited by 120Construction Project Management and PerformanceCapital Investment and Risk AnalysisResource-Constrained Project Scheduling

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Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques

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Acebes, Fernando, Pereda, María, Poza, David, Pajares, Javier, Galán, José Manuel·2015·International Journal of Project Management
DOI 10.1016/j.ijproman.2015.06.012
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Research works printed but not linked: 31

  1. Acebes, 2014, A new approach for project control under uncertainty. Going back to the basics, Int. J. Proj. Manag., 32, 423, 10.1016/j.ijproman.2013.08.003 · DOI · Paper page
  2. Anbari, 2003, Earned value project management method and extensions, Proj. Manag. J., 34, 12, 10.1177/875697280303400403 · DOI
  3. Anderssen, 2006, Reducing over-optimism in variable selection by cross-model validation, Chemom. Intell. Lab. Syst., 84, 69, 10.1016/j.chemolab.2006.04.021 · DOI
  4. Blanco, 2013, Earned value management: a predictive analysis tool, Navy Supply Corps Newsl., 66, 24
  5. Bradley, 1997, The use of the area under the ROC curve in the evaluation of machine learning algorithms, Pattern Recogn., 30, 1145, 10.1016/S0031-3203(96)00142-2 · DOI · Paper page
  6. Breiman, 1996, Bagging predictors, Mach. Learn., 24, 123, 10.1007/BF00058655 · DOI · Paper page
  7. Breiman, 2001, Random Forests, Mach. Learn., 45, 5, 10.1023/A:1010933404324 · DOI · Paper page
  8. Cioffi, 2006, Designing project management: a scientific notation and an improved formalism for earned value calculations, Int. J. Proj. Manag., 24, 136, 10.1016/j.ijproman.2005.07.003 · DOI
  9. Colin, 2014, Setting tolerance limits for statistical project control using earned value management, Omega, 49, 107, 10.1016/j.omega.2014.06.001 · DOI
  10. Criminisi, 2011, Decision Forests: a unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning, Found. Trends Comput. Graph. Comput. Vis., 7, 81, 10.1561/0600000035 · DOI · Paper page
  11. Ding, 2014, An experimental evaluation of novelty detection methods, Neurocomputing, 135, 313, 10.1016/j.neucom.2013.12.002 · DOI
  12. Duong, 2007, ks: kernel density estimation and kernel discriminant analysis for multivariate data in R, J. Stat. Softw., 21, 1, 10.18637/jss.v021.i07 · DOI
  13. Duong, 2005, Cross-validation bandwidth matrices for multivariate kernel density estimation, Scand. J. Stat., 32, 485, 10.1111/j.1467-9469.2005.00445.x · DOI
  14. Hazir, 2015, A review of analytical models, approaches and decision support tools in project monitoring and control, Int. J. Proj. Manag., 33, 808, 10.1016/j.ijproman.2014.09.005 · DOI
  15. Hodge, 2004, A survey of outlier detection methodologies, Artif. Intell. Rev., 22, 85, 10.1023/B:AIRE.0000045502.10941.a9 · DOI · Paper page
  16. Kim, 2003, A model for effective implementation of earned value management methodology, Int. J. Proj. Manag., 21, 375, 10.1016/S0263-7863(02)00049-2 · DOI
  17. Lambrechts, 2008, Proactive and reactive strategies for resource-constrained project scheduling with uncertain resource availabilities, J. Sched., 11, 121, 10.1007/s10951-007-0021-0 · DOI
  18. Lipke, 1999, Applying management reserve to software project management, J. Def. Softw. Eng., 17
  19. Lipke, 2004, The probability of success, J. Qual. Assur. Inst., 14
  20. Lipke, 2009, Prediction of project outcome: the application of statistical methods to earned value management and earned schedule performance indexes, Int. J. Proj. Manag., 27, 400, 10.1016/j.ijproman.2008.02.009 · DOI
  21. Markou, 2003, Novelty detection: a review—part 1: statistical approaches, Signal Process., 83, 2481, 10.1016/j.sigpro.2003.07.018 · DOI
  22. Markou, 2003, Novelty detection: a review—part 2: neural network based approaches, Signal Process., 83, 2499, 10.1016/j.sigpro.2003.07.019 · DOI
  23. McKim, 2000, Project performance control in reconstruction projects, J. Constr. Eng. Manag., 126, 137, 10.1061/(ASCE)0733-9364(2000)126:2(137) · DOI
  24. Moslemi Naeni, 2011, Evaluating fuzzy earned value indices and estimates by applying alpha cuts, Expert Syst. Appl., 38, 8193, 10.1016/j.eswa.2010.12.165 · DOI
  25. Naeni, 2011, A fuzzy approach for the earned value management, Int. J. Proj. Manag., 29, 764, 10.1016/j.ijproman.2010.07.012 · DOI
  26. Narbaev, 2014, An earned schedule-based regression model to improve cost estimate at completion, Int. J. Proj. Manag., 32, 1007, 10.1016/j.ijproman.2013.12.005 · DOI
  27. Pajares, 2011, An extension of the EVM analysis for project monitoring: the Cost Control Index and the Schedule Control Index, Int. J. Proj. Manag., 29, 615, 10.1016/j.ijproman.2010.04.005 · DOI
  28. Plaza, 2009, A model-based DSS for integrating the impact of learning in project control, Decis. Support. Syst., 47, 488, 10.1016/j.dss.2009.04.010 · DOI
  29. Stone, 1974, Cross-validatory choice and assessment of statistical predictions, J. R. Stat. Soc. Ser. B, 36, 111, 10.1111/j.2517-6161.1974.tb00994.x · DOI · Paper page
  30. Tseng, 2011, Statistical analysis for comparison of overall performance of projects using Weibull analysis on earned value metrics, J. Chin. Inst. Ind. Eng., 28, 165
  31. Wauters, 2014, Support Vector Machine regression for project control forecasting, Autom. Constr., 47, 92, 10.1016/j.autcon.2014.07.014 · DOI

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Metadata

Authors
Acebes, F., Pereda, M., Poza, D., Pajares, J., & Galán, J. M.
Affiliations
  • Universidad de Valladolid (ES)
  • Universidad de Burgos (ES)
Corresponding author
Acebes, Fernando
ORCID
Venue
International Journal of Project Management
Publisher
Elsevier BV
Published
2015-10
Volume
33
Issue
7
Pages
1597-1609
ISSN
0263-7863 (ISSN-L)
DOI
10.1016/j.ijproman.2015.06.012
OpenAlex
W958645160
Cited by
120
References
2
Citations by year
2026: 15 · 2025: 16 · 2024: 14 · 2023: 10 · 2022: 10 · 2021: 12 · 2020: 13 · 2019: 8 · 2018: 9 · 2017: 6 · 2016: 5 · 2015: 2
FWCI
8.22
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Project Management (publishedVersion)
  • Hispana (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • arXiv (Cornell University) (submittedVersion, cc-by-nc-nd)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
  • RWTH Publications (RWTH Aachen) (submittedVersion)
  • Repositorio Institucional de la Universidad de Burgos (University of Burgos) (submittedVersion, other-oa)
  • UVaDOC UVaDOC University of Valladolid Documentary Repository (University of Valladolid) (submittedVersion, other-oa)
  • University of Valladolid Documentary Repository (University of Valladolid) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • Regional Government of Castile and Leon (Spain) (VA056A12-2)
  • Spanish Ministerio de Ciencia e Innovación (CSD2010-00034)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Construction Project Management and Performance
  • Social Sciences › Economics, Econometrics and Finance › Finance › Capital Investment and Risk Analysis
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Resource-Constrained Project Scheduling
Keywords
earned value management, Monte Carlo simulation, anomaly detection, statistical learning, project risk analysis, classification and regression

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