Quantile Regression–Based Estimation of Dynamic Statistical Contingency Fuel
Published Online:13 Oct 2020https://doi.org/10.1287/trsc.2020.0997
References
- (2009) Air carrier responses to the fuel price crisis: Some issues. Global Trade Customs J. 4(2):31–43.Google Scholar
- (2009) Effective flight plans can help airlines economize. AERO Online 9(3):8.Google Scholar
- Bureau of Transportation Statistics (2016) Airline financial data, 2016. Accessed January 25, 2017, https://www.rita.dot.gov/bts/press_releases/bts061_16.Google Scholar
- (1996a) Bagging predictors. Machine Learn. 24:123–140.Crossref, Google Scholar
- (1996b) Stacked regressions. Machine Learn. 24:49–64.Crossref, Google Scholar
- (2001) Random forests. Machine Learn. 45:5–32.Crossref, Google Scholar
- Electronic Code of Federal Regulations (E-CFR) (2015) Title 14: Aeronautics and space part 121: Operating requirements: Domestic, flag, and supplemental operations. Accessed February 20, 2017, http://www.ecfr.gov/cgi-bin/text-idx?SID=a8d3c4800d167b64bbfa2349ec337755&mc=true&node=pt14.3.121&rgn=div5.Google Scholar
- Environmental Protection Agency (2013) Emission factors for greenhouse gas inventories. Accessed February 20, 2017, http://www.epa.gov/climateleadership/documents/emission-factors.pdf.Google Scholar
- Environmental Protection Agency (2016) Fast facts: U.S. transportation sector greenhouse gas emissions 1990–2014. Accessed February 20, 2017, https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100ONBL.pdf.Google Scholar
- European Commission (2010) Report on the SES legislation implementation. Accessed February 20, 2017, http://ec.europa.eu/transport/modes/air/single_european_sky/doc/2011_10_03_ses_legislation_report_2010.pdf.Google Scholar
- European Commission (2015) Fuel and air transport. Accessed February 20, 2017, http://ec.europa.eu/transport/modes/air/doc/fuel_report_final.pdf.Google Scholar
- Federal Aviation Administration (2014) Next Gen: The business case for the Next Generation Air Transportation System. Accessed February 20, 2017, https://www.faa.gov/nextgen/media/BusinessCaseForNextGen-2014.pdf.Google Scholar
- (1997) A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. System Sci. 55(1):119–139.Crossref, Google Scholar
- (2001) Greedy function approximation: A gradient boosting machine. Ann. Statist. 29(5):1189–1232.Crossref, Google Scholar
- (2003) Importance sampled learning ensembles. Technical report, Department of Statistics, Stanford University, Palo Alto, CA.Google Scholar
- (2013) A fuel tankering model applied to a domestic airline network. J. Adv. Transportation 47(4):386–398.Crossref, Google Scholar
- (2016) Fueling for contingencies: The hidden cost of unpredictability in the air transportation system. Transportation Res. Part D: Transport Environ. 44:199–210.Crossref, Google Scholar
- (2017) Estimating fuel burn impacts of taxi-out delay with implications for gate-hold benefits. Transportation Res. Part C: Emerging Tech. 80:454–466.Crossref, Google Scholar
- (2016) Economics of advanced thin-haul concepts and operations. 16th AIAA Aviation Tech. Integration Oper. Conf., June 13–17, 2016, Washington DC.Google Scholar
- (2009) The Elements of Statistical Learning (Springer).Crossref, Google Scholar
- (2008) The feasibility and potential environmental benefits of alternative fuels for commercial aviation. Proc. 26th Congress Aeronautical Sci., September 14-19, 2008 (Anchorage, AK).Google Scholar
- International Air Transport Association (2004) Environmental review. Accessed February 20, 2017, http://web.docuticker.com/go/docubase/5452.Google Scholar
- Intergovernmental Panel on Climate Change (1999) Aviation and the global atmosphere. Accessed February 20, 2017, https://www.ipcc.ch/pdf/special-reports/spm/av-en.pdf.Google Scholar
- Intergovernmental Panel on Climate Change (2014) Climate Change 2014: Mitigation of Climate Change (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- International Civil Aviation Organization (ICAO) (2010) Annex 6 - Operation of Aircraft. Accessed May 5, 2020, http://verifavia.com/bases/ressource_pdf/299/icao-annex-6-part-i.pdf.Google Scholar
- International Civil Aviation Organization (2012) A planning framework for seamless ATM. Accessed February 20, 2017, http://www.icao.int/APAC/Meetings/2012_APSAPG1/WP15%20IATA_A%20Planning%20Framework%20for%20Seamless%20ATM.pdf.Google Scholar
- International Civil Aviation Organization (2014) ICAO environment report 2013: Aviation and climate change. Accessed February 20, 2017, http://cfapp.icao.int/Environmental-Report-2013/files/assets/common/downloads/ICAO_2013_Environmental_Report.pdf.Google Scholar
- (2011) A look at the state of airline fuel conservation 51st AGIFORS Annual Proc., October 10-14, 2011, Antalya, Turkey.Google Scholar
- (2018) Stochastic optimization models for transferring delay along flight trajectories to reduce fuel usage. Transportation Sci. 52(1):134–149.Link, Google Scholar
- (2017) Behavioral analysis of airline scheduled block time adjustment. Transportation Res. Part E: Logist. Transportation Rev. 103:56–68.Crossref, Google Scholar
- (2018a) Assessing the impact of tactical airport surface operations on airline schedule block time setting. Transportation Res. Part C: Emerging Tech. 89:133–147.Crossref, Google Scholar
- (2018b) Improving airline fuel efficiency via fuel burn prediction and uncertainty estimation. Transportation Res. Part C: Emerg. Tech. 97:128–146.Crossref, Google Scholar
- (2018) Evaluating predictability based on gate-in fuel prediction and cost-to-carry estimation. J. Air Transportation Management 67:146–152.Crossref, Google Scholar
- (2012) Operations Quantitative Problem Solving Methods in the Airline Industry (Springer, New York).Google Scholar
- (2005) Quantile Regression (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (1999). Goodness of fit and related inference processes for quantile regression. J. Amer. Statist. Assoc. 94(448):1296–1310.Crossref, Google Scholar
- (1996) Combining estimates in regression and classification. J. Amer. Statist. Assoc. 91(436):1641–1650.Google Scholar
- (2015) Scalable ensemble learning and computationally efficient variance estimation. Unpublished doctoral dissertation, University of California, Berkeley, CA.Google Scholar
- (2009) Aviation and global climate change in the 21st century. Atmosphere Environ. 43(22-23):3520–3537.Crossref, Google Scholar
- (2011) Quantification of fuel burn reduction in cruise via speed and altitude optimization strategies. Report No. ICAT-2011-03, MIT International Center for Air Transportation. http://dspace.mit.edu/bitstream/handle/1721.1/62196/Lovegren_ICAT-2011.pdf?sequence=1.Google Scholar
- (2017) Integrated disruption management and flight planning to trade off delays and fuel burn. Transportation Sci. 51(1):88–111.Link, Google Scholar
- (2006) Quantile regression forests. J. Machine Learn. Res. 7:983–999.Google Scholar
- (2007) Generalized boosted models: A guide to the GBM package. Accessed May 1, 2016, http://www.saedsayad.com/docs/gbm2.pdf.Google Scholar
- (2015) Landing on empty: Estimating the benefits from reducing fuel uplift in U.S. civil aviation. Environ. Res. Lett. 10:094002.Crossref, Google Scholar
- (2012) Aircraft Design: A Systems Engineering Approach (John Wiley & Sons, Hoboken, NJ).Crossref, Google Scholar
- (2011) Managing flight operational costs, SABRE. Accessed May 1, 2016, http://www.sabreairlinesolutions.com/pdfs/ManagingFlightOperationalCosts.pdf.Google Scholar
- (1996) Uncertainties that flight crews and dispatchers must consider when calculating the fuel needed for a flight. NASA Technical Memorandum 110240. Accessed May 1, 2016, http://ntrs.nasa.gov/search.jsp?R=19960042496.Google Scholar
- (2007) Super Learner. U.C. Berkeley Division of Biostatistics Working Paper Series, Paper No. 222, University of California, Berkeley, CA.Google Scholar
- (1992) Stacked generalization. Neural Networks 5(2):241–259.Crossref, Google Scholar

