Improving Forecasting Performance by Exploiting Expert Knowledge: Evidence from Guangzhou Port

Abstract

Expert knowledge has been proved by substantial studies to be contributory to higher forecasting performance; meanwhile, its application is criticized and opposed by some groups for biases and inconsistency inherent in experts’ subjective judgment. This paper proposes a new approach to improving forecasting performance, which takes advantage of expert knowledge by constructing a constraint equation rather than directly adjusting the predicted values by experts. For the comparison purpose, the proposed approach, together with several widely used models including ARIMA, BP-ANN and the judgment model (JM), is applied to forecasting the container throughput of Guangzhou Port, which is one of the most important ports of China. Forecasting performances of the above models are compared and the results clearly show superiority of the proposed approach over its rivals, which implies that expert knowledge will make positive contribution as long as it is used in a right way.

Aggregating predictions from experts: A review of statistical methods, experiments, and applications

“…Forecasting presents decision makers with actionable information that they can use to prevent (or prepare for) economic (Huang, Qiao, Wang, & Liu, 2016; Mak, Bui, & Blanning, 1996; Shin, Coh, & Lee, 2013), engineering (Guangliang, 1996; Neves & Frangopol, 2008; Zio, 1996), ecological (Borsuk, 2004; Failing, Horn, & Higgins, 2004; Johnson, Alhainen, Fox, Madsen, & Guillemain, 2018; Morales‐Nápoles, Paprotny, Worm, Abspoel‐Bukman, & Courage, 2017), social (Cabello, Conde, Diego, Moguerza, & Redchuk, 2012; Craig, Goldstein, Rougier, & Seheult, 2001; Kläs, Nakao, Elberzhager, & Münch, 2010), and public health burdens (Alho, 1992; Evans et al, 1994).…”

Aggregating expert-elicited data for prediction: A scoping review of statistical methods, experiments, and applications v1

“…Articles taking a Bayesian approach accounted for 25% of analysis-set articles and emphasized how priors can compliment sparse data (Zio and Apostolakis, 1997;Clemen and Winkler, 2007;Tartakovsky, 2007;Huang et al, 2016;Neves and Frangopol, 2008;Abramson et al, 1996;Ren-jun and Xian-zhong, 2002;Mantyka-Pringle et al, 2014;Brito and Griffiths, 2016b;Wang and Zhang, 2018;. Many papers focused on assessing risk (Zio and Apostolakis, 1997;Brito and Griffiths, 2016b;Tartakovsky, 2007).…”

“…(Alvarado-Valencia et al, 2017;Graefe et al, 2014a;Borsuk, 2004;Brito and Griffiths, 2016a;Abramson et al, 1996;Mak et al, 1996) Ill-structured tasks When changes to an environment impact the probabilistic links between cues an expert receives and their effect (how these cues should should be interpreted). (Seifert and Hadida, 2013;Huang et al, 2016)…”

“…Forecasting presents decision makers with actionable information that they can use to prevent (or prepare for) economic (Shin et al, 2013;Huang et al, 2016;Mak et al, 1996), engineering Guangliang (1996); Zio (1996b);Neves andFrangopol (2008), ecological Borsuk (2004); Failing et al (2004); ; Johnson et al (2018), social Cabello et al (2012); ; Craig et al (2001), and public health burdens Evans et al (1994a); Alho (1992).…”

“…These fields focus on decision makers and their ability to make predictions from data that cannot easily be collected and fed to a statistical model. Other areas of active research in expert opinion are quality assurance , politics ; Graefe et al (2014a); Graefe (2015Graefe ( , 2018; Cai et al (2016); Wang and Zhang (2018); Satopää et al (2014); Graefe et al (2014b), economics Shin et al (2013); Huang et al (2016); Mak et al (1996), engineering Craig et al (2001; Tartakovsky (2007); Neves and Frangopol (2008); Zio (1996a); Brito and Griffiths (2016a); Jin et al (2007); Wang et al (2008); ; ; Ren-jun and Xianzhong (2002), sports Gu et al (2016), sociology Cabello et al (2012); Adams et al (2009), meteorological Abramson et al (1996), ecological Johnson et al (2018; Borsuk (2004);Failing et al (2004); , environmental science ; Mantyka-Pringle et al (2014); Li et al (2012); Zio and Apostolakis (1997), and public health Alho (1992); Evans et al (1994b); Jana et al (2019); Kurowicka et al (2010). The diversity and breadth of applications underscore the importance of expert opinion in a wide variety of disciplines.…”