단기 항공수요 예측을 위한 경제지표의 LAD 분석

Abstract

In recognition of the importance of short-term forecasting in airline industry, this paper proposes Logical Analysis of Data (LAD) for the purpose and demonstrates its usefulness with the analysis of 12 macro-economic indicators for their relation to airline demand at two major international airports of South Korea. More specifically, numerical studies of this paper demonstrate the practicality and usefulness of LAD as an ‘explainable AI’ methodology and show benefits of LAD patterns (that is, classification knowledge), thereby the power of data classification via LAD and, at large, combinatorial optimization principles.