Lag-ℓ forecasting and machine-learning algorithms

Jae Joon Ahn, Il Suh Son, Kyong Joo Oh, Tae Yoon Kim, Gyu Moon Song

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


In this study, we discuss the problem of lag-ℓ forecasting, which has been solved using a machine-learning algorithm. The main aim of this study is to define the lag-ℓ forecaster based on a precise classification approach and to discuss the technical issues involved in the lag-ℓ forecasting problem, including a comparison of various machine-learning algorithms for proper implementation of the technique. This study focuses on an application that uses the lag-ℓ forecaster in an early-warning system.

Original languageEnglish
Pages (from-to)269-282
Number of pages14
JournalExpert Systems
Issue number3
Publication statusPublished - 2011 Jul

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence


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