Estimation Models Generation using Linear Genetic Programming
Javier Martínez Canillas, Roberto Sánchez, Benjamı́n Barán · CLEI electronic journal · 2009
The use of decision rules and estimation techniques is increasingly common for decision mak-ing. In recent years studies were conducted which applies Genetic Programming (GP) to obtainrules to make predictions. A new branch in the area of Evolutionary Algorithms (EA) is LinearGenetic Programming (LGP). LGP evolves instructions sequences of an imperative programminglanguage. This paper proposes estimation models generation for time series forecasting using LGP.The forecasting result for the Consumer Price Index (CPI) and the price of soybeans per ton showsthe potential of this new proposal.