Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/75652
Type: Artigo de periódico
Title: SERFIT - AN ALGORITHM TO FORECAST MINERAL TRENDS
Author: SUSLICK, SB
HARRIS, DP
ALLAN, LHE
Abstract: A PASCAL computer program, named SERFIT, facilitates the identification of trend model for long-term forecasting and the estimation of model parameters. Model identification is achieved through the computation of slope characteristics from mineral data time series. The trend models generated by the program are: linear, normal, lognormal, and modified exponentials: simple-modified exponential, logistic, derivative logistic, Gompertz, and derivative Gompertz. Parameters of the family of modified exponential models are estimated using Mitscherlich's regression, which is based upon the maximum likelihood method and provides a probability structure for the models. SERFIT is demonstrated on U.S. petroleum production and world copper consumption data.
Subject: TREND CURVES
LONG-TERM FORECASTING
MINERAL DEMAND AND PRODUCTION PROJECTIONS
LIFE-CYCLES MODELS
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Rights: fechado
Identifier DOI: 10.1016/0098-3004(94)00105-4
Date Issue: 1995
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

Files in This Item:
File Description SizeFormat 
WOSA1995RE78300006.pdf917.89 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.