Meteorological time series modeling using an adaptive gene expression programming

Authors:
Alina Barbulescu;Elena Bautu
Affiliations:
Department of Mathematics and Computers Science, Ovidius University, Constanta, Romania;Department of Mathematics and Computers Science, Ovidius University, Constanta, Romania
Venue:
EC'09 Proceedings of the 10th WSEAS international conference on evolutionary computing
Year:
2009

Citing 6
Cited 2

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection

Genetic programming: on the programming of computers by means of natural selection
Evolutionary Computation

Evolutionary Computation
Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)

Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)
AdaGEP - An Adaptive Gene Expression Programming Algorithm

SYNASC '07 Proceedings of the Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
Handbook of Parametric and Nonparametric Statistical Procedures

Handbook of Parametric and Nonparametric Statistical Procedures

Statistical analysis and evaluation of Hurst coefficient for annual and monthly precipitation time series

WSEAS Transactions on Mathematics
Nonparametric models for the regional precipitation evolution in Dobrudja

ACACOS'12 Proceedings of the 11th WSEAS international conference on Applied Computer and Applied Computational Science

Quantified Score

Hi-index	0.00

Visualization

Abstract

The precipitations are characterized by important spatial and temporal variation. Model determination for such series is of high importance for hydrological purposes (e.g. weather forecasting, agriculture, flood areas, administrative planning), even if discovering patterns in such series is a very difficult problem. The objective of the current study is to describe the use of an adaptive evolutionary technique that give promising results for the development of non-linear time series models.