Multi resolution genetic programming approach for stream flow forecasting

Maheswaran Rathinasamy; Rakesh Khosa

doi:10.1007/978-3-642-27172-4_84

Multi resolution genetic programming approach for stream flow forecasting

Maheswaran Rathinasamy, Rakesh Khosa

St. Anthony Falls Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

Genetic Programming (GP) is increasingly used as an alternative for Artificial Neural Networks (ANN) in many applications viz. forecasting, classification etc. However, GP models are limited in scope as their application is restricted to stationary systems. This study proposes use of Multi Resolution Genetic Programming (MRGP) based approach as an alternative modelling strategy to treat non-stationaries. The proposed approach is a synthesis of Wavelets based Multi-Resolution Decomposition and Genetic Programming. Wavelet transform is used to decompose the time series at different scales of resolution so that the underlying temporal structures of the original time series become more tractable. Further, Genetic Programming is then applied to capture the underlying process through evolutionary algorithms. In the case study investigated, the MRGP is applied for forecasting one month ahead stream flow in Fraser River, Canada, and its performance compared with the conventional, but scale insensitive, GP model. The results show the MRGP as a promising approach for flow forecasting.

Original language	English (US)
Title of host publication	Swarm, Evolutionary, and Memetic Computing - Second International Conference, SEMCCO 2011, Proceedings
Pages	714-722
Number of pages	9
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-27172-4_84
State	Published - Dec 1 2011
Event	2nd International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011 - Visakhapatnam, Andhra Pradesh, India Duration: Dec 19 2011 → Dec 21 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	7076 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	2nd International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011
Country	India
City	Visakhapatnam, Andhra Pradesh
Period	12/19/11 → 12/21/11

Keywords

Genetic Programming
Multiscale Forecasting
Stream flow
Wavelet Analysis

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10.1007/978-3-642-27172-4_84

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Rathinasamy, M., & Khosa, R. (2011). Multi resolution genetic programming approach for stream flow forecasting. In Swarm, Evolutionary, and Memetic Computing - Second International Conference, SEMCCO 2011, Proceedings (PART 1 ed., pp. 714-722). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7076 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-27172-4_84

Multi resolution genetic programming approach for stream flow forecasting. / Rathinasamy, Maheswaran; Khosa, Rakesh.

Swarm, Evolutionary, and Memetic Computing - Second International Conference, SEMCCO 2011, Proceedings. PART 1. ed. 2011. p. 714-722 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7076 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Rathinasamy, M & Khosa, R 2011, Multi resolution genetic programming approach for stream flow forecasting. in Swarm, Evolutionary, and Memetic Computing - Second International Conference, SEMCCO 2011, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7076 LNCS, pp. 714-722, 2nd International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011, Visakhapatnam, Andhra Pradesh, India, 12/19/11. https://doi.org/10.1007/978-3-642-27172-4_84

Rathinasamy M, Khosa R. Multi resolution genetic programming approach for stream flow forecasting. In Swarm, Evolutionary, and Memetic Computing - Second International Conference, SEMCCO 2011, Proceedings. PART 1 ed. 2011. p. 714-722. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-27172-4_84

Rathinasamy, Maheswaran ; Khosa, Rakesh. / Multi resolution genetic programming approach for stream flow forecasting. Swarm, Evolutionary, and Memetic Computing - Second International Conference, SEMCCO 2011, Proceedings. PART 1. ed. 2011. pp. 714-722 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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