A cooperative-competitive master-slave global-best harmony search for ANN optimization and water-quality prediction

Najmeh Sadat Jaddi, Salwani Abdullah

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

The artificial neural network (ANN) is one of the most accurate and commonly used machine-learning techniques and can learn even complex data by employing metaheuristic algorithms. Harmony search (HS) is a metaheuristic algorithm that imitates the process by which musicians tune their instruments to achieve perfect harmony. Global-best harmony search(GHS) is an effective variant of the HS algorithm that borrows the concept of gbest (globalbest) from particle-swarm optimization (PSO) to improve the performance of HS. Employing a multi-population technique improves the convergence of the algorithm. The master-slave technique is one of the most powerful multi-population techniques. This paper proposes a cooperative-competitive master-slave multi-population GHS (CC-GHS) to train the ANN. To provide the proposed CC-GHS algorithm with strong abilities in both exploration and exploitation, a competitive master-slave strategy (Com-GHS)is interacted with a cooperative master-slave strategy(Coo-GHS). A probabilistic variable is employed to achieve a good balance between cooperativeness and competitiveness. The method is tested on benchmark classification and time-series prediction problems, and statistical analyses demonstrate the ability of the proposed method. The CC-GHS is also applied to a real-world water-quality prediction problem with promising results.

Original languageEnglish
Pages (from-to)209-224
Number of pages16
JournalApplied Soft Computing Journal
Volume51
DOIs
Publication statusPublished - 1 Feb 2017

Fingerprint

Water quality
Neural networks
Particle swarm optimization (PSO)
Learning systems
Time series

Keywords

  • Artificial neural network
  • Cooperative-competitive master-slave
  • Global-best harmony search
  • Multi-population
  • Water-quality prediction

ASJC Scopus subject areas

  • Software

Cite this

A cooperative-competitive master-slave global-best harmony search for ANN optimization and water-quality prediction. / Jaddi, Najmeh Sadat; Abdullah, Salwani.

In: Applied Soft Computing Journal, Vol. 51, 01.02.2017, p. 209-224.

Research output: Contribution to journalArticle

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