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Prediction Using Cuckoo Search Optimized Echo State Network

  • Abubakar BalaEmail author
  • Idris Ismail
  • Rosdiazli Ibrahim
  • Sadiq M. Sait
  • Hamza Onoruoiza Salami
Research Article - Computer Engineering and Computer Science

Abstract

The advent of internet of things has brought a revolution in the amount of data generated in industry. Researchers now have to develop ways to harness such huge amount of data. Thus, a new method called “predictive maintenance” was developed. In this technique, sensor data is used to predict failures so that appropriate actions are taken to save accidents and costs. Artificial neural networks have proven to be excellent tools for prediction. In this work, the echo state network (ESN), which is a new concept of recurrent neural network (RNN), is used to predict failures in turbofan engines. The ESN was developed to solve the complexities of earlier RNNs. However, choosing the right topology and parameters for the ESN is often a difficult problem. Hence, we develop a cuckoo search optimization-based algorithm to optimize the ESN. The approach is compared with three particle swarm optimization methods and two other methods, and it performed better.

Keywords

Algorithms Artificial neural networks Artificial intelligence Cuckoo search Echo state network Lévy flight Prediction Turbofan engine 

Notes

Acknowledgements

The authors recognize the support of Universiti Teknologi PETRONAS (UTP), Malaysia. Appreciation also goes to King Fahd University of Petroleum & Minerals for their support.

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Copyright information

© King Fahd University of Petroleum & Minerals 2019

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringUniversiti Teknologi PETRONAS, MalaysiaBandar Seri IskandarMalaysia
  2. 2.Electrical Engineering DepartmentBayero University KanoKanoNigeria
  3. 3.Computer Engineering Department and Center for Communications and IT Research, Research InstituteKing Fahd University of Petroleum & MineralsDhahranSaudi Arabia
  4. 4.College of Computer Science and EngineeringUniversity of Hafr AlbatinHafar Al BatinSaudi Arabia

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