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Arabian Journal for Science and Engineering
Published in: Arabian Journal for Science and Engineering 11/2019

13-07-2019 | Research Article - Computer Engineering and Computer Science

Prediction Using Cuckoo Search Optimized Echo State Network

Authors: Abubakar Bala, Idris Ismail, Rosdiazli Ibrahim, Sadiq M. Sait, Hamza Onoruoiza Salami

Published in: Arabian Journal for Science and Engineering | Issue 11/2019

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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.
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Footnotes
1
For singular objective CS, the terms “egg” and “nest” are similar because one egg is assumed per nest.
 
2
The engine of modern airplanes, often placed under the plane’s wings and is responsible for the thrust of the airplane.
 
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Metadata
Title
Prediction Using Cuckoo Search Optimized Echo State Network
Authors
Abubakar Bala
Idris Ismail
Rosdiazli Ibrahim
Sadiq M. Sait
Hamza Onoruoiza Salami
Publication date
13-07-2019
Publisher
Springer Berlin Heidelberg
Published in
Arabian Journal for Science and Engineering / Issue 11/2019
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-019-04008-0

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