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Adaptive Pipelined Neural Network Structure in Self-aware Internet of Things

  • Dhiya AI-Jumeily
  • Mohamad Al-Zawi
  • Abir Jaafar Hussain
  • Ciprian Dobre
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 546)

Abstract

Self-Managing systems are a significant feature in Autonomic Computing which is required for system reliability and performance in a changing environment. The work described in this book chapter is concerned with self-healing systems; systems that can detect and analyse issues with their behavior and performance, and fixe or reconfigure as appropriate. These processes should occur in real-time to restore the desired functionality as soon as possible. The system should ideally maintain functionality during the healing process which occurs at runtime. Adaptive neural networks are proposed as a solution to some of these challenges; monitoring the system and environment, mapping a suitable solution and adapting the system accordingly. A novel application of a modified Pipelined Recurrent Neural Network is proposed in this chapter with experiments aimed to assess its applicability to online.

Keywords

Power System Mean Square Error Feedforward Neural Network Circuit Breaker Autonomic Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Dhiya AI-Jumeily
    • 1
  • Mohamad Al-Zawi
    • 1
    • 2
  • Abir Jaafar Hussain
    • 1
  • Ciprian Dobre
    • 3
  1. 1.Applied Computing Research GroupLiverpool John Moores UniversityLiverpoolUK
  2. 2.Institute of Applied TechnologyAbu DhabiUAE
  3. 3.University Politehnica of BucharestBucharestRomania

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