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Advances on Computational Intelligence in Energy

The Applications of Nature-Inspired Metaheuristic Algorithms in Energy

  • Tutut Herawan
  • Haruna Chiroma
  • Jemal H. Abawajy
Book

Part of the Green Energy and Technology book series (GREEN)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Haruna Chiroma, Usman Ali Abdullahi, Ibrahim Abaker Targio Hashem, Younes Saadi, Rawaa Dawoud Al-Dabbagh, Muhammad Murtala Ahmad et al.
    Pages 1-20
  3. Mustafa Tareq, Saad Adnan Abed, Elankovan A. Sundararajan
    Pages 21-38
  4. Abdullah Khan, Rahmat Shah, Junaid Bukhari, Nasreen Akhter, Attaullah, Muhammad Idrees et al.
    Pages 39-58
  5. Abdullah Khan, Rahmat Shah, Nasreen Akhter, Awais Qureshi, Kamran Ullah, Hilal Ahmad et al.
    Pages 59-76
  6. Mohammed Abdullahi, Shafi’i Muhammad Abdulhamid, Salihu Idi Dishing, Mohammed Joda Usman
    Pages 77-97
  7. Nasir Faruk, Abdulkarim A. Oloyede, Abubakar Abdulkarim, Lukman A. Olawoyin, Yinusa A. Adediran
    Pages 99-124
  8. Mohammed Joda Usman, Abdul Samad Ismail, Hassan Chizari, Abdulsalam Ya’u Gital, Haruna Chiroma, Mohammed Abdullahi et al.
    Pages 125-145
  9. Ayuba K. Danburam, Mohammed A. Gadam, Aliyu D. Usman, Suleiman M. Sani
    Pages 147-168
  10. Nasir Faruk, Abubakar Abdulkarim, Nazmat T. Surajudeen-Bakinde, Segun I. Popoola
    Pages 169-194
  11. Zhou Zhou, Jemal H. Abawajy, Fangmin Li
    Pages 195-215

About this book

Introduction

Addressing the applications of computational intelligence algorithms in energy, this book presents a systematic procedure that illustrates the practical steps required for applying bio-inspired, meta-heuristic algorithms in energy, such as the prediction of oil consumption and other energy products. 

Contributions include research findings, projects, surveying work and industrial experiences that describe significant advances in the applications of computational intelligence algorithms in energy. For easy understanding, the text provides practical simulation results, convergence and learning curves as well as illustrations and tables.  

Providing a valuable resource for undergraduate and postgraduate students alike, it is also intended for researchers in the fields of computational intelligence and energy.

Keywords

Computational intelligence algorithms Bio-inspired meta-heuristic algorithms Energy data sources Energy consumption Oil consumption Forecasting of IAEA energy

Editors and affiliations

  • Tutut Herawan
    • 1
  • Haruna Chiroma
    • 2
  • Jemal H. Abawajy
    • 3
  1. 1.University of MalayaKuala LumpurMalaysia
  2. 2.Federal College of Education (Technical)GombeNigeria
  3. 3.Deakin UniversityGeelongAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-69889-2
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Energy
  • Print ISBN 978-3-319-69888-5
  • Online ISBN 978-3-319-69889-2
  • Series Print ISSN 1865-3529
  • Series Online ISSN 1865-3537
  • Buy this book on publisher's site
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