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E-grāmata: Advances on Computational Intelligence in Energy: The Applications of Nature-Inspired Metaheuristic Algorithms in Energy

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  • Formāts: EPUB+DRM
  • Sērija : Green Energy and Technology
  • Izdošanas datums: 12-Jul-2019
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319698892
  • Formāts - EPUB+DRM
  • Cena: 106,47 €*
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  • Formāts: EPUB+DRM
  • Sērija : Green Energy and Technology
  • Izdošanas datums: 12-Jul-2019
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319698892

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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.

A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
1(20)
Haruna Chiroma
Usman Ali Abdullahi
Ibrahim Abaker Targio Hashem
Younes Saadi
Rawaa Dawoud Al-Dabbagh
Muhammad Murtala Ahmad
Gbenga Emmanuel Dada
Sani Danjuma
Jaafar Zubairu Maitama
Adamu Abubakar
Shafi'i Muhammad Abdulhamid
Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network
21(18)
Mustafa Tareq
Saad Adnan Abed
Elankovan A. Sundararajan
A Novel Chicken Swarm Neural Network Model for Crude Oil Price Prediction
39(20)
Abdullah Khan
Rahmat Shah
Junaid Bukhari
Nasreen Akhter
Attaullah
Muhammad Idrees
Hilal Ahmad
Forecasting OPEC Electricity Generation Based on Elman Network Trained by Cuckoo Search Algorithm
59(18)
Abdullah Khan
Rahmat Shah
Nasreen Akhter
Awais Qureshi
Kamran Ullah
Hilal Ahmad
Muhammad Idrees
Variable Neighborhood Search-Based Symbiotic Organisms Search Algorithm for Energy-Efficient Scheduling of Virtual Machine in Cloud Data Center
77(22)
Mohammed Abdullahi
Shafi'i Muhammad Abdulhamid
Salihu Idi Dishing
Mohammed Joda Usman
Energy Savings in Heterogeneous Networks with Self-Organizing Backhauling
99(26)
Nasir Faruk
Abdulkarim A. Oloyede
Abubakar Abdulkarim
Lukman A. Olawoyin
Yinusa A. Adediran
Integrated Resource Allocation Model for Cloud and Fog Computing: Toward Energy-Efficient Infrastructure as a Service (IaaS)
125(22)
Mohammed Joda Usman
Abdul Samad Ismail
Hassan Chizari
Abdulsalam Ya'u Gital
Haruna Chiroma
Mohammed Abdullahi
Ahmed Aliyu
Energy-Efficient Bias-Based User Association for Heterogeneous Networks in LTE-Advanced
147(22)
Ayuba K. Danburam
Mohammed A. Gadam
Aliyu D. Usman
Suleiman M. Sani
Energy Efficiency of Backhauling Options for Future Heterogeneous Networks
169(26)
Nasir Faruk
Abubakar Abdulkarim
Nazmat T. Surajudeen-Bakinde
Segun I. Popoola
Analysis of Energy Consumption Model in Cloud Computing Environments
195
Zhou Zhou
Jemal H. Abawajy
Fangmin Li
Dr. Tutut Herawan received a B.Ed degree (2002) and M.Sc degree (2006) in Mathematics from the Universitas Ahmad Dahlan and Universitas Gadjah Mada Yogyakarta, Indonesia, respectively. In 2010, he obtained a PhD in Computer Science from the Universiti Tun Hussein Onn Malaysia. During 2010-2012, he worked as a senior lecturer at the Department of Computer Science and as a co-ordinator of the Data Mining and Knowledge Management research group in the Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang (UMP). Currently a senior lecturer at the Department of Information System, University of Malaya, Herawan has successfully co-supervised 3 PhDs and currently supervises 8 PhDs. Herawan has published papers in various international journals, conference proceedings and book chapters, and has been appointed to the editorial board for MJCS (SCIE), IJDTA, TELKOMNIKA (scopus), IJNCAA, IJDCA and IJDIWC. He has also been appointed as a reviewer of several international journals and as a guest editor for several special issues, such as TELKOMNIKA journal, Applied Soft Computing Elsevier, and IJMISSP Inderscience. Herawan has served as a Chair, PC chair, program committee member and co-organizer for numerous international conferences/workshops. His research area includes data mining and knowledge discovery, decision support in information system, and rough and soft set theory.





















Haruna Chiroma possessed B.Tech., Msc, and Ph.D.  He has published over 100 academic articles including ISI WoS indexed journals such as Applied Soft Computing (Elsevier), PLoS ONE, International Journal of Information Management (Elsevier), Applied Energy (Elsevier), Neural Computing and Applications (Springer), SpringerPLus (Springer), etc. His research interest includes: nature inspired algorithms, deep learning, machine learning and their applications in internet of vehicles, self-driving vehicles, big data analytics, cybersecurity, IoT and edge computing. He is a reviewer for 17 ISI WoS indexed journals with impact factor. Chiroma is an associate editor of IEEE Access ISI/WoS Indexed with impact factor of 3.55. Leading Guest Editor for Journal of Optimization (ESCI WoS indexed) Hindawi. Volume Editor of an edited book in Green Energy and Technology series (Scopus indexed) - Springer. He has been a technical programme committee member for more than 20 high profile international conferences Springer, IEEE. He was invited by QS world universities ranking body Intelligent Unit in 2017 and 2018 to evaluate research strength of universities in computer science. Chiroma is presently a lecturer at the Federal College of Education (Technical), Gombe and visiting senior lecturer at the Abubakar Tafawa Balewa University, Bauchi, Nigeria. He is supervising Ph.D. and M.Sc. students. 















Jemal H. Abawajy is a professor at the school of Information Technology, Faculty of Science, Engineering and Built Environment, Deakin University, Australia. He is the current director of the Parallel and Distributing Computing Laboratory and is a senior member of IEEE Computer Society; IEEE Technical Committee on Scalable Computing (TCSC); IEEE Technical Committee on Dependable Computing and Fault Tolerance and IEEE Communication Society. Abawajys leadership is extensive spanning industrial, academic and professional areas. He has served on the Academic Board, Faculty Board, IEEE Technical Committee on Scalable Computing Performance track coordinator, Research Integrity Advisory Group, Research Committee, Teaching and Learning Committee and Expert of International Standing Grant and external PhD thesis assessor. Having delivered more than 50 keynote addresses, Abawajy has been actively involved in the organization of more than 200 national and international conferences in various capacity including chair and vice-chair.Having served on the numerous editorial boards for international journals, Abawajy is currently serving as Associate Editor of the International Journal of Big Data Intelligence and International Journal of Parallel, Emergent and Distributed Systems. Abawajy is actively involved in funded research supervising large number of PhD students, postdoctoral, research assistants and visiting scholar in the area of Cloud Computing, Big Data, Network and System Security, Decision Support System, and E-healthcare. He is the author/coauthor of five books, more than 250 papers in conferences, book chapters and journals such as IEEE Transactions on Computers and IEEE Transactions on Fuzzy Systems. He has also edited 10 conference volumes.