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.
Auteur
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. Abawajy's 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.
Basic descriptions of computational intelligence algorithms (single, hybrid, ensemble, integrated and etc.- Credible sources of energy datasets.- Applications of computational algorithms in energy.- Practical application of cuckoo search and neural network in the prediction of OECD oil consumption.- Hybrid of Fuzzy systems and particle swarm optimization in the forecasting gas flaring from oil consumption.- Forecasting of OECD gas flaring using Elman neural network and cuckoo search algorithm.- Artificial bee colony and neural network for the forecasting of Malaysia renewable energy.- Soft computing methods in the modelling of OECD carbon dioxide emission from petroleum consumption.- Modelling energy crises based on Soft computing.- The forecasting of WTI and Dubai crude oil prices benchmarks based on soft computing.- A new approach for the forecasting of IAEA energy.- Modelling of gasoline prices using fuzzy multi-criteria decision making.- Soft computing for the prediction of Australia petroleum consumption based on OECD countries.- Future research problems in the area of computational intelligence algorithms in energy.