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Editeur : Springer SingaporeLangue : Anglais Parution : 01/05/2022Format : Moyen, de 350g à 1kgNombre de pages : 244Expédition : 376Dimensions : 23.5 x 15.5 x 1.4
ISBN : 9811606641
Résumé :
Applied Optimization and Swarm Intelligence: A Systematic Review and Prospect Opportunities.- A Review on Ensemble Methods and their Applications to Optimization Problems.- A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining.- Review of Swarm Intelligence for Improving Time Series Forecasting.- Soccer-Inspired Metaheuristics: Systematic Review of Recent Research and Applications.- Formal Cognitive Modeling of Swarm Intelligence for Decision-Making Optimization Problems.- Nature-Inspired Optimization Algorithms for Path Planning and Fuzzy Tracking Control of Mobile Robots.- A Hardware Architecture and Physical Prototype for General-Purpose Swarm Minirobotics: Proteus II.- Evolving a Multi-Objective Optimization Framework.- Swarm Intelligence Based Optimum Design of Deep Excavation System....
Biographie:
Eneko Osaba works at TECNALIA as a senior researcher in the ICT/OPTIMA area. He received the B.S. and M.S. degrees in computer sciences from the University of Deusto, Spain, in 2010 and 2011, respectively. He obtained his Ph.D. degree on artificial intelligence in 2015 in the same university, being the recipient of a Basque Government doctoral grant. Throughout his career, he has participated in the proposal, development and justification of more than 25 local and European research projects. Additionally, Eneko has also participated in the publication of 125 scientific papers (including more than 25 Q1). He has performed several stays in universities of UK (Middlesex University), Italy (Universit? Politecnica delle Merche) and Malta (University of Malta). Eneko has served as a member of the program committee in more than 45 international conferences. Furthermore, he has participated in organizing activities in more than 12 international conferences. Besides this, he is a member of the editorial board of International Journal of Artificial Intelligence, Data in Brief and Journal of Advanced Transportation, and he has acted as the guess editor in journals such as Journal of Computational Science, Neurocomputing, Logic Journal of IGPL, Advances in Mechanical Engineering Journal, Swarm and Evolutionary Computation and IEEE ITS Magazine. In his research profile, it can be found a 19 h-index with 1450 cites in google scholar. Additionally, Eneko was an individual ambassador for ORCID along 2017-2018. Finally, he has nine intellectual property registers, granted by the Basque Government, and he has two European patents under review.
Xin-She Yang obtained his D.Phil. in applied mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as Senior research Scientist. Now he is a reader/professor at Middlesex University London, and the IEEE CIS chair for the task force on business intelligence and knowledge management. With more than 20 years' teaching and research experience, he has authored 15 books and edited 25 books. He has published more than 250 peer-reviewed research papers with nearly 55,000 citations. According to Clarivate Analytics/Web of Sciences, he has been on the prestigious list of highly cited researchers for five consecutive years (2016-2020).
Sommaire:
This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.
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