Frontier Applications of Nature Inspired Computation

1. Auflage 2020
ISBN: 978-981-15-2132-4
Verlag: Springer

Buch, Englisch, 389 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 843 g

Reihe: Springer Tracts in Nature-Inspired Computing

This book addresses the frontier advances in the theory and application of nature-inspired optimization techniques, including solving the quadratic assignment problem, prediction in nature-inspired dynamic optimization, the lion algorithm and its applications, optimizing the operation scheduling of microgrids, PID controllers for two-legged robots, optimizing crane operating times, planning electrical energy distribution systems, automatic design and evaluation of classification pipelines, and optimizing wind-energy power generation plants. The book also presents a variety of nature-inspired methods and illustrates methods of adapting these to said applications.

Nature-inspired computation, developed by mimicking natural phenomena, makes a significant contribution toward the solution of non-convex optimization problems that normal mathematical optimizers fail to solve. As such, a wide range of nature-inspired computing approaches has been used in multidisciplinary engineering applications. Written by researchers and developers from a variety of fields, this book presents the latest findings, novel techniques and pioneering applications.

Zielgruppe

Research

Autoren/Hrsg.

Khosravy, Mahdi

Gupta, Neeraj

Patel, Nilesh

Senjyu, Tomonobu

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie

Inhaltsverzeichnis

Nature-inspired Metaheuristic Optimization: Recent Advances and Applications.- Prediction in Nature Inspired Dynamic Optimization.- Plants Genetics Inspired Evolutionary Optimization: A Descriptive Tutorial.- Trends on fitness landscape analysis in evolutionary computation and meta-heuristics.- Lion Algorithm and its Applications.- A self-adaptive nature-inspired procedure for solving the quadratic assignment problem.

Über Autor(innen)

Mahdi Khosravy was born in Birjand city, Iran, 1979. He received BSc. in Electrical Engineering (bio-electric) from Sahand University of Technology, Tabriz, Iran, and MSc. in Biomedical Engineering (bio-electric) from Beheshti University of Medical Studies, Tehran, Iran. Mahdi received his Ph.D. in the field of Information Technology from University of the Ryukyus, Okinawa, Japan. He was awarded by the head of University for his excellence in research activities. To grow his international experience in education and research, in September 2010, he joined the University of Information Science and Technology (UIST), Ohrid, Macedonia, in the capacity of assistant professor. In 2016, he established a journal in information technology (ejist.uist.edu.mk) in UIST as currently hold its executive editorship. UIST professorship helped him a lot to extend his international collaborations. In July 2017, he became an associate professor. From August 2018 he joined the Energy lab in University of the Ryukyus as a Visiting Researcher. Since April 2018, he is jointly a visiting associate professor in the Electrical Engineering Department, Federal Universit of Juiz de Fora in Brazil. Since November 2019, Dr Khosravy is an appointed researcher in media-integrated laboratories, University of Osaka, Japan. Dr. Khosravy is a member of IEEE. Dr. Khosravy is a member of IEEE. Neeraj Gupta was born in India on November 1979. Multidisciplinary graduation studies provide him the ability to make fusion of different engineering fields to explore cutting-edge research in optimization, information technology, network design, image, and smart grids. He got diploma in civil engineering (specialized in environmental and pollution control) in 1999, Bachelor of Engineering in electrical and electronics engineering in 2003, Master of Technology (M.Tech.) in engineering systems in 2006, and Ph.D. in economic operation of power systems (power & control) in February 2013 from IIT Kanpur, India. He worked as postdoctoral fellow (Sr. Project Engineer) at Indian Institute of Technology (IIT) Jodhpur, India, for one year (June 2012–May 2013). Thereafter, he joined the same institute as faculty (May 2013–August 2014). He has also two years of industrial along with academic experience before M.Tech. At IIT Jodhpur, he was involved as collaborator in many national and international projects funded from MNRE, UNICEF, etc. He was the Assistant. Professor at the University for Information Science and Technology, “St. Paul the Apostle,”, Ohrid, Macedonia, from 2014 to 2017. Currently, he is teaching and research staff in the Department of Engineering and Technology, Oakland University, USA. Due to the exposition of different engineering fields and wide research domain, his current research interests are in the fields of optimization, smart grid technology, smart cities, big data problem, multiagent modeling, IoT and applications, development of heuristic optimization algorithms, particularly in the areas of multilateral and real-time operation of the complex systems.

Nilesh Patel is an Associate Professor in the Department of Computer Science and Engineering at Oakland University, Rochester, Michigan. Prior to his tenure at Oakland University, he served as an Assistant Professor at the University of Michigan, Dearborn. In addition to his academic service, Dr. Patel served as a Software Architect and Software Engineering Manager at Ford Motors and Visteon Corporation, where he played an instrumental role in design and development of first voice-enabled vehicular control and GPS navigation systems. His research interests include deep machine learning, pattern recognition, visual computing, evolutionary computing, and big data analytics.

Tomonobu Senjyu (SM'06) was born in Saga Prefecture, Japan, in 1963. He received the B.S. and M.S. degrees in Electrical Engineering from the University of the Ryukyus, Nishihara, Japan, in 1986 and 1988,respectively, and the Ph.D. degree in Electrical Engineering from Nagoya University, Nagoya, Japan, in 1994. He is currently a Full Professor in the Department of Electrical and Electronics Engineering, University of the Ryukyus. His research interests are in the areas of renewable energy, power system optimization and operation, power electronics, and advanced control of electrical machines.