This book highlights essential concepts in connection with the traditional bat algorithm and its recent variants, as well as its application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic algorithms are extensively being used to address a wide range of real-world optimization problems due to their adaptability and robustness. Developed in 2009, the bat algorithm (BA) is one of the most successful swarm intelligence procedures, and has been used to tackle optimization tasks for more than a decade. The BA’s mathematical model is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, it has attracted the attention of researchers who are working to find optimal solutions in a diverse range of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization and linear/nonlinear optimization problems. Along with the traditional BA, its enhanced versions are now also being used to solve optimization problems in science, engineering and medical applications around the globe.
"synopsis" may belong to another edition of this title.
Nilanjan Dey is an Assistant Professor at the Department of Information Technology, Techno International New Town (formerly Techno India College of Technology), Kolkata, India. He is also a Visiting Fellow of the University of Reading, UK and a Visiting Professor at Duy Tan University, Vietnam. He was an honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). Holding a Ph.D. from Jadavpur University (2015), he is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence, IGI Global. He is also the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (Springer Nature); Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier); and Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal processing and Data Analysis (CRC). He has authored/edited more than 50 books with Springer, Elsevier, Wiley and CRC Press and published more than 300 peer-reviewed research papers. His main research interests include medical imaging, machine learning, computer-aided diagnosis, and data mining. He is the Indian Ambassador of the International Federation for Information Processing (IFIP) – Young ICT Group.
Venkatesan Rajinikanth is a Professor at the Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai, India. Recently, he edited a book titled Advances in Artificial Intelligence Systems with Nova Science Publisher, USA. He is an Associate Editor for the International Journal of Rough Sets and Data Analysis. Having published more than 75 papers, his main research interests include medical imaging, machine learning and computer-aided diagnosis, as well as data mining.
This book highlights essential concepts in connection with the traditional bat algorithm and its recent variants, as well as its application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic algorithms are extensively being used to address a wide range of real-world optimization problems due to their adaptability and robustness. Developed in 2009, the bat algorithm (BA) is one of the most successful swarm intelligence procedures, and has been used to tackle optimization tasks for more than a decade. The BA’s mathematical model is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, it has attracted the attention of researchers who are working to find optimal solutions in a diverse range of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization and linear/nonlinear optimization problems. Along with the traditional BA, its enhanced versions are now also being used to solve optimization problems in science, engineering and medical applications around the globe.
"About this title" may belong to another edition of this title.
Seller: Brook Bookstore On Demand, Napoli, NA, Italy
Condition: new. Questo è un articolo print on demand. Seller Inventory # 0ed1e477970d764fc3396d209252a7c2
Quantity: Over 20 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9789811550997_new
Quantity: Over 20 available
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book highlights essential concepts in connection with the traditional bat algorithm and its recent variants, as well as its application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic algorithms are extensively being used to address a wide range of real-world optimization problems due to their adaptability and robustness. Developed in 2009, the bat algorithm (BA) is one of the most successful swarm intelligence procedures, and has been used to tackle optimization tasks for more than a decade. The BA's mathematical model is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, it has attracted the attention of researchers who are working to find optimal solutions in a diverse range of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization and linear/nonlinear optimization problems. Along with the traditional BA, its enhanced versions are now also being used to solve optimization problems in science, engineering and medical applications around the globe. 184 pp. Englisch. Seller Inventory # 9789811550997
Quantity: 2 available
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Hence, it has attracted the attention of researchers who are working to find optimal solutions in a diverse range of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization and linear/nonlinear optimization problems. Seller Inventory # 473138589
Quantity: Over 20 available
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP. Seller Inventory # 26386416081
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand. Seller Inventory # 394232334
Quantity: 4 available
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book highlights essential concepts in connection with the traditional bat algorithm and its recent variants, as well as its application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic algorithms are extensively being used to address a wide range of real-world optimization problems due to their adaptability and robustness. Developed in 2009, the bat algorithm (BA) is one of the most successful swarm intelligence procedures, and has been used to tackle optimization tasks for more than a decade. The BA¿s mathematical model is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, it has attracted the attention of researchers who are working to find optimal solutions in a diverse range of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization and linear/nonlinear optimization problems. Along with the traditional BA, its enhanced versions are now also being used to solve optimization problems in science, engineering and medical applications around the globe.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 184 pp. Englisch. Seller Inventory # 9789811550997
Quantity: 1 available
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book highlights essential concepts in connection with the traditional bat algorithm and its recent variants, as well as its application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic algorithms are extensively being used to address a wide range of real-world optimization problems due to their adaptability and robustness. Developed in 2009, the bat algorithm (BA) is one of the most successful swarm intelligence procedures, and has been used to tackle optimization tasks for more than a decade. The BA's mathematical model is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, it has attracted the attention of researchers who are working to find optimal solutions in a diverse range of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization and linear/nonlinear optimization problems. Along with the traditional BA, its enhanced versions are now also being used to solve optimization problems in science, engineering and medical applications around the globe. Seller Inventory # 9789811550997
Quantity: 1 available
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND. Seller Inventory # 18386416091
Quantity: 4 available
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 184 pages. 9.25x6.10x0.44 inches. In Stock. Seller Inventory # x-9811550999
Quantity: 2 available