Articles by "Artificial Intelligence"

Showing posts with label Artificial Intelligence. Show all posts

Monday, June 20, 2016 , , , ,
Xin-She Yang ... 300 pages - Publisher: Elsevier; 1st edition (March, 2014) ... 
Language: English - ISBN-10: 0124167438 - ISBN-13: 978-0124167438 ...

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. * * * Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature + Provides a theoretical understanding as well as practical implementation hints + Provides a step-by-step introduction to each algorithm.
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Monday, May 23, 2016 , ,
B. H. Topping ... 
Volume I: 653 pages - Publisher: Springer; Reprint of the original 1st (1992) edition (December 3, 2010)
Language: English - ISBN-10: 9048142016 - ISBN-13: 978-9048142019

Volume II: 354 pages - Publisher: Springer; Reprint of the original 1st (1992) edition (December 8, 2010)
Language: English - ISBN-10: 9048142024 - ISBN-13: 978-9048142026

This volume and its companion volume includes the edited versions of the principal lectures and selected papers presented at the NATO Advanced Study Institute on Optimization and Decision Support Systems in Civil Engineering. The Institute was held in the Department of Civil Engineering at Heriot-Watt University, Edinburgh from June 25th to July 6th 1989 and was attended by eighty participants from Universities and Research Institutes around the world. A number of practising civil and structural engineers also attended. The lectures and papers have been divided into two volumes to reflect the dual themes of the Institute namely Optimization and Decision Support Systems in Civil Engineering. Planning for this ASI commenced in late 1986 when Andrew Templeman and I discussed developments in the use of the systems approach in civil engineering. A little later it became clear that much of this approach could be realised through the use of knowledge-based systems and artificial intelligence techniques. Both Don Grierson and John Gero indicated at an early stage how important it would be to include knowledge-based systems within the scope of the Institute. The title of the Institute could have been: 'Civil Engineering Systems' as this would have reflected the range of systems applications to civil engineering problems considered by the Institute. These volumes therefore reflect the full range of these problems including: structural analysis and design; water resources engineering; geotechnical engineering; transportation and environmental engineering.
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Saturday, May 21, 2016 , , , ,
Kurt Marti ... 368 pages - Publisher: Springer; 3rd edition (February, 2015) ... Language: English - ISBN-10: 3662462133 - ISBN-13: 978-3662462133 ...

This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems.Due to the probabilities and expectations involved, the book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.
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