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LEADER 00000cam 22002415i 4500
008 180606s2019 gw o 001 0 eng d
020 9783030082291
050 4 Q342|b.E965 2019
245 00 Evolutionary and Swarm Intelligence Algorithms /|cedited
by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R.
Pal.
250 1st ed.
260 Cham :|bSpringer International Publishing :|bImprint:
Springer,|c2019.
300 x, 190 p. :|bill. ;|c24 cm.
490 1 Studies in Computational Intelligence,|x1860-949X ;|v779
500 KH-AUL-8
505 0 Swarm and Evolutionary Computation -- Particle Swarm
Optimization -- Artificial Bee Colony Algorithm Variants
and Its Application to Colormap Quantization -- Spider
Monkey Optimization Algorithm -- Genetic Algorithm and Its
Advances in Embracing Memetics -- Constrained Multi-
Objective Evolutionary Algorithm -- Genetic Programming
for Classification and Feature Selection -- Genetic
Programming for Job Shop Scheduling -- Evolutionary Fuzzy
Systems: A Case Study for Intrusion Detection Systems.
520 This book is a delight for academics, researchers and
professionals working in evolutionary and swarm computing,
computational intelligence, machine learning and
engineering design, as well as search and optimization in
general. It provides an introduction to the design and
development of a number of popular and recent swarm and
evolutionary algorithms with a focus on their applications
in engineering problems in diverse domains. The topics
discussed include particle swarm optimization, the
artificial bee colony algorithm, Spider Monkey
optimization algorithm, genetic algorithms, constrained
multi-objective evolutionary algorithms, genetic
programming, and evolutionary fuzzy systems. A friendly
and informative treatment of the topics makes this book an
ideal reference for beginners and those with experience
alike.
650 0 Artificial intelligence
650 0 Computational intelligence
700 1 Bansal, Jagdish Chand
700 1 Pal, Nikhil R.|eeditor
700 1 Singh, Pramod Kumar