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Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
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Handbook of Metaheuristic Algorithms - From Fundamental Theories to Advanced Applications (Paperback)
Loot Price: R3,524
Discovery Miles 35 240
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Handbook of Metaheuristic Algorithms - From Fundamental Theories to Advanced Applications (Paperback)
Series: Uncertainty, Computational Techniques, and Decision Intelligence
Expected to ship within 10 - 15 working days
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Handbook of Metaheuristic Algorithms: From Fundamental Theories to
Advanced Applications provides a brief introduction to
metaheuristic algorithms from the ground up, including basic ideas
and advanced solutions. Although readers may be able to find source
code for some metaheuristic algorithms on the Internet, the coding
styles and explanations are generally quite different, and thus
requiring expanded knowledge between theory and implementation.
This book can also help students and researchers construct an
integrated perspective of metaheuristic and unsupervised algorithms
for artificial intelligence research in computer science and
applied engineering domains. Metaheuristic algorithms can be
considered the epitome of unsupervised learning algorithms for the
optimization of engineering and artificial intelligence problems,
including simulated annealing (SA), tabu search (TS), genetic
algorithm (GA), ant colony optimization (ACO), particle swarm
optimization (PSO), differential evolution (DE), and others.
Distinct from most supervised learning algorithms that need labeled
data to learn and construct determination models, metaheuristic
algorithms inherit characteristics of unsupervised learning
algorithms used for solving complex engineering optimization
problems without labeled data, just like self-learning, to find
solutions to complex problems.
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