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Books > Professional & Technical > Energy technology & engineering > Electrical engineering
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Modern Music-Inspired Optimization Algorithms for Electric Power Systems - Modeling, Analysis and Practice (Hardcover, 1st ed. 2019)
Loot Price: R6,040
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Modern Music-Inspired Optimization Algorithms for Electric Power Systems - Modeling, Analysis and Practice (Hardcover, 1st ed. 2019)
Series: Power Systems
Expected to ship within 10 - 15 working days
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In today's world, with an increase in the breadth and scope of
real-world engineering optimization problems as well as with the
advent of big data, improving the performance and efficiency of
algorithms for solving such problems has become an indispensable
need for specialists and researchers. In contrast to conventional
books in the field that employ traditional single-stage
computational, single-dimensional, and single-homogeneous
optimization algorithms, this book addresses multiple newfound
architectures for meta-heuristic music-inspired optimization
algorithms. These proposed algorithms, with multi-stage
computational, multi-dimensional, and multi-inhomogeneous
structures, bring about a new direction in the architecture of
meta-heuristic algorithms for solving complicated, real-world,
large-scale, non-convex, non-smooth engineering optimization
problems having a non-linear, mixed-integer nature with big data.
The architectures of these new algorithms may also be appropriate
for finding an optimal solution or a Pareto-optimal solution set
with higher accuracy and speed in comparison to other optimization
algorithms, when feasible regions of the solution space and/or
dimensions of the optimization problem increase. This book, unlike
conventional books on power systems problems that only consider
simple and impractical models, deals with complicated,
techno-economic, real-world, large-scale models of power systems
operation and planning. Innovative applicable ideas in these models
make this book a precious resource for specialists and researchers
with a background in power systems operation and planning. Provides
an understanding of the optimization problems and algorithms,
particularly meta-heuristic optimization algorithms, found in
fields such as engineering, economics, management, and operations
research; Enhances existing architectures and develops innovative
architectures for meta-heuristic music-inspired optimization
algorithms in order to deal with complicated, real-world,
large-scale, non-convex, non-smooth engineering optimization
problems having a non-linear, mixed-integer nature with big data;
Addresses innovative multi-level, techno-economic, real-world,
large-scale, computational-logical frameworks for power systems
operation and planning, and illustrates practical training on
implementation of the frameworks using the meta-heuristic
music-inspired optimization algorithms.
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