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Modern Music-Inspired Optimization Algorithms for Electric Power Systems: Modeli

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Last updated on Apr 01, 2024 08:20:29 EDTView all revisionsView all revisions

Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN-13
9783030120436
Type
NA
Publication Name
NA
ISBN
9783030120436
Publication Year
2019
Format
Hardcover
Language
English
Book Title
Modern Music-Inspired Optimization Algorithms for Electric Power Systems : Modeling, Analysis and Practice
Author
Mohammad Kiani-Moghaddam, Mojtaba Shivaie, Philip D. Weinsier
Item Length
9.3in
Publisher
Springer International Publishing A&G
Genre
Technology & Engineering, Computers, Mathematics
Topic
Power Resources / Electrical, Intelligence (Ai) & Semantics, Optimization
Item Width
6.1in
Item Weight
45.6 Oz
Number of Pages
Xxvii, 727 Pages

About this product

Product Information

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.

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3030120430
ISBN-13
9783030120436
eBay Product ID (ePID)
28038547561

Product Key Features

Book Title
Modern Music-Inspired Optimization Algorithms for Electric Power Systems : Modeling, Analysis and Practice
Author
Mohammad Kiani-Moghaddam, Mojtaba Shivaie, Philip D. Weinsier
Format
Hardcover
Language
English
Topic
Power Resources / Electrical, Intelligence (Ai) & Semantics, Optimization
Publication Year
2019
Genre
Technology & Engineering, Computers, Mathematics
Number of Pages
Xxvii, 727 Pages

Dimensions

Item Length
9.3in
Item Width
6.1in
Item Weight
45.6 Oz

Additional Product Features

Number of Volumes
1 Vol.
Lc Classification Number
Tk1001-1841
Table of Content
Chapter1: Introduction to Meta-Heuristic Optimization Algorithms.- Chapter2: Introduction to Multi-Objective Optimization and Decision Making Analysis.- Chapter3: Music-Inspired Optimization Algorithms: From Past to Present.- Chapter4: Advances in Music-Inspired Optimization Algorithms.- Chapter5: Power Systems Operation.- Chapter6: Power Systems Planning.- Chapter7: Power Quality Planning.
Copyright Date
2019
Series
Power Systems Ser.
Illustrated
Yes

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