Modern Music-Inspired Optimization Algorithms for Electric Power Systems: Modeling, Analysis and Practice, Kiani-Moghaddam Mohammad, Shivaie Mojtaba, Weinsier Philip D.
Автор: Mohammad Kiani-Moghaddam; Mojtaba Shivaie; Philip Название: Modern Music-Inspired Optimization Algorithms for Electric Power Systems ISBN: 3030120430 ISBN-13(EAN): 9783030120436 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
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.
Автор: F.Carl Knopf Название: Modeling, Analysis and Optimization of Process and Energy Systems ISBN: 0470624213 ISBN-13(EAN): 9780470624210 Издательство: Wiley Рейтинг: Цена: 118220.00 T Наличие на складе: Поставка под заказ. Описание: Energy costs impact the profitability of virtually all industrial processes.
Автор: Dan Gusfield Название: Integer Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course ISBN: 1108421768 ISBN-13(EAN): 9781108421768 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Integer linear programming is a versatile modeling and optimization technique with potential to transform biological computation. This hands-on text, designed for students, researchers, and professionals in both biology and computational fields, demonstrates applications in genomics, RNA and protein folding, DNA sequencing, phylogenetics, and more.
Автор: Dash Sujata, Tripathy B. K., Rahman Atta Ur Название: Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms ISBN: 1522528571 ISBN-13(EAN): 9781522528579 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 257790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems.The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.
Автор: Steven L. Brunton, J. Nathan Kutz Название: Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control ISBN: 1108422098 ISBN-13(EAN): 9781108422093 Издательство: Amazon Internet Рейтинг: Цена: 0.00 T Наличие на складе: Невозможна поставка. Описание: Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. Aimed at advanced undergraduate and beginning graduate students, this textbook provides an integrated viewpoint that shows how to apply emerging methods from data science, data mining, and machine learning to engineering and the physical sciences.
Автор: Fan, Mingtian, Название: Mathematical models and algorithms for power system optimization : ISBN: 0128132310 ISBN-13(EAN): 9780128132319 Издательство: Elsevier Science Рейтинг: Цена: 150470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Mathematical Models and Algorithms for Power System Optimization helps readers build a thorough understanding of new technologies and world-class practices developed by the State Grid Corporation of China, the organization responsible for the world's largest power distribution network. This reference covers three areas: power operation planning, electric grid investment and operational planning and power system control. It introduces economic dispatching, generator maintenance scheduling, power flow, optimal load flow, reactive power planning, load frequency control and transient stability, using mathematic models including optimization, dynamic, differential and difference equations.
Provides insights on the development of new mathematical models of power system optimization
Analyzes power systems comprehensively to create novel mathematic models and algorithms for issues related to the planning operation of power systems
Includes research on the optimization of power systems and related practical research projects carried out since 1981
Автор: Resener Mariana, Rebennack Steffen, Pardalos Panos Название: Handbook of Optimization in Electric Power Distribution Systems ISBN: 3030361144 ISBN-13(EAN): 9783030361143 Издательство: Springer Рейтинг: Цена: 167700.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This handbook gathers state-of-the-art research on optimization problems in power distribution systems, covering classical problems as well as the challenges introduced by distributed power generation and smart grid resources.
Автор: Soliman Abdel-Hady Soliman; Abdel-Aal Hassan Manta Название: Modern Optimization Techniques with Applications in Electric Power Systems ISBN: 148998979X ISBN-13(EAN): 9781489989796 Издательство: Springer Рейтинг: Цена: 144410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presenting ways of using AI optimization techniques to operate and control electric power systems, this book is full of practical applications and examples and features, among other methods, functional analysis, simulated annealing and Tabu-search.
Автор: Karl Frauendorfer; Hans Glavitsch; Rainer Bacher Название: Optimization in Planning and Operation of Electric Power Systems ISBN: 3790807184 ISBN-13(EAN): 9783790807189 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Permanently increasing requirements in power supply necessitate efficient control of electric power systems. This work represents a state-of-the-art of mathematical programming methodologies, unit commitment, optimal power flow and their applications in power system control.
Автор: Omid Bozorg-Haddad Название: Advanced Optimization by Nature-Inspired Algorithms ISBN: 981135345X ISBN-13(EAN): 9789811353451 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.
Автор: Xin-She Yang Название: Nature-Inspired Algorithms and Applied Optimization ISBN: 3319884654 ISBN-13(EAN): 9783319884653 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Нет в наличии. Описание: This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
Автор: Jeffrey Humpherys, Tyler J. Jarvis Название: Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization ISBN: 1611976057 ISBN-13(EAN): 9781611976052 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 81090.00 T Наличие на складе: Невозможна поставка. Описание: In this second book of what will be a four-volume series, the authors present, in a mathematically rigorous way, the essential foundations of both the theory and practice of algorithms, approximation, and optimization—essential topics in modern applied and computational mathematics. This material is the introductory framework upon which algorithm analysis, optimization, probability, statistics, machine learning, and control theory are built. This text gives a unified treatment of several topics that do not usually appear together: the theory and analysis of algorithms for mathematicians and data science students; probability and its applications; the theory and applications of approximation, including Fourier series, wavelets, and polynomial approximation; and the theory and practice of optimization, including dynamic optimization.When used in concert with the free supplemental lab materials, Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization teaches not only the theory but also the computational practice of modern mathematical methods. Exercises and examples build upon each other in a way that continually reinforces previous ideas, allowing students to retain learned concepts while achieving a greater depth. The mathematically rigorous lab content guides students to technical proficiency and answers the age-old question “When am I going to use this?”This textbook is geared toward advanced undergraduate and beginning graduate students in mathematics, data science, or machine learning.
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