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Optimization, Learning, and Control for Interdependent Complex Networks

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Cover of 'Optimization, Learning, and Control for Interdependent Complex Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Panorama of Optimization, Control, and Learning Algorithms for Interdependent SWEET (Societal, Water, Energy, Economic, and Transportation) Networks
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    Chapter 2 Promises of Fully Distributed Optimization for IoT-Based Smart City Infrastructures
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    Chapter 3 Evolutionary Computation, Optimization, and Learning Algorithms for Data Science
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    Chapter 4 Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics
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    Chapter 5 Feature Selection in High-Dimensional Data
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    Chapter 6 An Introduction to Advanced Machine Learning: Meta-Learning Algorithms, Applications, and Promises
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    Chapter 7 Predictive Analytics in Future Power Systems: A Panorama and State-Of-The-Art of Deep Learning Applications
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    Chapter 8 Bi-level Adversary-Operator Cyberattack Framework and Algorithms for Transmission Networks in Smart Grids
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    Chapter 9 Toward Operational Resilience of Smart Energy Networks in Complex Infrastructures
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    Chapter 10 Control of Cooperative Unmanned Aerial Vehicles: Review of Applications, Challenges, and Algorithms
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    Chapter 11 An Optimal Approach for Load-Frequency Control of Islanded Microgrids Based on Nonlinear Model
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    Chapter 12 Photovoltaic Design for Smart Cities and Demand Forecasting Using a Truncated Conjugate Gradient Algorithm
Attention for Chapter 11: An Optimal Approach for Load-Frequency Control of Islanded Microgrids Based on Nonlinear Model
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Citations

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Chapter title
An Optimal Approach for Load-Frequency Control of Islanded Microgrids Based on Nonlinear Model
Chapter number 11
Book title
Optimization, Learning, and Control for Interdependent Complex Networks
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-34094-0_11
Book ISBNs
978-3-03-034093-3, 978-3-03-034094-0
Authors

Fatemeh Jamshidi, Mohammad Reza Salehizadeh, Fatemeh Gholami, Miadreza Shafie-khah

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 40%
Student > Ph. D. Student 1 20%
Unspecified 1 20%
Unknown 1 20%
Readers by discipline Count As %
Engineering 2 40%
Energy 1 20%
Unspecified 1 20%
Unknown 1 20%