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Data Analytics for Smart Grids Applications—A Key to Smart City Development

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Cover of 'Data Analytics for Smart Grids Applications—A Key to Smart City Development'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Data Analytics for Smart Grids and Applications—Present and Future Directions
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    Chapter 2 Design, Optimization and Performance Analysis of Microgrids Using Multi-agent Q-Learning
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    Chapter 3 Big Data Analytics for Smart Grid: A Review on State-of-Art Techniques and Future Directions
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    Chapter 4 Smart Grid Management for Smart City Infrastructure Using Wearable Sensors
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    Chapter 5 Studies on Conventional and Advanced Machine Learning Algorithm Towards Framing of Robust Data Analytics for the Smart Grid Application
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    Chapter 6 Prediction and Classification for Smart Grid Applications
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    Chapter 7 A Review on Smart Metering Using Artificial Intelligence and Machine Learning Techniques: Challenges and Solutions
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    Chapter 8 Machine Learning Applications for the Smart Grid Infrastructure
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    Chapter 9 A Privacy Mitigating Framework for the Smart Grid Internet of Things Data
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    Chapter 10 Protecting Future of Energy: Data Security and Privacy for Smart Grid Applications Using MATLAB
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    Chapter 11 Revolutionizing Smart Grids with Big Data Analytics: A Case Study on Integrating Renewable Energy and Predicting Faults
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    Chapter 12 Fake User Account Detection in Online Social Media Networks Using Machine Learning and Neural Network Techniques
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    Chapter 13 Data Analytics for Smart Grids Applications to Improve Performance, Optimize Energy Consumption, and Gain Insights
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    Chapter 14 Advanced Digital Twin Technology: Opportunity and Challenges
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    Chapter 15 Machine Learning Applications for the Smart Grid
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    Chapter 16 Intelligent Data Collection Devices in Smart Grid
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    Chapter 17 5G Multi-Carrier Modulation Techniques: Prototype Filters, Power Spectral Density, and Bit Error Rate Performance
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    Chapter 18 Towards Applications of Machine Learning Algorithms for Sustainable Systems and Precision Agriculture
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    Chapter 19 Innovative Smart Grid Solutions for Fostering Data Security and Effective Privacy Preservation
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    Chapter 20 Unification of Internet of Video Things (IoVT) and Smart Grid Towards Emerging Information and Communication Technology (ICT) Systems
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    Chapter 21 Human Face Recognition and Facial Attribute Analysis Using Data Analytics Techniques in Smart Grid Using Image Processing
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    Chapter 22 Data Analytics Techniques for Smart Grids Applications Using Machine Learning
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    Chapter 23 Homorphic Encryption in Smart Grid System for Secure Information Aggregation
Attention for Chapter 18: Towards Applications of Machine Learning Algorithms for Sustainable Systems and Precision Agriculture
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Chapter title
Towards Applications of Machine Learning Algorithms for Sustainable Systems and Precision Agriculture
Chapter number 18
Book title
Data Analytics for Smart Grids Applications—A Key to Smart City Development
Published in
Intelligent Systems Reference Library, January 2023
DOI 10.1007/978-3-031-46092-0_18
Book ISBNs
978-3-03-146091-3, 978-3-03-146092-0
Authors

Juyal, Aayush, Bhushan, Bharat, Hameed, Alaa Ali

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The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

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Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 100%
Readers by discipline Count As %
Psychology 3 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 December 2023.
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#17,732,227
of 25,992,468 outputs
Outputs from Intelligent Systems Reference Library
#1
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#276,358
of 482,636 outputs
Outputs of similar age from Intelligent Systems Reference Library
#1
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