Artificial Intelligence for Smart and Sustainable Energy Systems and Applications

Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy researc...

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Bibliographic Details
Main Authors: Lytras, Miltiadis, Chui, Kwok Tai
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
ambient assisted living
artificial intelligence
artificial neural network
artificial neural networks
CNN
computational intelligence
conditional random fields
decision tree
deep learning
demand response
demand side management
distributed genetic algorithm
drill-in fluid
ELR
energy
energy disaggregation
energy efficient coverage
energy management
ERELM
Faster R-CNN
feature extraction
forecasting
genetic algorithm
History of engineering and technology
home energy management
home energy management systems
insulator
internet of things
Jetson TX2
load
load disaggregation
LSTM
machine learning
Marsh funnel
MCP39F511
mud rheology
multiple kernel learning
NILM
non-intrusive load monitoring
nonintrusive load monitoring
object detection
optimization algorithms
plastic viscosity
policy making
price
RELM
RPN
sandstone reservoirs
scheduling
self-adaptive differential evolution algorithm
sensor network
smart cities
smart city
smart grid
smart grids
smart metering
smart villages
static young’s modulus
support vector machine
sustainable development
T1-995
TA1-2040
Technology, Engineering, Agriculture, Industrial processes
Technology: general issues
transient signature
wireless sensor networks
yield point
ISBN:9783039288892, 9783039288908, 3039288903, 303928889X
Online Access:Get full text
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Summary:Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy research, particularly research devoted to non-intrusive load monitoring, network, and grid, as well as other emerging topics. The presented artificial intelligence algorithms may provide insight into how to apply similar approaches, subject to fine-tuning and customization, to other unexplored energy research. The ultimate goal is to fully apply artificial intelligence to the energy sector. This book may serve as a guide for professionals, researchers, and data scientists—namely, how to share opinions and exchange ideas so as to facilitate a better fusion of energy, academic, and industry research, and improve in the quality of people's daily life activities.
ISBN:9783039288892
9783039288908
3039288903
303928889X
DOI:10.3390/books978-3-03928-890-8