|
|
|
|
| LEADER |
04061nma a2201057 u 4500 |
| 001 |
EB001974673 |
| 003 |
EBX01000000000000001137575 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
210512 ||| eng |
| 020 |
|
|
|a 9783039288908
|
| 020 |
|
|
|a 9783039288892
|
| 020 |
|
|
|a books978-3-03928-890-8
|
| 100 |
1 |
|
|a Lytras, Miltiadis
|
| 245 |
0 |
0 |
|a Artificial Intelligence for Smart and Sustainable Energy Systems and Applications
|h Elektronische Ressource
|
| 260 |
|
|
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2020
|
| 300 |
|
|
|a 1 electronic resource (258 p.)
|
| 653 |
|
|
|a machine learning
|
| 653 |
|
|
|a smart grids
|
| 653 |
|
|
|a optimization algorithms
|
| 653 |
|
|
|a forecasting
|
| 653 |
|
|
|a static young’s modulus
|
| 653 |
|
|
|a genetic algorithm
|
| 653 |
|
|
|a RPN
|
| 653 |
|
|
|a smart villages
|
| 653 |
|
|
|a scheduling
|
| 653 |
|
|
|a multiple kernel learning
|
| 653 |
|
|
|a NILM
|
| 653 |
|
|
|a smart metering
|
| 653 |
|
|
|a drill-in fluid
|
| 653 |
|
|
|a deep learning
|
| 653 |
|
|
|a policy making
|
| 653 |
|
|
|a LSTM
|
| 653 |
|
|
|a smart city
|
| 653 |
|
|
|a self-adaptive differential evolution algorithm
|
| 653 |
|
|
|a insulator
|
| 653 |
|
|
|a LR
|
| 653 |
|
|
|a feature extraction
|
| 653 |
|
|
|a smart cities
|
| 653 |
|
|
|a mud rheology
|
| 653 |
|
|
|a artificial neural network
|
| 653 |
|
|
|a ELR
|
| 653 |
|
|
|a ERELM
|
| 653 |
|
|
|a yield point
|
| 653 |
|
|
|a sandstone reservoirs
|
| 653 |
|
|
|a object detection
|
| 653 |
|
|
|a non-intrusive load monitoring
|
| 653 |
|
|
|a Faster R-CNN
|
| 653 |
|
|
|a Jetson TX2
|
| 653 |
|
|
|a wireless sensor networks
|
| 653 |
|
|
|a nonintrusive load monitoring
|
| 653 |
|
|
|a sensor network
|
| 653 |
|
|
|a load
|
| 653 |
|
|
|a MCP39F511
|
| 653 |
|
|
|a transient signature
|
| 653 |
|
|
|a energy disaggregation
|
| 653 |
|
|
|a demand response
|
| 653 |
|
|
|a home energy management systems
|
| 653 |
|
|
|a energy management
|
| 653 |
|
|
|a demand side management
|
| 653 |
|
|
|a smart grid
|
| 653 |
|
|
|a support vector machine
|
| 653 |
|
|
|a energy
|
| 653 |
|
|
|a energy efficient coverage
|
| 653 |
|
|
|a CNN
|
| 653 |
|
|
|a internet of things
|
| 653 |
|
|
|a ambient assisted living
|
| 653 |
|
|
|a RELM
|
| 653 |
|
|
|a artificial intelligence
|
| 653 |
|
|
|a home energy management
|
| 653 |
|
|
|a computational intelligence
|
| 653 |
|
|
|a decision tree
|
| 653 |
|
|
|a distributed genetic algorithm
|
| 653 |
|
|
|a load disaggregation
|
| 653 |
|
|
|a plastic viscosity
|
| 653 |
|
|
|a artificial neural networks
|
| 653 |
|
|
|a conditional random fields
|
| 653 |
|
|
|a Marsh funnel
|
| 653 |
|
|
|a price
|
| 653 |
|
|
|a sustainable development
|
| 700 |
1 |
|
|a Chui, Kwok Tai
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b DOAB
|a Directory of Open Access Books
|
| 500 |
|
|
|a Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
|
| 024 |
8 |
|
|a 10.3390/books978-3-03928-890-8
|
| 856 |
4 |
0 |
|u https://directory.doabooks.org/handle/20.500.12854/41352
|3 Volltext
|
| 082 |
0 |
|
|a 000
|
| 082 |
0 |
|
|a 576
|
| 082 |
0 |
|
|a 333
|
| 082 |
0 |
|
|a 700
|
| 520 |
|
|
|a 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.
|