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Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids

Artificial intelligence techniques, such as expert systems, fuzzy logic, and artificial neural network techniques have become efficient tools in modeling and control applications. For example, there are several benefits in optimizing cost-effectiveness, because fuzzy logic is a methodology for the h...

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Guardat en:
Format: Online
Idioma:anglès
Publicat: MDPI - Multidisciplinary Digital Publishing Institute 2021
Matèries:
droop curve
frequency regulation
fuzzy logic
the rate of change of frequency
reserve power
smart grid
energy Internet
convolutional neural network
decision optimization
deep reinforcement learning
electric load forecasting
non-dominated sorting genetic algorithm II
multi-layer perceptron
adaptive neuro-fuzzy inference system
meta-heuristic algorithms
automatic generation control
fuzzy neural network control
thermostatically controlled loads
back propagation algorithm
particle swarm optimization
load disaggregation
artificial intelligence
cognitive meters
machine learning
state machine
NILM
non-technical losses
semi-supervised learning
knowledge embed
deep learning
distribution network equipment
condition assessment
multi information source
fuzzy iteration
current balancing algorithm
level-shifted SPWM
medium-voltage applications
multilevel current source inverter
motor drives
phase-shifted carrier SPWM
STATCOM
electricity forecasting
CNN–LSTM
very short-term forecasting (VSTF)
short-term forecasting (STF)
medium-term forecasting (MTF)
long-term forecasting (LTF)
asynchronous motor
linear active disturbance rejection control
error differentiation
vector control
renewable energy
solar power plant
Data Envelopment Analysis (DEA)
Fuzzy Analytical Network Process (FANP)
Fuzzy Theory
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Accés en línia:ONIX_20210501_9783039433346_959
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