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reinforcement learning (võtmesõna)
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1
artikkel kogumikus
Applying reinforcement learning method for real-time energy management
Borhan Dayani, Aida
;
Fazlollahtabar, Hamed
;
Ahmadiahangar, Roya
;
Rosin, Argo
2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
2019
/
5 p. : ill
https://doi.org/10.1109/EEEIC.2019.8783766
artikkel kogumikus
2
artikkel kogumikus
Constrained intelligent frequency control in an AC Microgrid : an Online reinforcement learning based PID tuning approach
Nosrati, Komeil
;
Tepljakov, Aleksei
;
Petlenkov, Eduard
;
Škiparev, Vjatšeslav
;
Belikov, Juri
;
Levron, Yoash
2023 IEEE Power & Energy Society General Meeting (PESGM)
2023
/
5 p. : ill
https://doi.org/10.1109/PESGM52003.2023.10252482
artikkel kogumikus
Seotud publikatsioonid
1
Virtual inertia control of microgrids using deep reinforcement learning methods = Mikrovõrkude virtuaalse inertsi juhtimine sügava stiimulõppe meetoditega
3
artikkel kogumikus
Coordinated PI-based frequency deviation control of isolated hybrid microgrid : an online multi-agent tuning approach via reinforcement learning
Nosrati, Komeil
;
Tepljakov, Aleksei
;
Petlenkov, Eduard
;
Levron, Yoash
;
Škiparev, Vjatšeslav
;
Belikov, Juri
2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) : proceedings
2022
/
p. 1-5 : ill
https://doi.org/10.1109/ISGT-Europe54678.2022.9960311
artikkel kogumikus
Seotud publikatsioonid
1
Virtual inertia control of microgrids using deep reinforcement learning methods = Mikrovõrkude virtuaalse inertsi juhtimine sügava stiimulõppe meetoditega
4
artikkel kogumikus
Digital twin simulations based reinforcement learning for navigation and control of a wheel-on-leg mobile robot
Alsaleh, Saleh Ragheb Saleh
;
Tepljakov, Aleksei
;
Tamre, Mart
;
Kuts, Vladimir
;
Petlenkov, Eduard
Proceedings of ASME 2022 International Mechanical Engineering Congress and Exposition (IMECE2022), 2B: Columbus, Ohio, USA, October 30 - November 3, 2022
2022
/
art. IMECE2022-95411, V02BT02A025, 8 p
https://doi.org/10.1115/IMECE2022-95411
artikkel kogumikus
Seotud publikatsioonid
1
Digital twin based computational methods for XR applications = Digitaalkaksikute põhised arvutuslikud meetodid XR rakenduste jaoks
5
artikkel kogumikus EST
/
artikkel kogumikus ENG
EcoLight : Eco-friendly traffic signal control driven by urban noise prediction
Ounoughi, Chahinez
;
Touibi, Ghofrane
;
Ben Yahia, Sadok
Database and Expert Systems Applications : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022 : proceedings, Part I
2022
/
p. 205–219
https://doi.org/10.1007/978-3-031-12423-5_16
Conference Proceedings at Scopus
Article at Scopus
Conference Proceedings at WOS
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Urban traffic : data fusion and vehicle flow prediction in smart cities = Linnaliiklus : andmete ühtesulamine ja sõidukite voo prognoosimine nutikates linnades
6
artikkel kogumikus
An enhanced NN-based load frequency control design of MGs : a fractional order modeling method
Škiparev, Vjatšeslav
;
Nosrati, Komeil
;
Belikov, Juri
;
Tepljakov, Aleksei
;
Petlenkov, Eduard
2023 IEEE 17th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)
2023
/
6 p
https://doi.org/10.1109/CPE-POWERENG58103.2023.10227392
artikkel kogumikus
Seotud publikatsioonid
1
Virtual inertia control of microgrids using deep reinforcement learning methods = Mikrovõrkude virtuaalse inertsi juhtimine sügava stiimulõppe meetoditega
7
artikkel kogumikus
Frequency and power allocation schemes for heterogeneous networks including femto cells
Ahmed, Tauseef
;
Le Moullec, Yannick
2015 23rd Telecommunications Forum (TELFOR) : Belgrade, Serbia, November, 24-26, 2015 : proceedings of papers = XXIII Телекомуникациони Форум ТЕЛФОР 2015 : зборник радова
2015
/
p. 277-280 : ill
http://dx.doi.org/10.1109/TELFOR.2015.7377464
artikkel kogumikus
8
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Intelligent control of robots with minimal power consumption in pick-and-place operations
Vodovozov, Valery
;
Raud, Zoja
;
Petlenkov, Eduard
Energies
2023
/
art. 7418
https://doi.org/10.3390/en16217418
Journal metrics at Scopus
Article at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
9
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Joint optimization via deep reinforcement learning in wireless networked controlled systems
Ashraf, Kanwal
;
Le Moullec, Yannick
;
Pardy, Tamas
;
Rang, Toomas
IEEE Access
2022
/
p. 67152-67167
https://doi.org/10.1109/ACCESS.2022.3185244
Journal metrics at Scopus
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Article at WOS
artikkel ajakirjas EST
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artikkel ajakirjas ENG
Seotud publikatsioonid
1
Co-design of wireless networked control systems : model-based architecture and joint optimization = Juhtmevabade võrgustatud juhtimissüsteemide koosdisain : mudelipõhine arhitektuur ja ühisoptimeerimine
10
artikkel kogumikus EST
/
artikkel kogumikus ENG
Machine learning techniques for wireless-powered ambient backscatter communications : enabling intelligent iot networks in 6g era
Jameel, Furqan
;
Sharma, Navuday
;
Khan, Muhammad Awais
;
Khan, Imran
;
Alam, Muhammad Mahtab
;
Alam, Muhammad Mahtab
;
Mavromoustakis, Constandinos X.
Internet of Things
/
2020
https://doi.org/10.1007/978-3-030-44907-0_8
Article collection metrics at Scopus
Article at Scopus
artikkel kogumikus EST
/
artikkel kogumikus ENG
11
artikkel kogumikus
Management of braking energy in electric vehicles using reinforcement learning
Vodovozov, Valery
;
Raud, Zoja
;
Petlenkov, Eduard
2023 International Conference on Clean Electrical Power (ICCEP)
2023
/
p. 559-564
https://doi.org/10.1109/ICCEP57914.2023.10247359
artikkel kogumikus
12
artikkel kogumikus
MIMO reinforcement learning based approach for frequency support in microgrids with high renewable energy penetration
Škiparev, Vjatšeslav
;
Belikov, Juri
;
Petlenkov, Eduard
2021 IEEE Power & Energy Society General Meeting (PESGM), 26-29 July 2021
2021
/
5 p. : ill
https://doi.org/10.1109/PESGM46819.2021.9637942
artikkel kogumikus
Seotud publikatsioonid
1
Virtual inertia control of microgrids using deep reinforcement learning methods = Mikrovõrkude virtuaalse inertsi juhtimine sügava stiimulõppe meetoditega
13
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
On coverage of critical nodes in UAV-assisted emergency networks
Waheed, Maham
;
Ahmad, Rizwan
;
Ahmed, Waqas
;
Alam, Muhammad Mahtab
;
Magarini, Maurizio
Sensors
2023
/
art. 1586
https://doi.org/10.3390/s23031586
Journal metrics at Scopus
Article at Scopus
Journal metrics at WOS
Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
14
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Optimal tuning of fractional order sliding mode controller for PMSM speed using neural network with reinforcement learning
Zahraoui, Younes
;
Zaihidee, Fardila M.
;
Kermadi, Mostefa
;
Mekhilef, Saad
;
Alhamrouni, Ibrahim
;
Seyedmahmoudian, Mehdi
;
Stojcevski, Alex
Energies
2023
/
art. 4353
https://doi.org/10.3390/en16114353
Journal metrics at Scopus
Article at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
15
artikkel kogumikus
Optimization of channel allocation in wireless body area networks by means of reinforcement learning
Ahmed, Tauseef
;
Ahmed, Faisal
;
Le Moullec, Yannick
APWiMob : IEEE Asia Pacific Conference on Wireless and Mobile 2016 : conference proceedings : 13-15 September 2016, Grand Royal Panghegar Hotel, Bandung, Indonesia
2016
/
p. 120-123 : ill
https://doi.org/10.1109/APWiMob.2016.7811445
artikkel kogumikus
16
artikkel kogumikus
Power-efficient frequency allocation algorithms for self-organized networks
Ahmed, Tauseef
;
Le Moullec, Yannick
2015 Advances in Wireless and Optical Communications RTUWO : 5-6 November 2015, Riga, Latvia : proceedings
2015
/
p. 142-145 : ill
http://dx.doi.org/10.1109/RTUWO.2015.7365738
artikkel kogumikus
17
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
A QoS optimization approach in cognitive body area networks for healthcare applications
Ahmed, Tauseef
;
Le Moullec, Yannick
Sensors
2017
/
art. 780, p. 1-23 : ill
https://doi.org/10.3390/s17040780
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Article at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
18
artikkel kogumikus
Reinforcement learning based approach for virtual inertia control in microgrids with renewable energy sources
Škiparev, Vjatšeslav
;
Belikov, Juri
;
Petlenkov, Eduard
Proceedings of 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 26-28 October, 2020
2020
/
p. 1020-1024
https://doi.org/10.1109/ISGT-Europe47291.2020.9248777
artikkel kogumikus
Seotud publikatsioonid
1
Virtual inertia control of microgrids using deep reinforcement learning methods = Mikrovõrkude virtuaalse inertsi juhtimine sügava stiimulõppe meetoditega
19
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
A reinforcement learning routing protocol for UAV aided public safety networks
Minhas, Hassan Ishtiaq
;
Ahmad, Rizwan
;
Ahmed, Waqas
;
Waheed, Maham
;
Alam, Muhammad Mahtab
;
Gul, Sufi Tabassum
Sensors
2021
/
Art. nr. 4121
https://doi.org/10.3390/s21124121
Journal metrics at Scopus
Article at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
20
artikkel kogumikus
Reward function evaluation in a reinforcement learning approach for energy management [Online resource]
Rioual, Yohann
;
Le Moullec, Yannick
;
Laurent, Johann
;
Khan, Muhidul Islam
;
Diguet, Jean-Philippe
BEC 2018 : 2018 16th Biennial Baltic Electronics Conference (BEC) : proceedings of the 16th Biennial Baltic Electronics Conference, October 8-10, 2018
2019
/
4 p
https://doi.org/10.1109/BEC.2018.8600992
artikkel kogumikus
21
artikkel kogumikus
Simulation study of processes in electric vehicles under braking control based on reinforcement learning
Vodovozov, Valery
;
Raud, Zoja
;
Petlenkov, Eduard
2023 IEEE 17th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)
2023
/
5 p
https://doi.org/10.1109/CPE-POWERENG58103.2023.10227478
artikkel kogumikus
22
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Using reinforcement learning to optimize the acceptance threshold of a credit scoring model
Herasymovych, Mykola
;
Märka, Karl
;
Lukason, Oliver
Applied Soft Computing Journal
2019
/
Art. 105697
https://doi.org/10.1016/j.asoc.2019.105697
Journal metrics at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Kirjeid leitud 22, kuvan
1 - 22
võtmesõna
228
1.
cooperative reinforcement learning
2.
deep reinforcement learning
3.
distributed independent reinforcement learning
4.
inverse reinforcement learning
5.
Multi-agent reinforcement learning
6.
reinforcement learning
7.
Reinforcement Learning (RL)
8.
true online reinforcement learning
9.
carbide reinforcement
10.
cermet reinforcement
11.
concrete reinforcement
12.
fiber reinforcement
13.
glass-fiber reinforcement
14.
hardmetal reinforcement
15.
Helical reinforcement
16.
in situ reinforcement
17.
particulate reinforcement mass fraction
18.
reinforcement
19.
reinforcement mass fraction
20.
twomodal reinforcement
21.
WC reinforcement
22.
active blended learning
23.
active learning
24.
active learning methods
25.
adversarial machine learning
26.
adversarial machine-learning
27.
algorithm controlling the learning process
28.
appetitive associative learning
29.
approach to learning
30.
Attitude to learning
31.
authoritarian learning
32.
automata learning
33.
automatic machine learning (autoML)
34.
BIM-enabled learning
35.
BIM-enabled learning environment
36.
blended learning
37.
business school as learning organization
38.
business school learning organization questionnaire (BSLOQ)
39.
business school learning rate dependence on GPD
40.
business school learning rate measurement instrument
41.
client learning
42.
Collaborative e-learning
43.
collaborative learning
44.
competence based learning
45.
competence learning
46.
competence-based learning
47.
competency based learning
48.
Component organised learning (COL)
49.
computer assisted language learning
50.
computer based learning
51.
computer-assisted language learning (CALL)
52.
coping with online teaching and learning
53.
customer learning
54.
deep learning
55.
deep learning (DL)
56.
deep learning classifier
57.
deep learning model
58.
deep learning model quantization
59.
deep learning network
60.
Deep reinforcing learning SDN
61.
Deep-learning
62.
deep-learning (DL)
63.
dictionary learning
64.
digital learning module
65.
Dimensions of Learning Organisation Questionnaire (DLOQ)
66.
distance learning
67.
distant learning
68.
double Q-learning
69.
effective teaching and learning
70.
e-learning
71.
e‐learning
72.
e-Learning course
73.
e-Learning database
74.
e-learning environment
75.
electronic learning
76.
embedded deep learning
77.
Emergency remote learning
78.
ensemble learning
79.
enterprising and entrepreneurial learning
80.
entrepreneurial learning
81.
entrepreneurial teaching and learning
82.
experiential learning
83.
Federated learning
84.
federated learning (FL)
85.
flexible learning
86.
game based learning
87.
game-based learning
88.
graph machine learning
89.
guided in-service learning
90.
hands-on-learning
91.
history learning
92.
hybrid learning
93.
incremental learning
94.
inductive learning
95.
inductive learning algorithm
96.
interactive learning objects
97.
interdisciplinary learning
98.
interpretable machine learning
99.
investor learning
100.
iterative learning
101.
Learner-centered learning environment
102.
learning
103.
learning (artificial intelligence)
104.
learning activities
105.
learning adaptation in autonomous vehicles
106.
learning algorithm
107.
learning analysis
108.
learning analytics
109.
learning and experimentation
110.
learning and health outcomes
111.
learning and memory
112.
learning business school
113.
learning by teaching
114.
learning concept
115.
learning design
116.
learning difficulties
117.
Learning environment
118.
learning experience
119.
learning infrastructures
120.
Learning Lab
121.
learning management
122.
learning management system
123.
learning management systems
124.
learning methodology
125.
learning metrics
126.
learning models
127.
learning motivation
128.
learning objectives
129.
learning objects
130.
learning organization
131.
learning orientation
132.
learning outcomes
133.
learning process
134.
learning processes
135.
learning rate
136.
learning rate dependence on ownership form
137.
learning rate of organization
138.
learning region
139.
learning situation
140.
learning software agents
141.
learning styles
142.
learning systems
143.
learning technologies
144.
learning theories
145.
learning through the questionnaires
146.
learning university
147.
learning-to-rank
148.
lifelong learning
149.
machine learning
150.
machine learning (ML)
151.
machine learning algorithms
152.
machine learning approach
153.
Machine Learning Explainable model
154.
machine learning for environmental applications
155.
machine learning models
156.
machine learning systems
157.
machine-learning
158.
machine-learning predictive model
159.
mathematics students learning habits
160.
Meaningful learning
161.
measuring learning
162.
mobile learning
163.
model learning
164.
mutual learning
165.
new learning models
166.
node embedding learning
167.
NREN e-learning
168.
on-device transfer learning
169.
online learning
170.
ontologies for learning systems
171.
ontology learning
172.
organisational learning
173.
organizational learning
174.
organizational learning measurement instruments
175.
organizational learning rate dependence on management
176.
organizational learning rate measurement
177.
outcome oriented learning
178.
Parkinson’s disease machine learning
179.
peer‐to‐peer learning group
180.
personalised learning
181.
policy learning
182.
problem-based learning
183.
Problem-based learning (PBL)
184.
project learning
185.
project-based learning
186.
Q-learning
187.
Q-learning algorithm
188.
query learning
189.
regional learning
190.
relative learning performance
191.
Remote learning
192.
research-oriented learning
193.
reusable learning objects
194.
robust machine learning
195.
scholarship of teaching and learning
196.
self learning software
197.
self learning system
198.
self-learning
199.
self-regulated learning
200.
semi-supervised learning
201.
small data machine learning
202.
smart learning
203.
smart learning environment
204.
social learning
205.
stochastic learning theory
206.
supervised learning
207.
supervised learning data
208.
supervised machine learning
209.
task based learning
210.
team learning
211.
Technological learning
212.
technology-enhanced learning
213.
the dimensions of the learning organisation
214.
the dimensions of the learning organization questionnaire (DLOQ)
215.
tools for interactive learning and teaching
216.
trans-disciplinary social-learning
217.
transfer learning
218.
ubiquitous learning
219.
unsupervised learning
220.
unsupervised machine learning
221.
urban learning center
222.
value of learning
223.
web and computerbased learning
224.
Web and computer-based learning
225.
virtual learning environment
226.
virtual learning factory
227.
work-based learning
228.
workplace learning
autor
1
1.
ELIXIR Machine Learning Focus Group
märksõna
1
1.
UNDP Urban Learning Center
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