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reinforcement learning (võtmesõna)

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1

artikkel kogumikus

Applying reinforcement learning method for real-time energy managementBorhan Dayani, Aida; Fazlollahtabar, Hamed; Ahmadiahangar, Roya; Rosin, Argo2019 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 approachNosrati, Komeil; Tepljakov, Aleksei; Petlenkov, Eduard; Škiparev, Vjatšeslav; Belikov, Juri; Levron, Yoash2023 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 learningNosrati, Komeil; Tepljakov, Aleksei; Petlenkov, Eduard; Levron, Yoash; Škiparev, Vjatšeslav; Belikov, Juri2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) : proceedings2022 / 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 robotAlsaleh, Saleh Ragheb Saleh; Tepljakov, Aleksei; Tamre, Mart; Kuts, Vladimir; Petlenkov, EduardProceedings of ASME 2022 International Mechanical Engineering Congress and Exposition (IMECE2022), 2B: Columbus, Ohio, USA, October 30 - November 3, 20222022 / 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 predictionOunoughi, Chahinez; Touibi, Ghofrane; Ben Yahia, SadokDatabase and Expert Systems Applications : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022 : proceedings, Part I2022 / 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 methodŠkiparev, Vjatšeslav; Nosrati, Komeil; Belikov, Juri; Tepljakov, Aleksei; Petlenkov, Eduard2023 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 cellsAhmed, Tauseef; Le Moullec, Yannick2015 23rd Telecommunications Forum (TELFOR) : Belgrade, Serbia, November, 24-26, 2015 : proceedings of papers = XXIII Телекомуникациони Форум ТЕЛФОР 2015 : зборник радова2015 / 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 operationsVodovozov, Valery; Raud, Zoja; Petlenkov, EduardEnergies2023 / art. 7418 https://doi.org/10.3390/en16217418 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
9

artikkel ajakirjas EST / artikkel ajakirjas ENG

Intelligent frequency control of AC microgrids with communication delay : an online tuning method subject to stabilizing parametersNosrati, Komeil; Škiparev, Vjatšeslav; Tepljakov, Aleksei; Petlenkov, Eduard; Belikov, JuriEnergy and AI2024 / art. 100421 https://doi.org/10.1016/j.egyai.2024.100421 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
10

artikkel ajakirjas EST / artikkel ajakirjas ENG

Joint optimization via deep reinforcement learning in wireless networked controlled systemsAshraf, Kanwal; Le Moullec, Yannick; Pardy, Tamas; Rang, ToomasIEEE Access2022 / p. 67152-67167 https://doi.org/10.1109/ACCESS.2022.3185244 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / 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
11

artikkel kogumikus EST / artikkel kogumikus ENG

Machine learning techniques for wireless-powered ambient backscatter communications : enabling intelligent iot networks in 6g eraJameel, 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
12

artikkel kogumikus

Management of braking energy in electric vehicles using reinforcement learningVodovozov, Valery; Raud, Zoja; Petlenkov, Eduard2023 International Conference on Clean Electrical Power (ICCEP)2023 / p. 559-564 https://doi.org/10.1109/ICCEP57914.2023.10247359

artikkel kogumikus
13

artikkel kogumikus

MIMO reinforcement learning based approach for frequency support in microgrids with high renewable energy penetrationŠkiparev, Vjatšeslav; Belikov, Juri; Petlenkov, Eduard2021 IEEE Power & Energy Society General Meeting (PESGM), 26-29 July 20212021 / 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
14

artikkel ajakirjas EST / artikkel ajakirjas ENG

On coverage of critical nodes in UAV-assisted emergency networksWaheed, Maham; Ahmad, Rizwan; Ahmed, Waqas; Alam, Muhammad Mahtab; Magarini, MaurizioSensors2023 / 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
15

artikkel ajakirjas EST / artikkel ajakirjas ENG

Optimal tuning of fractional order sliding mode controller for PMSM speed using neural network with reinforcement learningZahraoui, Younes; Zaihidee, Fardila M.; Kermadi, Mostefa; Mekhilef, Saad; Alhamrouni, Ibrahim; Seyedmahmoudian, Mehdi; Stojcevski, AlexEnergies2023 / art. 4353 https://doi.org/10.3390/en16114353 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
16

artikkel kogumikus

Optimization of channel allocation in wireless body area networks by means of reinforcement learningAhmed, Tauseef; Ahmed, Faisal; Le Moullec, YannickAPWiMob : IEEE Asia Pacific Conference on Wireless and Mobile 2016 : conference proceedings : 13-15 September 2016, Grand Royal Panghegar Hotel, Bandung, Indonesia2016 / p. 120-123 : ill https://doi.org/10.1109/APWiMob.2016.7811445

artikkel kogumikus
17

artikkel kogumikus

Power-efficient frequency allocation algorithms for self-organized networksAhmed, Tauseef; Le Moullec, Yannick2015 Advances in Wireless and Optical Communications RTUWO : 5-6 November 2015, Riga, Latvia : proceedings2015 / p. 142-145 : ill http://dx.doi.org/10.1109/RTUWO.2015.7365738

artikkel kogumikus
18

artikkel ajakirjas EST / artikkel ajakirjas ENG

A QoS optimization approach in cognitive body area networks for healthcare applicationsAhmed, Tauseef; Le Moullec, YannickSensors2017 / art. 780, p. 1-23 : ill https://doi.org/10.3390/s17040780 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
19

artikkel kogumikus

Reinforcement learning based approach for virtual inertia control in microgrids with renewable energy sourcesŠkiparev, Vjatšeslav; Belikov, Juri; Petlenkov, EduardProceedings of 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 26-28 October, 20202020 / 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
20

artikkel ajakirjas EST / artikkel ajakirjas ENG

Reinforcement learning model-based and model-free paradigms for optimal control problems in power systems: comprehensive review and future directionsGinzburg-Ganz, Elinor; Segev, Itay; Balabanov, Alexander; Segev, Elior; Kaully Naveh, Sivan; Machlev, Ram; Belikov, Juri; Katzir, Liran; Keren, Sarah; Levron, YoashEnergies2024 / art. 5307, 54 p. : ill https://doi.org/10.3390/en17215307 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
21

artikkel ajakirjas EST / artikkel ajakirjas ENG

A reinforcement learning routing protocol for UAV aided public safety networksMinhas, Hassan Ishtiaq; Ahmad, Rizwan; Ahmed, Waqas; Waheed, Maham; Alam, Muhammad Mahtab; Gul, Sufi TabassumSensors2021 / Art. nr. 4121 https://doi.org/10.3390/s21124121 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
22

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-PhilippeBEC 2018 : 2018 16th Biennial Baltic Electronics Conference (BEC) : proceedings of the 16th Biennial Baltic Electronics Conference, October 8-10, 20182019 / 4 p https://doi.org/10.1109/BEC.2018.8600992

artikkel kogumikus
23

artikkel kogumikus

Simulation study of processes in electric vehicles under braking control based on reinforcement learningVodovozov, Valery; Raud, Zoja; Petlenkov, Eduard2023 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
24

artikkel kogumikus

Strengthening active learning with a reinforcement approach in engineering educationVodovozov, Valery; Raud, Zoja; Petlenkov, Eduard2024 IEEE 65th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)2024 / 5 p

artikkel kogumikus
25

artikkel ajakirjas EST / artikkel ajakirjas ENG

Using reinforcement learning to optimize the acceptance threshold of a credit scoring modelHerasymovych, Mykola; Märka, Karl; Lukason, OliverApplied Soft Computing Journal2019 / Art. 105697 https://doi.org/10.1016/j.asoc.2019.105697 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG

Kirjeid leitud 25, kuvan 1 - 25

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. digital remote learning
66. Dimensions of Learning Organisation Questionnaire (DLOQ)
67. distance learning
68. distant learning
69. double Q-learning
70. effective teaching and learning
71. e-learning
72. e‐learning
73. e-Learning course
74. e-Learning database
75. e-learning environment
76. electronic learning
77. embedded deep learning
78. Emergency remote learning
79. ensemble learning
80. enterprising and entrepreneurial learning
81. entrepreneurial learning
82. entrepreneurial teaching and learning
83. ESG-learning
84. experiential learning
85. Federated learning
86. federated learning (FL)
87. flexible learning
88. game based learning
89. game-based learning
90. graph machine learning
91. guided in-service learning
92. hands-on-learning
93. history learning
94. horizontal federated learning
95. hybrid learning
96. incremental learning
97. inductive learning
98. inductive learning algorithm
99. interactive learning objects
100. interdisciplinary learning
101. interpretable machine learning
102. investor learning
103. iterative learning
104. Kolb’s experiential learning cycle
105. language learning
106. Learner-centered learning environment
107. learning
108. learning (artificial intelligence)
109. learning activities
110. learning adaptation in autonomous vehicles
111. learning algorithm
112. learning analysis
113. learning analytics
114. learning and experimentation
115. learning and health outcomes
116. learning and memory
117. learning business school
118. learning by teaching
119. learning concept
120. learning design
121. learning difficulties
122. Learning environment
123. learning experience
124. learning infrastructures
125. Learning Lab
126. learning management
127. learning management system
128. learning management systems
129. learning methodology
130. learning metrics
131. learning models
132. learning motivation
133. learning objectives
134. learning objects
135. learning organization
136. learning orientation
137. learning outcomes
138. learning process
139. learning processes
140. learning rate
141. learning rate dependence on ownership form
142. learning rate of organization
143. learning region
144. learning situation
145. learning software agents
146. learning styles
147. learning systems
148. learning technologies
149. learning theories
150. learning through the questionnaires
151. learning university
152. learning-to-rank
153. lifelong learning
154. machine learning
155. machine learning (ML)
156. machine learning algorithms
157. machine learning approach
158. Machine Learning Explainable model
159. machine learning for environmental applications
160. machine learning models
161. machine learning systems
162. machine-learning
163. machine-learning predictive model
164. mathematics students learning habits
165. Meaningful learning
166. measuring learning
167. mobile learning
168. model learning
169. mutual learning
170. new learning models
171. node embedding learning
172. NREN e-learning
173. on-device transfer learning
174. online learning
175. ontologies for learning systems
176. ontology learning
177. organisational learning
178. organizational learning
179. organizational learning measurement instruments
180. organizational learning rate dependence on management
181. organizational learning rate measurement
182. outcome oriented learning
183. Parkinson’s disease machine learning
184. peer‐to‐peer learning group
185. personalised learning
186. policy learning
187. problem-based learning
188. Problem-based learning (PBL)
189. project learning
190. project-based learning
191. Q-learning
192. Q-learning algorithm
193. query learning
194. regional learning
195. relative learning performance
196. Remote learning
197. research-oriented learning
198. reusable learning objects
199. robust machine learning
200. scholarship of teaching and learning
201. self learning software
202. self learning system
203. self-learning
204. self-regulated learning
205. semi-supervised learning
206. small data machine learning
207. smart learning
208. smart learning environment
209. social learning
210. stochastic learning theory
211. supervised learning
212. supervised learning data
213. supervised machine learning
214. zero-shot learning
215. task based learning
216. team learning
217. Technological learning
218. technology-enhanced learning
219. the dimensions of the learning organisation
220. the dimensions of the learning organization questionnaire (DLOQ)
221. tools for interactive learning and teaching
222. trans-disciplinary social-learning
223. transfer learning
224. ubiquitous learning
225. unsupervised learning
226. unsupervised machine learning
227. urban learning center
228. value of learning
229. web and computerbased learning
230. Web and computer-based learning
231. virtual collaborative learning environment (VCLE)
232. virtual learning environment
233. virtual learning factory
234. work-based learning
235. workplace learning

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