statistiche ricercatore

Continente	#
NA - Nord America	1.588
AS - Asia	848
EU - Europa	659
SA - Sud America	100
Continente sconosciuto - Info sul continente non disponibili	47
AF - Africa	26
OC - Oceania	4
Totale	3.272

Nazione	#
US - Stati Uniti d'America	1.567
SG - Singapore	295
IT - Italia	290
VN - Vietnam	183
CN - Cina	113
RU - Federazione Russa	92
BR - Brasile	81
FR - Francia	59
HK - Hong Kong	58
BD - Bangladesh	54
DE - Germania	54
KR - Corea	42
IN - India	26
FI - Finlandia	25
BE - Belgio	23
GB - Regno Unito	20
NL - Olanda	19
IE - Irlanda	15
CH - Svizzera	12
CA - Canada	11
ID - Indonesia	10
TR - Turchia	9
AR - Argentina	8
CI - Costa d'Avorio	8
AT - Austria	7
ES - Italia	7
JP - Giappone	7
IQ - Iraq	6
PH - Filippine	6
PK - Pakistan	6
BG - Bulgaria	5
EC - Ecuador	5
JO - Giordania	5
MY - Malesia	5
NG - Nigeria	5
SE - Svezia	5
TW - Taiwan	5
DK - Danimarca	4
LV - Lettonia	4
MA - Marocco	4
MX - Messico	4
AU - Australia	3
SA - Arabia Saudita	3
TH - Thailandia	3
UA - Ucraina	3
ZA - Sudafrica	3
AM - Armenia	2
BF - Burkina Faso	2
CR - Costa Rica	2
CZ - Repubblica Ceca	2
LT - Lituania	2
MU - Mauritius	2
NO - Norvegia	2
PT - Portogallo	2
RO - Romania	2
SV - El Salvador	2
UZ - Uzbekistan	2
VE - Venezuela	2
AZ - Azerbaigian	1
BH - Bahrain	1
CL - Cile	1
CO - Colombia	1
DZ - Algeria	1
GE - Georgia	1
GR - Grecia	1
HN - Honduras	1
HR - Croazia	1
HU - Ungheria	1
IL - Israele	1
KG - Kirghizistan	1
LA - Repubblica Popolare Democratica del Laos	1
LB - Libano	1
LK - Sri Lanka	1
MT - Malta	1
NZ - Nuova Zelanda	1
PE - Perù	1
PR - Porto Rico	1
PY - Paraguay	1
SK - Slovacchia (Repubblica Slovacca)	1
TN - Tunisia	1
Totale	3.225

Nome	#
Practical deployment of reinforcement learning for building controls using an imitation learning approach	1.077
A scalable approach for real-world implementation of deep reinforcement learning controllers in buildings based on online transfer learning: The HiLo case study	304
Transfer learning to enhance the scalability of artificial intelligence-based control strategies in buildings	259
Real building implementation of a deep reinforcement learning controller to enhance energy efficiency and indoor temperature control	247
Online implementation of a soft actor-critic agent to enhance indoor temperature control and energy efficiency in buildings	239
Energy Management of a Residential Heating System Through Deep Reinforcement Learning	230
Exploring the potentialities of deep reinforcement learning for incentive-based demand response in a cluster of small commercial buildings	226
Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings	202
Effective pre-training of a deep reinforcement learning agent by means of long short-term memory models for thermal energy management in buildings	195
An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems	178
Comparison of two deep reinforcement learning algorithms towards an optimal policy for smart building thermal control	115
Totale	3.272

	Totale	Lug	Ago	Sett	Ott	Nov	Dic	Gen	Feb	Mar	Apr	Mag	Giu
2021/2022	81	0	0	0	3	6	2	13	4	12	18	12	11
2022/2023	95	7	18	3	4	9	14	5	3	8	3	5	16
2023/2024	132	8	6	5	14	8	24	6	11	14	5	24	7
2024/2025	508	4	28	8	41	35	33	78	45	69	56	61	50
2025/2026	2.092	111	64	894	76	62	78	162	103	224	132	73	113
2026/2027	266	42	43	81	100	0	0	0	0	0	0	0	0
Totale													3.272

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