Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Jaroslav Loebl"'
Autor:
Viera Rozinajová, Jaroslav Loebl
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030166595
ISDA (2)
ISDA (2)
Cartesian Genetic Programming (CGP) is a type of Genetic Programming, which uses a sequence of integers to represent an executable graph structure. The most common way of optimizing the CGP is to use a simple evolutionary strategy with mutations, whi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b76bee59011e430cfed49b312d4ae4d2
https://doi.org/10.1007/978-3-030-16660-1_96
https://doi.org/10.1007/978-3-030-16660-1_96
Autor:
Dávid Kubík, Jaroslav Loebl
Publikováno v:
Data Analytics for Renewable Energy Integration. Technologies, Systems and Society ISBN: 9783030043025
DARE@PKDD/ECML
DARE@PKDD/ECML
We propose a method for finding the most appropriate photovoltaic (hereafter PV) module and the return on investment for specific household needs, leveraging mathematical optimization. Based on electricity consumption and location of the household, t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1408e2c7b20a08c8e59597f181dcfcf
https://doi.org/10.1007/978-3-030-04303-2_1
https://doi.org/10.1007/978-3-030-04303-2_1
Autor:
Petra Vrablecová, Róbert Magyar, Anna Bou Ezzeddine, Viera Rozinajová, Jaroslav Loebl, Marek Loderer
This chapter presents one way of incorporating computational intelligence into smart grid environment. We introduce an energy ecosystem, where contemporary technologies are used and by involving advanced methods of data analysis and optimization, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aceaf3512fa2bd672dcc491dcb0027d2
https://doi.org/10.1016/b978-0-12-813314-9.00002-5
https://doi.org/10.1016/b978-0-12-813314-9.00002-5
Autor:
Mohamed Abdel-Basset, Laila Abdel-Fatah, Armin Haj Aboutalebi, A. Sherly Alphonse, Grace Mojisola Asogbon, Senthil Murugan Balakrishnan, Soumya Banerjee, S.S. Blessy Trencia Lincy, Arun Das, Prasun Das, Dejey Dharma, Lide Duan, Anna Bou Ezzeddine, Kaneez Fatima, Sakshi Kaushal, Aydin Kaya, Ali Seydi Keceli, Harish Kumar, Guanglin Li, Marek Lóderer, Mir Muhammad Lodro, Jaroslav Loebl, Róbert Magyar, Yacine Ouzrout, Shalini Parasuraman, Sandeep Pirbhulal, Paul Rad, Anitha Ramchandran, Viera Rozinajová, Sounak Sadhukhan, Oluwarotimi Williams Samuel, Arun Kumar Sangaiah, Aicha Sekhari, Megha Sharma, Chinu Singla, Ali Hassan Sodhro, Gul Hassan Sodhro, N. Suresh Kumar, Bedir Tekinerdogan, Huseyin Temucin, Alex D. Torres, Amandeep Verma, Petra Vrablecová, Hamdi Yalin Yalic, Hao Yan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::999fa34d757381567e14d9c2eeeb3afd
https://doi.org/10.1016/b978-0-12-813314-9.00021-9
https://doi.org/10.1016/b978-0-12-813314-9.00021-9
Publikováno v:
Data Analytics for Renewable Energy Integration: Informing the Generation and Distribution of Renewable Energy ISBN: 9783319716428
DARE@PKDD/ECML
DARE@PKDD/ECML
This paper proposes a recommendation system for load shifting of energy consumption for residential consumers. The main goal is to provide to customer a set of energy consumption strategies, which would span from maximum cost saving strategy, to maxi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b8bc6475e9123444195d11c4babbd16
https://doi.org/10.1007/978-3-319-71643-5_3
https://doi.org/10.1007/978-3-319-71643-5_3