Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Anna Bou Ezzeddine"'
Publikováno v:
Web Intelligence and Intelligent Agents
One of the great challenges attracting researchers of various disciplines has been the question: how to solve it? Problem solving has been an important topic of research e.g. in artificial intelligence and many remarkable results have been achieved t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d04aaafdb2501262fe13e35e4cbf4ae9
http://www.intechopen.com/articles/show/title/exploring-the-bee-hive-metaphor-as-a-model-for-problem-solving-search-optimisation-and-more
http://www.intechopen.com/articles/show/title/exploring-the-bee-hive-metaphor-as-a-model-for-problem-solving-search-optimisation-and-more
Publikováno v:
Towards Digital Intelligence Society ISBN: 9783030638719
The huge amount of data generated on a daily basis in many areas of our lives predetermines data science to be one of the most significant current IT research areas. Thanks to the recent technological trends, such as internet of things (IoT), the dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::977a36560a5171486a8398404ae64731
https://doi.org/10.1007/978-3-030-63872-6_5
https://doi.org/10.1007/978-3-030-63872-6_5
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030539559
ICSI
ICSI
Prediction of photovoltaic (PV) energy is an important task. It allows grid operators to plan production of energy in order to secure stability of electrical grid. In this work we focus on improving prediction of PV energy using nature-inspired algor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90eb9b75275cfc18d8bb6b6bd9f77a97
https://doi.org/10.1007/978-3-030-53956-6_3
https://doi.org/10.1007/978-3-030-53956-6_3
Publikováno v:
Computers & Electrical Engineering. 65:102-117
Smart grid, an integral part of a smart city, provides new opportunities for efficient energy management, possibly leading to big cost savings and a great contribution to the environment. Grid innovations and liberalization of the electricity market
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff1e3b02036080791df2e5af1198afea
https://doi.org/10.1016/j.compeleceng.2017.07.006
https://doi.org/10.1016/j.compeleceng.2017.07.006
Autor:
Peter Laurinec, Gabriela Grmanová, Mária Lucká, Marek Loderer, Petra Vrablecová, Viera Rozinajová, Anna Bou Ezzeddine, Peter Lacko
Publikováno v:
International Journal of Hybrid Intelligent Systems. 13:99-112
The complexity of certain problems causes that classical methods for finding exact solutions have some limitations. In this paper we propose an incremental heterogeneous ensemble model for time series prediction where biologically inspired algorithms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ac46f7ee56eea7b988b5dad0bfa64fc
https://doi.org/10.3233/his-160228
https://doi.org/10.3233/his-160228
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 Mining and Big Data ISBN: 9783319618449
DMBD
DMBD
Accurate power demand forecasts can help power distributors to lower differences between contracted and demanded electricity and minimize the imbalance in grid and related costs. Our forecasting method is designed to process continuous stream of data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96e07e2c48d11cfca157d6b700eb36c5
https://doi.org/10.1007/978-3-319-61845-6_9
https://doi.org/10.1007/978-3-319-61845-6_9
Autor:
Peter Laurinec, Petra Vrablecová, Viera Rozinajová, Mária Lucká, Marek Loderer, Anna Bou Ezzeddine
Publikováno v:
ICDM Workshops
The paper presents an improvement of incremental adaptive power load forecasting methods by performing cluster analysis prior to forecasts. For clustering the centroid based method K-means, with K-means++ centroids initialization, was used. Ten vario
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f67941d21c06079ddb71fc46417da7f
https://doi.org/10.1109/icdmw.2016.0063
https://doi.org/10.1109/icdmw.2016.0063
Publikováno v:
ICDM Workshops
This paper presents an approach to predictive modeling of sequentially arriving data, also known as a stream. Because of their unique properties, this kind of data requires different mining techniques. The ultimate limitations are the memory and the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e40bacff5bccfd9d122870db521a8346
https://doi.org/10.1109/icdmw.2016.0065
https://doi.org/10.1109/icdmw.2016.0065