Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Crockett, Keeley"'
Publikováno v:
Multimed Tools Appl 78, 2019
There is a general consensus of the good sensing and novelty characteristics of Twitter as an information media for the complex financial market. This paper investigates the permeability of Twittersphere, the total universe of Twitter users and their
Externí odkaz:
http://arxiv.org/abs/2312.11530
Publikováno v:
In Expert Systems With Applications 15 October 2023 228
Publikováno v:
In Expert Systems With Applications 1 May 2021 169
Publikováno v:
In Expert Systems With Applications 15 April 2021 168
Publikováno v:
In Expert Systems With Applications 1 August 2019 127:353-369
Autor:
Crockett, Keeley, Zoltán, Székely, O'shea, James, Szklarski, Lukasz, Malamou, Anna, Boultadakis, Georgios
Publikováno v:
In Biometric Technology Today July-August 2017 2017(7):5-8
Publikováno v:
In International Journal of Human - Computer Studies January 2017 97:98-115
Autor:
Reijnen, Robbert, Zhang, Yingqian, Bukhsh, Zaharah, Guzek, Mateusz, Ishibuchi, Hisao, Kwoh, Chee-Keong, Tan, Ah-Hwee, Srinivasan, Dipti, Miao, Chunyan, Trivedi, Anupam, Crockett, Keeley
Publikováno v:
The 2022 IEEE Symposium Series on Computational Intelligence (IEEE SSCI), 804-811
STARTPAGE=804;ENDPAGE=811;TITLE=The 2022 IEEE Symposium Series on Computational Intelligence (IEEE SSCI)
STARTPAGE=804;ENDPAGE=811;TITLE=The 2022 IEEE Symposium Series on Computational Intelligence (IEEE SSCI)
Evolutionary algorithms (EA) are efficient population-based stochastic algorithms for solving optimization problems. The performance of EAs largely depends on the configuration of values of parameters that control their search. Previous works studied
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6476937bca3719777c737243f0e41803
https://doi.org/10.1109/ssci51031.2022.10022227
https://doi.org/10.1109/ssci51031.2022.10022227
Autor:
Chandra, Abhishek, Curti, Mitrofan, Tiels, Koen, Lomonova, Elena A., Tartakovsky, Daniel M., Ishibuchi, Hisao, Kwoh, Chee-Keong, Tan, Ah-Hwee, Srinivasan, Dipti, Miao, Chunyan, Trivedi, Anupam, Crockett, Keeley
Publikováno v:
2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1451-1459
STARTPAGE=1451;ENDPAGE=1459;TITLE=2022 IEEE Symposium Series on Computational Intelligence (SSCI)
STARTPAGE=1451;ENDPAGE=1459;TITLE=2022 IEEE Symposium Series on Computational Intelligence (SSCI)
This paper investigates the application of Physics-Informed Neural Networks (PINNs) in modelling constitutive laws for transverse electromagnetic polarized waves in all three space dimensions governed by Maxwell Faraday equation and Ampere's circuita
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9806b643998bd20790f9a63c9c15cb10
https://doi.org/10.1109/ssci51031.2022.10022292
https://doi.org/10.1109/ssci51031.2022.10022292