Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Xian-Bing Meng"'
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 4, Pp 4615-4627 (2023)
Abstract Penalty function method is popular for constrained evolutionary optimization. However, it is non-trivial to set a proper penalty factor for a constrained optimization problem. This paper takes advantage of co-evolution to adjust the penalty
Externí odkaz:
https://doaj.org/article/4837ed8cad5a4159a7e8cf7a5bb03e86
Publikováno v:
IEEE Transactions on Industrial Electronics. 70:9432-9440
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7e975d93ee8e38af6148950286b90a6
https://doi.org/10.1109/tie.2022.3212419
https://doi.org/10.1109/tie.2022.3212419
Publikováno v:
IEEE Transactions on Cybernetics. 52:6518-6530
As an effective method for clustering applications, the clustering ensemble algorithm integrates different clustering solutions into a final one, thus improving the clustering efficiency. The key to designing the clustering ensemble algorithm is to i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40a8dbbc231a4356712a069161a93561
https://doi.org/10.1109/tcyb.2020.3034157
https://doi.org/10.1109/tcyb.2020.3034157
Publikováno v:
Applied Soft Computing. 131:109786
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea67fc40aee9993b4af6ad91889f4f4e
https://doi.org/10.1016/j.asoc.2022.109786
https://doi.org/10.1016/j.asoc.2022.109786
Publikováno v:
Applied Soft Computing. 131:109797
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::670aa1c2139682c44ae562dc025e911c
https://doi.org/10.1016/j.asoc.2022.109797
https://doi.org/10.1016/j.asoc.2022.109797
Publikováno v:
IEEE Transactions on Industrial Informatics. 15:2838-2848
Temperature monitoring is indispensable to the optimal and safe operation of a lithium-ion battery. In this paper, a spatio–temporal learning model designed by evolutionary algorithm is proposed to predict the thermal distribution. To formulate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea1760d576bb05d443ab68247a4187dd
https://doi.org/10.1109/tii.2018.2866468
https://doi.org/10.1109/tii.2018.2866468
Publikováno v:
Journal of Experimental & Theoretical Artificial Intelligence. 28:673-687
A new bio-inspired algorithm, namely Bird Swarm Algorithm (BSA), is proposed for solving optimisation applications. BSA is based on the swarm intelligence extracted from the social behaviours and social interactions in bird swarms. Birds mainly have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d7f61e264d4aa36319114f01ee92dfb
https://doi.org/10.1080/0952813x.2015.1042530
https://doi.org/10.1080/0952813x.2015.1042530
Publikováno v:
International Journal of Hybrid Information Technology. 8:383-396
A novel hybrid Bat Algorithm (BA) with the Differential Evolution (DE) strategy using the feasibility-based rules, namely BADE is proposed to deal with the constrained optimization problems. The sound interferences induced by other things are inevita
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::923aab0c737b92afcece23f1a576a3fd
https://doi.org/10.14257/ijhit.2015.8.1.34
https://doi.org/10.14257/ijhit.2015.8.1.34
Autor:
Xian-Bing Meng, Han-Xiong Li
Publikováno v:
2017 International Conference on Fuzzy Theory and Its Applications (iFUZZY).
This paper proposes an improved probabilistic fuzzy logic system with Dempster-Shafer structure (DS-PFLS) for wind speed prediction. The Dempster-Shafer theory and 3-sigma results are integrated into probabilistic fuzzy logic system (PFLS) to address
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6c9eed53466050dab098cab3d8575b8
https://doi.org/10.1109/ifuzzy.2017.8311787
https://doi.org/10.1109/ifuzzy.2017.8311787
Publikováno v:
International Journal of Bio-Inspired Computation. 14:114
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc37e4f5ab1ea7926b97a561268bc263
https://doi.org/10.1504/ijbic.2019.101639
https://doi.org/10.1504/ijbic.2019.101639