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pro vyhledávání: '"Stephen A. Adubi"'
Publikováno v:
Algorithms, Vol 15, Iss 11, p 405 (2022)
Hyper-heuristics are widely used for solving numerous complex computational search problems because of their intrinsic capability to generalize across problem domains. The fair-share iterated local search is one of the most successful hyper-heuristic
Externí odkaz:
https://doaj.org/article/7490500e40c14f22a720f66b2941e5d0
Publikováno v:
Journal of Computer Science. 17:330-348
In the literature, several methods explored to analyze breast cancer dataset have failed to sufficiently handle quantitative attribute sharp boundary problem to resolve inter and intra uncertainties in breast cancer dataset analysis. In this study an
Publikováno v:
CEC
Hyper-heuristics are general-purpose heuristic search methodologies for solving combinatorial optimization problems (COPs). Research findings have revealed that hyper-heuristics still suffer generalization issues as different strategies vary in perfo
Autor:
Stephen A. Adubi, Sanjay Misra
Publikováno v:
Arabian Journal for Science and Engineering. 41:3089-3097
Compression of texts has been widely studied by various researchers and in the process, several algorithms have been proposed. However, compression of texts using the syllabic structure of words in syllable-based languages has emerged as another dime
Publikováno v:
Cogent Engineering, Vol 7, Iss 1 (2020)
This paper focused on applying social network analysis techniques to co-authorship network in order to discover the influencers in Civil engineering research field in Nigeria. It further applies the Latent Dirichlet allocation (LDA) algorithm to unco
Autor:
Sanjay Misra, Stephen A. Adubi
Publikováno v:
2014 11th International Conference on Electronics, Computer and Computation (ICECCO).
colony algorithms which is part of the swarm intelligence methods. It is a probabilistic technique for finding close to optimal paths through a problem space. The ant colony optimization algorithms therefore mimic the behavior of natural ants with th
Publikováno v:
Cogent Engineering, Vol 7, Iss 1 (2020)
This paper focused on applying social network analysis techniques to co-authorship network in order to discover the influencers in Civil engineering research field in Nigeria. It further applies the Latent Dirichlet allocation (LDA) algorithm to unco
Externí odkaz:
https://doaj.org/article/4bfad5f7ae0b4d5ba226e118f0258da2