Zobrazeno 1 - 10
of 493
pro vyhledávání: '"Gaussian mutation"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract Degenerative musculoskeletal disease known as Osteoarthritis (OA) causes serious pain and abnormalities for humans and on detecting at an early stage, timely treatment shall be initiated to the patients at the earliest to overcome this pain.
Externí odkaz:
https://doaj.org/article/9e652b14370b41b398694a0ec779bb93
Autor:
Chauhan, Sumika a, Vashishtha, Govind a, 1, ⁎, Kumar, Rajesh b, Zimroz, Radoslaw a, Kumar Gupta, Munish c, Kumar, Anil d
Publikováno v:
In Information Sciences August 2024 677
Publikováno v:
e-Prime: Advances in Electrical Engineering, Electronics and Energy, Vol 8, Iss , Pp 100555- (2024)
This paper develops the Gaussian Mutation Based Teaching-Learning Optimization (GMBTLO) to solve different reactive power dispatch problems. In GMBTLO, Gaussian random variables are instituted, which includes both the ‘Teacher phase’ as well as
Externí odkaz:
https://doaj.org/article/6c14b01b21174f47b0f7db55a1d8fcbf
Publikováno v:
IEEE Access, Vol 12, Pp 106359-106384 (2024)
Glowworm Swarm Optimization (GSO) is a population-based optimization algorithm that successfully solves numerous optimization problems. Nonetheless, the convergence speed required to reach optimal solutions can be made more efficient by skipping loca
Externí odkaz:
https://doaj.org/article/06cb438338a64ab5b365e51cd0aab532
Publikováno v:
IEEE Access, Vol 12, Pp 30796-30823 (2024)
The feature selection problem involves selecting a subset of relevant features to enhance the performance of machine learning models, crucial for achieving model accuracy. Its complexity arises from the vast search space, necessitating the applicatio
Externí odkaz:
https://doaj.org/article/cb087be5e28d4251b6c4247b22f4bb09
Publikováno v:
Alexandria Engineering Journal, Vol 81, Iss , Pp 469-488 (2023)
There are many tricky optimization problems in real life, and metaheuristic algorithms are the most effective way to solve optimization problems at a lower cost. The dung beetle optimization algorithm (DBO) is a more innovative algorithm proposed in
Externí odkaz:
https://doaj.org/article/be00921c8920406e91270fbd1d6f864a
Autor:
Lulu Liu, Shuaiqun Wang
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 7, Pp 12211-12239 (2023)
The objective of this paper is to design a fast and efficient immune algorithm for solving various optimization problems. The immune algorithm (IA), which simulates the principle of the biological immune system, is one of the nature-inspired algorith
Externí odkaz:
https://doaj.org/article/28cb550626b54893b3b625909a844e81
Publikováno v:
Jisuanji kexue yu tansuo, Vol 17, Iss 5, Pp 1057-1074 (2023)
To solve the shortcomings of sparrow search algorithm (SSA), such as falling into local extremum easily influenced by initial solution and slow convergence in late iteration, a multi-chaotic sparrow search algorithm based on learning mechanism (MMCS
Externí odkaz:
https://doaj.org/article/7e850e69a3434a288c75a434ce6ee15e
Publikováno v:
Mathematics, Vol 12, Iss 10, p 1470 (2024)
The slime mould algorithm may not be enough and tends to trap into local optima, low population diversity, and suffers insufficient exploitation when real-world optimization problems become more complex. To overcome the limitations of SMA, the Gaussi
Externí odkaz:
https://doaj.org/article/83c774bb184649e3b266fbb9fce5602b
Publikováno v:
Meikuang Anquan, Vol 54, Iss 2, Pp 166-173 (2023)
Aiming at the problem that it is difficult to accurately predict the height of water flowing fractured zone in coal mining subsidence disaster early warning modeling, a prediction model based on improved sparrow search algorithm (SSA) to optimize BP
Externí odkaz:
https://doaj.org/article/1d8f61e709ec485ab12c9c2148edf4c8