Ocean Engineering, Год журнала: 2024, Номер 312, С. 119300 - 119300
Опубликована: Сен. 24, 2024
Язык: Английский
Agriculture, Год журнала: 2024, Номер 14(10), С. 1701 - 1701
Опубликована: Сен. 28, 2024
Tea polyphenols (TPs) are a critical indicator for evaluating the quality of tea leaves and esteemed their beneficial effects. The non-destructive detection this component is essential enhancing precise control in production improving product quality. This study developed an enhanced PKO-SVR (support vector regression based on Pied Kingfisher Optimization Algorithm) model rapidly accurately detecting polyphenol content Fu brick using hyperspectral reflectance data. During experiment, chemical analysis determined content, while imaging captured spectral Data preprocessing techniques were applied to reduce noise interference improve prediction model. Additionally, several other models, including K-nearest neighbor (KNN) regression, neural network (BP), support sparrow algorithm (SSA-SVR), particle swarm optimization (PSO-SVR), established comparison. experiment results demonstrated that improved excelled predicting (R2 = 0.9152, RMSE 0.5876, RPD 3.4345 test set) also exhibited faster convergence rate. Therefore, data combined with presented proved effective tea’s content.
Язык: Английский
Процитировано
3
Energies, Год журнала: 2024, Номер 17(21), С. 5296 - 5296
Опубликована: Окт. 24, 2024
In the off-grid photovoltaic DC microgrid, traditional droop control encounters challenges in effectively adjusting coefficient response to varying power fluctuation frequencies, which can be influenced by factors such as line impedance. This paper introduces a novel Multi-strategy Harris Hawk Optimization Algorithm (MHHO) that integrates variable universe fuzzy theory with develop an adaptive strategy. The algorithm employs Fuch mapping evenly distribute initial population across solution space and incorporates logarithmic spiral improved weight strategies during both exploration exploitation phases, enhancing its ability escape local optima. A comparative analysis against five classical meta-heuristic algorithms on CEC2017 benchmarks demonstrates superior performance of proposed algorithm. Ultimately, based MHHO dynamically optimizes mitigate negative impact internal system achieve balanced distribution between battery super-capacitor microgrid. Through MATLAB/Simulink simulations, it is demonstrated strategy limit range bus voltage within ±0.75%, enhance robustness stability system, optimize charge discharge energy storage unit.
Язык: Английский
Процитировано
3
Cluster Computing, Год журнала: 2024, Номер 28(2)
Опубликована: Ноя. 26, 2024
Язык: Английский
Процитировано
3
Symmetry, Год журнала: 2024, Номер 16(9), С. 1173 - 1173
Опубликована: Сен. 6, 2024
The osprey optimization algorithm (OOA) is a metaheuristic with simple framework, which inspired by the hunting process of ospreys. To enhance its searching capabilities and overcome drawbacks susceptibility to local optima slow convergence speed, this paper proposes modified (MOOA) integrating multiple advanced strategies, including Lévy flight strategy, Brownian motion strategy an RFDB selection method. are used algorithm’s exploration ability. method conducive search for global optimal solution, symmetrical strategy. Two sets benchmark functions from CEC2017 CEC2022 employed evaluate performance proposed By comparing eight other algorithms, experimental results show that MOOA has significant improvements in solution accuracy, stability, speed. Moreover, efficacy tackling real-world problems demonstrated using five engineering design problems. Therefore, potential solve complex more effectively.
Язык: Английский
Процитировано
2
Ocean Engineering, Год журнала: 2024, Номер 312, С. 119300 - 119300
Опубликована: Сен. 24, 2024
Язык: Английский
Процитировано
1