Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 103, P. 107431 - 107431
Published: Dec. 27, 2024
Language: Английский
Biomimetics, Journal Year: 2024, Volume and Issue: 9(1), P. 31 - 31
Published: Jan. 4, 2024
The slime mould algorithm (SMA) is a new swarm intelligence inspired by the oscillatory behavior of moulds during foraging. Numerous researchers have widely applied SMA and its variants in various domains field proved value conducting literatures. In this paper, comprehensive review introduced, which based on 130 articles obtained from Google Scholar between 2022 2023. study, firstly, theory described. Secondly, improved are provided categorized according to approach used apply them. Finally, we also discuss main applications SMA, such as engineering optimization, energy machine learning, network, scheduling image segmentation. This presents some research suggestions for interested algorithm, additional multi-objective discrete SMAs extending neural networks extreme learning machining.
Language: Английский
Citations
2
IEEE Transactions on Instrumentation and Measurement, Journal Year: 2024, Volume and Issue: 73, P. 1 - 9
Published: Jan. 1, 2024
We are aiming at the error problem of magnetometer while drilling, and an online geomagnetic compensation method based on magnetic inertial slime mold algorithm (MISMA) is proposed. First, by analyzing output strap-down magnetometer, model measurement established, parameters organized into solution vectors. Then, according to characteristics inertia sensor their relationship objective function ideal data, tangential Pearson inequality drill diameter, field modulus constraint conditions given. The upper lower bounds redefined decoupled data gyroscope data. regarded as fitness function, adaptive parameter designed control bounded global search range value vector. random step (RS) size local adaptively adjusted mode ratio, in-depth development threshold obtained combining value. Finally, simulation experiment actual drilling show that MISMA has lowest average iterations compared with (SMA) particle swarm optimization (PSO), respectively. convergence speed increased 49.7%, absolute tool azimuth angle can be kept within 2.81°, which improves measuring accuracy in borehole.
Language: Английский
Citations
2
Mathematics, Journal Year: 2024, Volume and Issue: 12(10), P. 1470 - 1470
Published: May 9, 2024
The slime mould algorithm may not be enough and tends to trap into local optima, low population diversity, suffers insufficient exploitation when real-world optimization problems become more complex. To overcome the limitations of SMA, Gaussian mutation (GM) with a novel strategy is proposed enhance SMA it named as SMA-GM. GM used increase which helps come out optima retain robust search capability. Additionally, oscillatory parameter updated incorporated set balance between exploration exploitation. By using greedy selection technique, this study retains an optimal position while ensuring algorithm’s rapid convergence. SMA-GM performance was evaluated by unconstrained, constrained, CEC2022 benchmark functions. results show that has capacity for global search, improved stability, faster rate convergence, ability solve constrained problems. Wilcoxon rank sum test illustrates there significant difference outcomes each compared algorithm. Furthermore, engineering problem such industrial refrigeration system (IRS), operation alkylation unit problem, welded beam tension/compression spring design are solved, prove better efficiency reach optimum value.
Language: Английский
Citations
2
Applied Sciences, Journal Year: 2024, Volume and Issue: 14(16), P. 7297 - 7297
Published: Aug. 19, 2024
The increase in installed PV capacity worldwide and the intermittent nature of solar resources highlight importance power prediction for grid integration this technology. Therefore, there is an urgent need effective model, but choice model hyperparameters greatly affects performance. In paper, a multi-strategy improved snowmelt algorithm (MISAO) proposed optimizing intrinsic computing-expressive empirical mode decomposition with adaptive noise (ICEEMDAN) weighted least squares support vector machine forecasting. Firstly, cyclic chaotic mapping initialization strategy used to generate uniformly distributed high-quality population, which facilitates enter appropriate search domain quickly. Secondly, Gaussian diffusion enhances local exploration ability intelligences extends their solution space, effectively preventing them from falling into optima. Finally, stochastic follower employed reserve better candidate solutions next iteration, thus achieving robust exploration–exploitation balance. With these strategies, optimization performance MISAO comprehensively improved. order evaluate MISAO, series numerical experiments were conducted using IEEE CEC2017 test sets, effectiveness each improvement was verified. terms accuracy, convergence speed, robustness, scalability, compared basic SAO, various state-of-the-art optimizers, some recently developed algorithms. results showed that overall excellent, Friedman average rankings 1.80 1.82 two comparison experiments. most cases, delivered more accurate reliable than its competitors. addition, altered applied selection ICEEMDAN-WLSSVM seven neural network models, including WLSSVM, ICEEMDAN-WLSSVM, MISAO-ICEEMDAN-WLSSVM, predict under three different weather types. models have high accuracy stability. MAPE, MAE RMSE reduced by at 25.3%, 17.8% 13.3%, respectively. This method useful predicting output power, conducive economic dispatch stable operation system.
Language: Английский
Citations
2
KSCE Journal of Civil Engineering, Journal Year: 2024, Volume and Issue: 28(10), P. 4436 - 4456
Published: Jan. 1, 2024
Language: Английский
Citations
1
AIP Advances, Journal Year: 2024, Volume and Issue: 14(8)
Published: Aug. 1, 2024
In this paper, a novel Gyro Fireworks Algorithm (GFA) is proposed by simulating the behaviors of gyro fireworks during display process, which adopts framework multi-stage and multiple search strategies. At beginning iteration, are full gunpowder; they move via Lévy flight spiral rotation, sprayed sparks widely distributed more balanced, an effective global exploration method. later iteration stages, due to consumption gunpowder, gradually undergo aggregation contraction conducive group exploit local area near optimal position. The GFA divides iterative process into four phases, each phase different strategy, in order enhance diversity population balance capability space exploitation space. verify performance GFA, it compared with latest algorithms, such as dandelion optimizer, Harris Hawks Optimization (HHO) algorithm, gray wolf slime mold whale optimization artificial rabbits optimization, 33 test functions. experimental results show that obtains solution for all algorithms on 76% functions, while second-placed HHO algorithm only 21% Meanwhile, has average ranking 1.8 CEC2014 benchmark set 1.4 CEC2019 set. It verifies paper better convergence robustness than competing algorithms. Moreover, experiments challenging engineering problems confirm superior over alternative
Language: Английский
Citations
1
Biomedical Signal Processing and Control, Journal Year: 2023, Volume and Issue: 87, P. 105423 - 105423
Published: Sept. 21, 2023
Language: Английский
Citations
3
Published: Sept. 8, 2023
Slime Mould Algorithm (SMA) is a new swarm intelligence algorithm inspired by the oscillatory behavior of slime molds during foraging. Numerous researchers have widely applied SMA and its variants in various domains proved value experiments literatures. In this paper comprehensive survey on introduced, which based 130 articles visa Google-scholar between 2022 July, 2023. Firstly, theory described. Secondly improved are provided categorized according to approach that they with. Finally, it also discusses main applications such as engineering optimization, energy machine learning, network, scheduling image segmentation etc. This review presents some research suggestion for researcher who interested algorithm.
Language: Английский
Citations
1
Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 173, P. 108294 - 108294
Published: March 13, 2024
Language: Английский
Citations
0
Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 103, P. 107431 - 107431
Published: Dec. 27, 2024
Language: Английский
Citations
0