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  1. 21

    Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

    Published 2025-07-01
    “…This study proposes a novel approach for continuous knee joint angle prediction based on surface electromyography (sEMG), integrating an Improved Zebra Optimization Algorithm (IZOA) with an attention-enhanced Gated Recurrent Unit (GRU) network. …”
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    Article
  2. 22

    Improved Nonprobabilistic Global Optimal Solution Method and Its Application in Bridge Reliability Assessment by Xiaoya Bian, Xuyong Chen, Hongyin Yang, Chen You

    Published 2019-01-01
    “…Utilizing the improved one-dimensional optimization algorithm conveniently solved the nonprobabilistic reliability index, however, only searching the part of probable failure points. …”
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    Article
  3. 23

    Improved Electrochemical–Mechanical Parameter Estimation Technique for Lithium-Ion Battery Models by Salvatore Scalzo, Davide Clerici, Francesca Pistorio, Aurelio Somà

    Published 2025-06-01
    “…An error analysis—based on the Root Mean Square Error (RMSE) and confidence ellipses—confirms that the inclusion of mechanical measurements significantly improves the accuracy of the identified parameters and the reliability of the algorithm compared to approaches relying just on electrochemical data. …”
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  4. 24

    Improvement analysis of organic light emitting diode temperature control by integrating whale algorithm in PID control system. by Dayu Zhang, Cong Guan

    Published 2025-01-01
    “…To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”
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    Article
  5. 25

    An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

    Published 2023-01-01
    “…To address this problem, the velocity update equation of the original PSO algorithm is modified by incorporating a dynamic linear decreasing inertia weight, which improves the PSO algorithm’s convergence behaviour and aids both local and global search. …”
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    Article
  6. 26

    Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

    Published 2025-12-01
    “…The goals of this study were to (i) identify optimal spectral indices and texture features from RGB and multispectral (MS) images and (ii) improve the accuracy of PNC prediction by combining optimal features with ML. …”
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    Article
  7. 27

    Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

    Published 2025-08-01
    “…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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  8. 28
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    An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

    Published 2025-04-01
    “…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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    Article
  10. 30

    Research on the Gas Emission Quantity Prediction Model of Improved Artificial Bee Colony Algorithm and Weighted Least Squares Support Vector Machine (IABC-WLSSVM) by Lei Wang, Jinghang Li, Wenbo Zhang, Yu Li

    Published 2022-01-01
    “…At the same time, the improved artificial bee colony algorithm is used to optimize the kernel width σ and regularization parameter λ of WLSSVM, which improves the prediction accuracy and convergence rate of WLSSVM. …”
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    Article
  11. 31

    (IoT) Network intrusion detection system using optimization algorithms by Luo Shan

    Published 2025-07-01
    “…Abstract To address the complex requirements of network intrusion detection in IoT environments, this study proposes a hybrid intelligent framework that integrates the Whale Optimization Algorithm (WOA) and the Grey Wolf Optimization (GWO) algorithm—referred to as WOA-GWO. …”
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  12. 32

    RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

    Published 2025-01-01
    “…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. To overcome this limitation, we propose the RRMSE (Relative Root Mean Square Error) Voting Regressor, a new ensemble regression technique that assigns weights to each base model based on their relative error rates. …”
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  13. 33

    Earthworm optimization algorithm for extracting parameters for solar cells and photovoltaic modules by Fatima Wardi, Mohamed Louzazni, Mohamed Hanine

    Published 2025-08-01
    “…In this paper, we deal with the use of the earthworm optimization algorithm (EOA) in foraging to estimate and extract the intrinsic electrical parameters of single-, double-, and triple-diode solar cells and photovoltaic modules across different technologies. …”
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  14. 34

    Control Optimization of Stochastic Systems Based on Adaptive Correction CKF Algorithm by FengJun Hu, Qian Zhang, Gang Wu

    Published 2020-01-01
    “…The control model is established by using the CKF algorithm, the covariance matrix of standard CKF is optimized by square root filter, the adaptive correction of error covariance matrix is realized by adding memory factor to the filter, and the disturbance factors in nonlinear time-varying discrete stochastic systems are eliminated by multistep feedback predictive control strategy, so as to improve the robustness of the algorithm. …”
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  15. 35

    An enhanced fruit fly optimization algorithm with random spare and double adaptive weight strategies for oil and gas production optimization by Xu Wang, Jingfu Shan

    Published 2025-08-01
    “…In this study, we propose an enhanced evolutionary algorithm tailored for global optimization and oil and gas production improvement. …”
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    Article
  16. 36

    Enhanced CO<sub>2</sub> Emissions Prediction Using Temporal Fusion Transformer Optimized by Football Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally

    Published 2025-05-01
    “…Feature selection using the Football Optimization Algorithm (FbOA) significantly improved its performance, reducing the RMSE to 0.018798774. …”
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  17. 37

    Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

    Published 2025-12-01
    “…In addition, it examines 2,000 random surface soil samples, ranging from 0 to 20 cm, that were optimized using genetic algorithms (GA), particle swarm optimization (PSO), and Optuna. …”
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  18. 38

    An effective parameter estimation on thermoelectric devices for power generation based on multiverse optimization algorithm by Luis Fernando Grisales-Noreña, Vanessa Botero-Gómez, Rubén Iván Bolaños, Faustino Moreno-Gamboa, Daniel Sanin-Villa

    Published 2025-03-01
    “…These results improve over those obtained by the Ant Lion Optimizer, which reported a minimum root mean square error of 0.001804 and a root mean square error of 0.001896 on average with a standard deviation of 3.788%.Additionally, the study highlights the efficiency of the Multiverse Optimization Algorithm in processing time, with an average execution time of 223.65 seconds. …”
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