Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…However, the MPC’s performance depends on the optimal tuning of its key parameters, a challenge addressed using the Multivariate Gaussian Mixture Model Continuous Ant Colony Optimization (MGMM-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>ACO</mi><mi>R</mi></msub></semantics></math></inline-formula>) algorithm. …”
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Deployment of On-Orbit Service Vehicles Using a Fuzzy Adaptive Particle Swarm Optimization Algorithm by Yaxiong Li, Xinglong Sun, Xinxue Liu, Jian Wu, Qingguo Liu

“…Second, an assignment optimization model of OSVs is established based on the discrete particle swarm optimization (DPSO) algorithm, laying the foundation of the next optimization model. …”
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A hybrid deep learning and differential evolution approach for accurate fake news detection by Shailendra Pratap Singh, Naween Kumar, Gyanendra Kumar, Ahamed Shafeeq B.M.

“…The proposed framework integrates Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and attention mechanisms for robust feature extraction and classification. By leveraging DE optimization, the model fine-tunes its parameters for improved convergence and detection performance. …”
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An Improved Galerkin Framework for Solving Unsteady High-Reynolds Navier–Stokes Equations by Jinlin Tang, Qiang Ma

“…This error indicator guides an AMR algorithm that combines longest-edge bisection with local Delaunay re-triangulation, ensuring optimal mesh adaptation to complex flow features such as boundary layers and vortices. …”
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Predicting the Recurrence of Differentiated Thyroid Cancer Using Whale Optimization-Based XGBoost Algorithm by Keshika Shrestha, H. M. Jabed Omur Rifat, Uzzal Biswas, Jun-Jiat Tiang, Abdullah-Al Nahid

“…Both of our algorithms optimize the hyperparameters of the Extreme Gradient Boosting (XGBoost) model to increase the overall performance. …”
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Safety Helmet Wearing Detection Based on Jetson Nano and Improved YOLOv5 by Zaihui Deng, Chong Yao, Qiyu Yin

“…Finally, the YOLOv5-SN network is obtained by improving the YOLOv5 model, and the optimized model is deployed on Jetson Nano for testing. …”
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Dual-Closed-Loop Control System for Polysilicon Reduction Furnace Power Supply Based on Hysteresis PID and Predictive Control by Shihao Li, Tiejun Zeng, Shan Jian, Guiping Cui, Ziwen Che, Genghong Lin, Zeyu Yan

“…Meanwhile, the outer loop employs a hybrid MFAC-based improved PID algorithm to optimize the temperature tracking performance, achieving precise temperature control even in the presence of system uncertainties. …”
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Multi-objective optimization of sustainable cement-zeolite improved sand based on life cycle assessment and artificial intelligence [version 1; peer review: 1 approved, 2 approved... by Hossein MolaAbasi, Satinder Kaur Brar, Amin Tanhadoust, Sepideh Nasrollahpour, Omolbanin Ataee, Moncef L. Nehdi

“…Through a tuning process, the BPNN model found the optimal architecture and accurately predicted the unconfined compressive strength of cement-zeolite improved sand systems. …”
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Optimized Rate Control Algorithm of High-Efficiency Video Coding Based on Region of Interest by Renjie Song, Yuandong Zhang

“…Firstly, the algorithm extracts the region of interest of video frames based on time and space domains by using the improved Itti model. …”
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Image cluster algorithm of hybrid encoding method by Chun-hui ZHAO, Xue-yuan LI, Ying CUI

“…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. by Afnan M Alhassan, Nouf I Altmami

“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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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

“…The parameters were estimated by conducting experimental power measurements and comparing the results with the real ones predicted by the equations model using the root mean square error. The Multiverse Optimization Algorithm demonstrates superior performance compared to other algorithms presented in previous works for this case. …”
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Enhancing analogy-based software cost estimation using Grey Wolf Optimization algorithm by Taghi Javdani Gandomani, Maedeh Dashti, Sadegh Ansaripour, Hazura Zulzalil

“…Among the software estimation methods, analogy-based estimation (ABE) is one of the most popular ones. Although this method has been customized in recent years with the help of optimization algorithms to achieve better results, the use of more powerful optimization algorithms can be effective in achieving better results in software size estimation. …”
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Residential Building Energy Usage Prediction Using Bayesian-Based Optimized XGBoost Algorithm by Nabaa Riyadh Baqer, Parviz Rashidi-Khazaee

“…To enhance the performance of XGB and improve prediction reliability, we propose a novel Bayesian optimization approach using the Tree-Structured Parzen Estimator (TPE), leading to the development of the TPE-XGB model for HL and CL estimation. …”
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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…In terms of the robustness of the algorithm and the overall performance comparison of different methods,the proposed algorithm can extract the formant robustly from order 9 to 22, and the model algorithm shows the optimal performance when the formant is extracted from order 18. …”
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A novel methodological approach to SaaS churn prediction using whale optimization algorithm. by Muhammed Kotan, Ömer Faruk Seymen, Levent Çallı, Sena Kasım, Burcu Çarklı Yavuz, Tijen Över Özçelik

“…This study introduces a novel approach to SaaS churn prediction using the Whale Optimization Algorithm (WOA) for feature selection. Results show that WOA-reduced datasets improve processing efficiency and outperform full-variable datasets in predictive performance. …”
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A green hydrogen production model from solar powered water electrolyze based on deep chaotic Lévy gazelle optimization by Heba Askr, Mahmoud Abdel-Salam, Václav Snášel, Aboul Ella Hassanien

“…DeepGaz combines a new Chaotic-Lévy variant of the gazelle optimization algorithm (CGOA) with a recurrent neural network (RNN/LSTM) for hyperparameter optimization. …”
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…The simulation results show that the neural network model can be applied to the prediction of stratospheric wind field and the BP neural networks optimized by genetic algorithm and particle swarm optimization can greatly improve the prediction accuracy of BP neural network, and the forecast wind speed is following the true value in a certain period of time. …”
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A Distributed Optimization Algorithm for Energy of Wireless Sensor Networks Based on Potential Game by Lingfeng Shao, Junjie Yang, Jicheng Fang

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Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model by Yiqing Yang, Guoyin Zhang, Yanxia Wu, Zhixiang Zhao, Yan Fu

“…Additionally, the Top-K algorithm optimizes the diagnostic model through a policy network loss function, effectively reducing the number of symptoms and diseases processed and improving the system’s response speed by 1.3–1.9 times compared to the state-of-the-art differential diagnosis systems.…”
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