Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In order to solve the mixed integer nonlinear problem (MINLP), a data offloading selection strategy based on proximity discovery and an iterative method-based resource allocation algorithm (IRA) are proposed. In addition, the closed-form solutions of the optimized variables are obtained. …”
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Flood resilience assessment of region based on TOPSIS-BOA-RF integrated model by Guofeng Wen, Fayan Ji

“…Training samples are then input into the Butterfly Optimization Algorithm(BOA) to optimize the key parameters in the Random Forest(RF). …”
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Enhancing and Generalizing Position-Velocity Tracking in Imperfect <italic>mm</italic>Wave Systems Using a Low-Complexity Neural Network by Deeb Assad Tubail, Mohammed Zourob, Salama Ikki

“…To manage the computational demands of the training phase, we employ a low-complexity algorithm, the Extreme Learning Machine (ELM), which calculates weights and biases through closed-form solution, avoiding complex optimization processes. …”
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User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…To address these challenges, we propose MHORANFed, a novel optimization algorithm tailored to minimize learning time and resource usage costs while preserving model performance within a mobility-aware hierarchical FL framework for O-RAN. …”
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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition by Mashael Maashi, Huda G. Iskandar, Mohammed Rizwanullah

“…Finally, the attraction-repulsion optimization algorithm (AROA) adjusts the hyperparameter values of the CNN-BiGRU-A method optimally, resulting in more excellent classification performance. …”
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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…The method automatically identifies clusters of varying densities while filtering out noise, ensuring a more precise change detection process. …”
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Enhancing Physical Layer Security in WPCNs With IRS and Controlled Jamming for 6G IoT Applications by Iqra Hameed, Abid Afridi, Myung-Sun Baek, Hyoung-Kyu Song

“…To address the non-convex nature of the problem, we develop an alternating optimization algorithm that decouples the problem into subproblems, ensuring efficient convergence to a locally optimal solution. …”
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Artificial intelligence approach to magnetohydrodynamic flow of non-Newtonian fluids over a wedge: Thermophoresis and Brownian motion effects by Talal Taha, Sohaib Abdal, Liaqat Ali, Rana Muhammad Zulqarnain, Se-Jin Yook

“…ODEs are first solved numerically using MATLAB’s bvp4c function, a known solver of boundary value problems known to solve complex ODEs within fluid dynamics very effectively. Further optimization and simplification of the analysis are achieved by using an artificial neural networking base Levenberg Marquardt algorithm (ANN-LMA) model. …”
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Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…This study proposes a systematic framework, termed VMD-RUN-Seq2Seq-Attention, for noise reduction, outlier detection, and wind speed prediction by integrating Variational Mode Decomposition (VMD), the Runge–Kutta optimization algorithm (RUN), and a Sequence-to-Sequence model with an Attention mechanism (Seq2Seq-Attention). …”
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MAPE-ViT: multimodal scene understanding with novel wavelet-augmented Vision Transformer by Muhammad Waqas Ahmed, Touseef Sadiq, Hameedur Rahman, Sulaiman Abdullah Alateyah, Mohammed Alnusayri, Mohammed Alatiyyah, Dina Abdulaziz AlHammadi

“…The feature discrimination capability is further enhanced through optimization using the Gray Wolf algorithm. The processed features then flow into a dual-stream architecture, where an extreme learning machine handles multi-object classification, while conditional random fields (CRF) manage scene-level categorization. …”
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Degree-Constrained k-Minimum Spanning Tree Problem by Pablo Adasme, Ali Dehghan Firoozabadi

“…Our numerical results indicate that the proposed models and algorithms allow obtaining optimal and near-optimal solutions, respectively. …”
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Mechanistic insights into synergistic effects using coupled PK-PD modeling by Jinzhou Sun, Qianqian Chen, Chumeng Zhuang, Xiaohong Li, Li Yu, Weifeng Jin

“…The model also showed that CA had a larger apparent volume of distribution and clearance in rats, while HSYA had a shorter mean retention time and elimination half-life. …”
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Synergistic Effect of <i>Bacillus</i> and Chitosan: From Flocculation to Enhanced Antimicrobial Activity by Selena Dmitrović, Nataša Lukić, Ivana Danilov, Vanja Vlajkov, Jovana Grahovac, Aleksandar Jokić

“…The response surface approach, followed by desirability function optimization and the genetic algorithm were applied. …”
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Data-driven robust outpatient physician scheduling with medical visiting information by Qingyun He, Shuqun Shen, Zhiyu Lv, Shixin Yang

“…In this study, we develop a data-driven optimization framework for a mid-term period spanning several weeks within the outpatient department of a dermatology hospital. …”
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Externally bonded reinforcement side extended (EBRSE) technique to postpone debonding of FRP laminates in strengthened concrete elements by Mehdi Aghabagloo, Laura Carreras, Cristina Barris, Alba Codina, Marta Baena

“…Additionally, a numerical approach was applied, combining the finite difference method with a metaheuristic optimization algorithm, to derive the bond-slip law governing the constitutive behavior of both systems. …”
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Energy-Efficient Dual-Iteration Power Allocation for Two-Phase Relay System with Massive Antennas by Long Zhao, Wei Xiang, Jie Mei, Hui Zhao, Hang Long, Lin Li

“…Numerical results show that the proposed DIPA algorithms can greatly improve EE while guaranteeing spectrum efficiency (SE) when compared with the equal power allocation algorithm. …”
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Machine learning-driven multi-targeted drug discovery in colon cancer using biomarker signatures by Tingting Liu, Lifan Zhong, Xizhe Sun, Zhijiang He, Witiao Lv, Liyun Deng, Yanfei Chen

“…The artificial intelligence model personalizes therapy by leveraging patient-specific molecular profiles, optimizing drug selection and dosage while minimizing side effects. …”
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Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

“…To reduce model complexity and improve deployment feasibility, a metaheuristic optimization algorithm was incorporated that significantly reduces computational overhead without compromising performance. …”
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A generative deep neural network for pan-digestive tract cancer survival analysis by Lekai Xu, Tianjun Lan, Yiqian Huang, Liansheng Wang, Junqi Lin, Xinpeng Song, Hui Tang, Haotian Cao, Hua Chai

“…Results In this study, we propose GDEC, a multi-task generative deep neural network designed for precise digestive tract cancer subtyping. The network optimization process involves employing an integrated loss function consisting of two modules: the generative-adversarial module facilitates spatial data distribution understanding for extracting high-quality information, while the clustering module aids in identifying disease subtypes. …”
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ENHANCING GRID INTEGRATION OF A SINGLE-PHASE SOLAR INVERTER THROUGH ADVANCED CONTROL TECHNIQUES AND REAL-TIME VALIDATION by Anupama Subhadarsini, Babita Panda, Byamakesh Nayak

“…The CMAES-CMBO algorithm optimizes the controller's parameters. Comparative analysis of the CMAES-CMBO-HFF-2DoF-FOTIDC controller with other state-of-the-art controllers demonstrates its superior performance and effectiveness. …”
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